Authors,Author(s) ID,Title,Year,Source title,Volume,Issue,Art. No.,Page start,Page end,Page count,Cited by,DOI,Link,Affiliations,Authors with affiliations,Abstract,Author Keywords,Index Keywords,Molecular Sequence Numbers,Chemicals/CAS,Tradenames,Manufacturers,Funding Details,Funding Text 1,Funding Text 2,References,Correspondence Address,Editors,Sponsors,Publisher,Conference name,Conference date,Conference location,Conference code,ISSN,ISBN,CODEN,PubMed ID,Language of Original Document,Abbreviated Source Title,Document Type,Publication Stage,Open Access,Source,EID
"Costin A., Adibfar A., Hu H., Chen S.S.","55200193500;57202945239;55740744300;7410262310;","Building Information Modeling (BIM) for transportation infrastructure – Literature review, applications, challenges, and recommendations",2018,"Automation in Construction","94",,,"257","281",,216,"10.1016/j.autcon.2018.07.001","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049913864&doi=10.1016%2fj.autcon.2018.07.001&partnerID=40&md5=7cb03d0a71127e349a5b5194ee805ecb","M.E. Rinker, Sr. School of Construction Management, University of Florida, P.O. Box 115703, Gainesville, FL  32611, United States; Michael Baker International, 100 Airside Dr., Moon Township, PA  15108, United States; Department of Civil, Structural and Environmental Engineering, The State University of New York at Buffalo, United States","Costin, A., M.E. Rinker, Sr. School of Construction Management, University of Florida, P.O. Box 115703, Gainesville, FL  32611, United States; Adibfar, A., M.E. Rinker, Sr. School of Construction Management, University of Florida, P.O. Box 115703, Gainesville, FL  32611, United States; Hu, H., Michael Baker International, 100 Airside Dr., Moon Township, PA  15108, United States; Chen, S.S., Department of Civil, Structural and Environmental Engineering, The State University of New York at Buffalo, United States","Transportation infrastructure is a critical component to a nation's economy, security, and wellbeing. In order to keep up with the rising population, there is a great need for more efficient and cost-effective technologies and techniques to not only repair the infrastructure, but also to advance and expand the transportation infrastructure to sustain the growing population. Building Information Modeling (BIM) has been widely adopted in the building industry, and its established methods and technologies show enormous potential in benefiting the transportation industry. The purpose of this paper is to present a literature review and critical analysis of BIM for transportation infrastructure. A total of 189 publications in the area of BIM for transportation infrastructure were reviewed, including journal articles, conference proceedings, and published reports. Additionally, schemas and file formats from 9 main categories and 34 areas related to transportation infrastructure were reviewed. An application was developed to collect, store, and analyze the publications. Various algorithms were developed and implemented to help in the automation and analysis of the review. The goal of this paper is to provide a comprehensive, up-to-date literature review and critical analysis of research areas regarding BIM for transportation infrastructure to further facilitate research and applications in this domain. Based on the results of the analysis, current topics and trends, applications and uses, emerging technologies, benefits, challenges and limitations, research gaps, and future needs are discussed. Significantly, the contribution of this paper is providing the foundation of current research, gaps, and emerging technologies needed to facilitate further research and applications for both academia and industry stakeholders to develop more efficient and cost-effective techniques necessary to repair, advance, and expand the transportation infrastructure. Furthermore, the results show that the use of BIM for transportation infrastructure has been increasing, although the research has mainly been focusing on roads, highways, and bridges. The results also reveal a major need for a standard neutral exchange format and schema to promote interoperability. Most importantly, the continuing collaboration between academia and industry is required to mitigate most challenges and to realize the full potential of BIM for transportation infrastructure. © 2018 Elsevier B.V.","Bridge Information Modeling (BrIM); Building Information Modeling (BIM); Civil information Modeling (CiM); Civil Integrated Management (CIM); Emerging technologies; Industry Foundation Classes (IFC); Literature review; Transportation infrastructure","Bridges; Construction industry; Cost effectiveness; Information theory; Repair; Building Information Model - BIM; Emerging technologies; Industry Foundation Classes - IFC; Information Modeling; Integrated management; Literature reviews; Transportation infrastructures; Architectural design",,,,,,,,"About the National BIM Standard-United States (2016), https://www.nationalbimstandard.org/about, (Accessed 8 June 2017); United States national building information modeling standard version 1—part 1: overview, principles, and methodologies (2007) Final Report, The Northern American Chapter of buildingSMART International (bSI), Washington, DC, , https://buildinginformationmanagement.files.wordpress.com/2011/06/nbimsv1_p1.pdf, (Accessed 24 October 2017); Kim, J.U., Kim, Y.J., Ok, H., Yang, S.H., (2015) A study on the status of infrastructure BIM and BIM library development, Proc. in International Conference on Computational Science and Computational Intelligence (CSCI), December 7–9, Las Vegas, Nevada, pp. 857-858; Bae, A., Lee, D., Park, B., BIM utilization for optimizing milling quantity and HMA pavement overlay quality (2016) Can. 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Box 115703, United States; email: aaron.costin@ufl.edu",,,"Elsevier B.V.",,,,,09265805,,AUCOE,,"English","Autom Constr",Article,"Final","",Scopus,2-s2.0-85049913864
"Lu R., Brilakis I.","57194640091;8837673400;","Digital twinning of existing reinforced concrete bridges from labelled point clusters",2019,"Automation in Construction","105",,"102837","","",,72,"10.1016/j.autcon.2019.102837","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065641838&doi=10.1016%2fj.autcon.2019.102837&partnerID=40&md5=eb8619b2d5d7a3d5ac059918869928f6","School of Architecture, Building and Civil Engineering, Loughborough University, United Kingdom; Darwin College, University of Cambridge, United Kingdom; Laing O'Rourke Reader, Department of Engineering, University of Cambridge, United Kingdom","Lu, R., School of Architecture, Building and Civil Engineering, Loughborough University, United Kingdom, Darwin College, University of Cambridge, United Kingdom; Brilakis, I., Laing O'Rourke Reader, Department of Engineering, University of Cambridge, United Kingdom","The automation of digital twinning for existing reinforced concrete bridges from point clouds remains an unresolved problem. Whilst current methods can automatically detect bridge objects in point clouds in the form of labelled point clusters, the fitting of accurate 3D shapes to point clusters remains largely human dependent largely. 95% of the total manual modelling time is spent on customizing shapes and fitting them correctly. The challenges exhibited in the fitting step are due to the irregular geometries of existing bridges. Existing methods can fit geometric primitives such as cuboids and cylinders to point clusters, assuming bridges are comprised of generic shapes. However, the produced geometric digital twins are too ideal to depict the real geometry of bridges. In addition, none of the existing methods have explicitly demonstrated how to evaluate the resulting Industry Foundation Classes bridge data models in terms of spatial accuracy using quantitative measurements. In this article, we tackle these challenges by delivering a slicing-based object fitting method that can generate the geometric digital twin of an existing reinforced concrete bridge from four types of labelled point cluster. The quality of the generated models is gauged using cloud-to-cloud distance-based metrics. Experiments on ten bridge point cloud datasets indicate that the method achieves an average modelling distance of 7.05 cm (while the manual method achieves 7.69 cm), and an average modelling time of 37.8 s. This is a huge leap over the current practice of digital twinning performed manually. © 2019 Elsevier B.V.","BIM; BrIM; Digital twin; IFC; Point cloud data","Concrete bridges; Geometry; Object detection; Railroad bridges; BrIM; Digital twin; Existing reinforced concrete; Geometric primitives; Industry Foundation Classes - IFC; Irregular geometries; Point cloud data; Quantitative measurement; Reinforced concrete",,,,,"Engineering and Physical Sciences Research Council, EPSRC: 31109806.0007, EP/L010917/1","This research work is supported by EPSRC , Infravation SeeBridge project under Grant Number No. 31109806.0007 , and Cambridge Trimble Fund . We would like to thank for their supports. 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"Jeong S., Hou R., Lynch J.P., Sohn H., Law K.H.","56893042300;57190580657;7403674374;7201426396;55671078700;","An information modeling framework for bridge monitoring",2017,"Advances in Engineering Software","114",,,"11","31",,54,"10.1016/j.advengsoft.2017.05.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019995271&doi=10.1016%2fj.advengsoft.2017.05.009&partnerID=40&md5=b81eda4ea474eff91bfb1ce783057d61","Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States; Department of Civil and Environmental Engineering, University of Michigan, 2350 Hayward St., Ann Arbor, MI  48109-2125, United States; Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States","Jeong, S., Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States; Hou, R., Department of Civil and Environmental Engineering, University of Michigan, 2350 Hayward St., Ann Arbor, MI  48109-2125, United States; Lynch, J.P., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States; Sohn, H., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States; Law, K.H., Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States","Bridge management involves a variety of information from different data sources, including geometric model, analysis model, bridge management system (BMS) and structural health monitoring (SHM) system. Current practice of bridge management typically handles these diverse types of data using isolated systems and operates with limited use of the data. Sharing and integration of such information would facilitate meaningful use of the information and improve bridge management, as well as enhance bridge operation and maintenance and public safety. In many industries, information models and interoperability standards have been developed and employed to facilitate information sharing and collaboration. Given the success of building information modeling (BIM) in the Architecture, Engineering and Construction (AEC) industry, efforts have been initiated to develop frameworks and standards for bridge information modeling (BrIM). Current developments of BrIM focus primarily on the physical descriptions of bridge structures, such as geometry and material properties. This paper presents an information modeling framework for supporting bridge monitoring applications. The framework augments and extends the prior work on the OpenBrIM standards to further capture the information relevant to engineering analysis and sensor network. Implementation of the framework employs an open-source NoSQL database system for scalability, flexibility and performance. The framework is demonstrated using bridge information and sensor data collected from the Telegraph Road Bridge located in Monroe, Michigan. The results show that the bridge information modeling framework can potentially facilitate the integration of information involved in bridge monitoring applications, and effectively support and provide services to retrieve and utilize the information. © 2017","Bridge information modeling; Bridge management; Bridge monitoring; NoSQL database","Architectural design; Information theory; Network function virtualization; Open systems; Sensor networks; Standards; Structural health monitoring; Architecture , engineering and construction industries; Bridge management; Bridge monitoring; Building Information Model - BIM; Information Modeling; Information modeling frameworks; Nosql database; Structural health monitoring (SHM); Information management",,,,,"ECCS-1446330; National Sleep Foundation, NSF; Michigan Department of Transportation, MDOT; Center for Social Inclusion, CSI; Stanford University, SU; University of Michigan, U-M; Ministry of Land, Infrastructure and Transport, MOLIT; Korea Agency for Infrastructure Technology Advancement, KAIA","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA). The research is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. Any opinions, findings, conclusions or recommendations expressed in this paper are solely those of the authors and do not necessarily reflect the views of NSF, MOLIT, MDOT, KAIA or any other organizations and collaborators.","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) . The research is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. 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"Perry B.J., Guo Y., Atadero R., van de Lindt J.W.","57217167354;55873076900;23988525500;6701580121;","Streamlined bridge inspection system utilizing unmanned aerial vehicles (UAVs) and machine learning",2020,"Measurement: Journal of the International Measurement Confederation","164",,"108048","","",,34,"10.1016/j.measurement.2020.108048","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086581119&doi=10.1016%2fj.measurement.2020.108048&partnerID=40&md5=51819f50aefaf65ff84fb62e02f9dec6","Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States","Perry, B.J., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; Guo, Y., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; Atadero, R., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; van de Lindt, J.W., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States","Recently, the rapid development of commercial unmanned aerial vehicles (UAVs) has made collecting images of bridge conditions trivial. Measuring the damage extent, growth, and location from the collected big image set, however, can be cumbersome. This paper proposes a streamlined bridge inspection system that offers advanced data analytics tools to automatically: (1) identify type, extent, growth, and 3D location of defects using computer vision techniques; (2) generate a 3D point-cloud model and segment structural elements using human-in-the-loop machine learning; and (3) establish a georeferenced element-wise as-built bridge information model to document and visualize damage information. This system allows bridge managers to better leverage UAV technologies in bridge inspection and conveniently monitor the health of a bridge through quantifying and visualizing the progression of damage for each structural element. The efficacy of the system is demonstrated using two bridges. © 2020 Elsevier Ltd","Bridge Information Model (BrIM); Bridge inspection; Computer vision; Machine learning; Structural Health Monitoring (SHM); Unmanned Aerial Vehicles (UAVs)","Advanced Analytics; Antennas; Bridges; Commercial vehicles; Composite structures; Data Analytics; Inspection; Inspection equipment; Machine learning; 3d point cloud models; Analytics tools; Bridge inspection; Computer vision techniques; Damage information; Human-in-the-loop; Information Modeling; Structural elements; Unmanned aerial vehicles (UAV)",,,,,"69A3551747108; U.S. Department of Transportation, DOT; Colorado State University, CSU; Mountain-Plains Consortium, MPC","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University’s Drone Center for providing the UAVs and support, as well as Dr. Ross Beveridge of Colorado State University for his insight on the project.","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University's Drone Center for providing the UAVs and support, as well as Dr. Ross Beveridge of Colorado State University for his insight on the project.","Ryan, T.W., Mann, E., Chill, Z.M., Ott, B.T., Bridge Inspector's Reference Manual (2012), Federal Highway Administration Washington, D.C; (2018), AASHTO, The Manual for Bridge Evaluation, Third Edition, 2017, American Association of State Highway and Transportation Officials, Washington, D.C; Omar, T., Nehdi, M.L., Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography (2017) Autom. 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"Xu Y., Turkan Y.","57212506817;54390463700;","BrIM and UAS for bridge inspections and management",2020,"Engineering, Construction and Architectural Management","27","3",,"785","807",,21,"10.1108/ECAM-12-2018-0556","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076888281&doi=10.1108%2fECAM-12-2018-0556&partnerID=40&md5=664b6093d4e42f1ce839804d05b96a5a","Oregon State University, Corvallis, OR, United States; School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, United States","Xu, Y., Oregon State University, Corvallis, OR, United States; Turkan, Y., School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, United States","Purpose: The purpose of this paper is to develop a novel and systematic framework for bridge inspection and management to improve the efficiency in current practice. Design/methodology/approach: A new framework that implements camera-based unmanned aerial systems (UASs) with computer vision algorithms to collect and process inspection data, and Bridge Information Modeling (BrIM) to store and manage all related inspection information is proposed. An illustrative case study was performed using the proposed framework to test its feasibility and efficiency. Findings: The test results of the proposed framework on an existing bridge verified that: high-resolution images captured by an UAS enable to visually identify different types of defects, and detect cracks automatically using computer vision algorithms, the use of BrIM enable assigning defect information on individual model elements, manage all bridge data in a single model across the bridge life cycle. The evaluation by bridge inspectors from 12 states across the USA demonstrated that all of the identified problems, except for being subjective, can be improved using the proposed framework. Practical implications: The proposed framework enables to: collect and document accurate bridge inspection data, reduce the number of site visits and avoid data overload and facilitate a more efficient, cost-effective and safer bridge inspection process. Originality/value: This paper contributes a novel and systematic framework for the collection and integration of inspection data for bridge inspection and management. The findings from the case study suggest that the proposed framework should help improve current bridge inspection and management practice. Furthermore, the difficulties experienced during the implementation are evaluated, which should be helpful for improving the efficiency and the degree of automation of the proposed framework further. © 2019, Emerald Publishing Limited.","Building information modelling; Information systems; Management; Methodology; Technology","Antennas; Bridges; Computer vision; Cost effectiveness; Data visualization; Defects; Efficiency; Information systems; Information theory; Inspection; Life cycle; Management; Unmanned aerial vehicles (UAV); Building Information Modelling; Computer vision algorithms; Design/methodology/approach; High resolution image; Inspection information; Management practices; Methodology; Unmanned aerial systems; Information management",,,,,,,,"Al-Shalabi, F.A., Turkan, Y., Laflamme, S., BrIM implementation for documentation of bridge condition for inspection (2015) Proceedings of the Canadian Society for Civil Engineering 5th International/11th Construction Specialty Conference, University of British Columbia, pp. 7-10. , Vancouver: June; 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Eastman, C., Teicholz, P., Sacks, R., Liston, K., (2011) BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers And Contractors, , John Wiley & Sons, Hoboken; Fanning, B., Clevenger, C.M., Ozbek, M.E., Mahmoud, H., Implementing BIM on infrastructure: comparison of two bridge construction projects (2014) Practice Periodical on Structural Design and Construction, 20 (4). , p. 04014044; Gillins, D.T., Parrish, C., Gillins, M.N., Simpson, C., (2018) Eyes in the sky: bridge inspections with unmanned aerial vehicles, , Oregon Department of Transportation (ODOT), Report FHWA-OR-RD-18-11; Hallermann, N., Morgenthal, G., Visual inspection strategies for large bridges using Unmanned Aerial Vehicles (UAV) (2014) Proc. of 7th IABMAS, International Conference on Bridge Maintenance, Safety and Management, pp. 661-667; Karakhan, A., Xu, Y., Nnaji, C., Alsaffar, O., Technology alternatives for workplace safety risk mitigation in construction: exploratory study (2019) Advances in Informatics and Computing in Civil and Construction Engineering, pp. 823-829. , Mutis, I. and Hartmann, T., and,(Eds), Springer, Cham; 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Constr. Archit. Manage.",Article,"Final","",Scopus,2-s2.0-85076888281
"Park S.I., Park J., Kim B.-G., Lee S.-H.","57204956510;56972745200;56125080500;56813177600;","Improving applicability for information model of an IFC-based steel bridge in the design phase using functional meanings of bridge components",2018,"Applied Sciences (Switzerland)","8","12","2531","","",,15,"10.3390/app8122531","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058105909&doi=10.3390%2fapp8122531&partnerID=40&md5=63454af0fb308c26703ca0d77e99a174","Department of Civil and Environmental Engineering, Yonsei University, Seoul, 03722, South Korea; Taesung SNI Singapore, 438 Alexandra Rd.119958, Singapore","Park, S.I., Department of Civil and Environmental Engineering, Yonsei University, Seoul, 03722, South Korea; Park, J., Department of Civil and Environmental Engineering, Yonsei University, Seoul, 03722, South Korea; Kim, B.-G., Taesung SNI Singapore, 438 Alexandra Rd.119958, Singapore; Lee, S.-H., Department of Civil and Environmental Engineering, Yonsei University, Seoul, 03722, South Korea","The industry foundation classes (IFC) data model is the most important data schema in ensuring the interoperability of the information generated throughout the lifecycle of facilities. However, because the current IFC model is focused on buildings, there are limitations when this model is applied to bridge structures. This paper proposes a method that enables the information modeling of steel box girder bridges based on the current IFC. To select the required and core items, we classify the components of a steel box girder bridge by the design stage with reference to engineering documents. To generate functional meanings of each bridge component, we develop the rules of the unique identifier and information reassignment, and then apply a semi-automated naming algorithm. The generated bridge information model was used to confirm the functional semantic meanings of individual components, and it was checked whether additional external information, such as carbon emissions, could be linked for specific bridge components. It was observed that information retrieval and extraction for components is possible through a semantic-based query to the generated IFC-based bridge information model. © 2018 by the authors.","Automated naming algorithm; Bridge information modeling (BrIM); IFC user-defined property sets; Industry foundation classes (IFC); Model-based object query",,,,,,"Ministry of Land, Infrastructure and Transport, MOLIT","Funding: This research was supported by a grant (18RTRP-B104237-04) from Railroad Technology Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.",,"Eadie, R., Browne, M., Odeyinka, H., McKeown, C., McNiff, S., BIM implementation throughout the UK construction project lifecycle: An analysis (2013) Autom. Constr, 36, pp. 145-151; Borrmann, A., Kolbe, T.H., Donaubauer, A., Steuer, H., Jubierre, J.R., Flurl, M., Multi-scale geometric-semantic modeling of shield tunnels for GIS and BIM applications (2015) Comput.-Aided Civ. 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Constr, 87, pp. 22-38; Mangal, M., Cheng, J.C.P., Automated optimization of steel reinforcement in RC building frames using building information modeling and hybrid genetic algorithm (2018) Autom. Constr, 90, pp. 39-57; Ramaji, I.J., Memari, A.M., Interpretation of structural analytical models from the coordination view in building information models (2018) Autom. Constr, 90, pp. 117-133; Ninić, J., Koch, C., Stascheit, J., An integrated platform for design and numerical analysis of shield tunnelling processes on different levels of detail (2017) Adv. Eng. 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(In Korean); Kim, B.-G., Lee, S.-H., Enhancement of spatial and physical elements for IFC-based bridge data model (2011) Proceedings of the 28th International Symposium on Automation and Robotics in Construction (ISARC 2011), pp. 375-376. , Seoul, Korea, 29 June-2 July; (2014) ISO 6707-1:2014 Buildings and Civil Engineering Works-Vocabulary-Part 1: General Terms, , ISO: Geneva, Switzerland; (2011) IPCC Guideline of Korea, , MLIT: Sejong, Korea. (In Korean); See, R., Liebich, T., Hietanen, J., (2009) Design to QTO/Cost Estimating, , http://www.blis-project.org/IAI-MVD/reporting/listMVDs_4.php?SRT=Name&MVD=GSA-004&DV=2, (accessed on 1 November 2018); Choi, J., Choi, J., Kim, H., Kim, I., Open BIM-based quantity take-off system for schematic estimation of building frame in early design stage (2015) J. Comput. Des. Eng, 2, pp. 16-25; Mazairac, W., Beetz, J., BIMQL-An open query language for building information models (2013) Adv. Eng. Inform, 27, pp. 444-456","Lee, S.-H.; Department of Civil and Environmental Engineering, South Korea; email: lee@yonsei.ac.kr",,,"MDPI AG",,,,,20763417,,,,"English","Appl. Sci.",Article,"Final","All Open Access, Gold, Green",Scopus,2-s2.0-85058105909
"McKenna T., Minehane M., O'Keeffe B., O'Sullivan G., Ruane K.","57199723174;56370629200;57199695161;57199694887;36101643600;","Bridge information modelling (BrIM) for a listed viaduct",2017,"Proceedings of the Institution of Civil Engineers: Bridge Engineering","170","3",,"192","203",,15,"10.1680/jbren.16.00007","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038376198&doi=10.1680%2fjbren.16.00007&partnerID=40&md5=dd7e2124feb0484deb26c52748b130b5","Department of Civil, Structural and Environmental Engineering, Cork Institute of Technology, Ireland; RPS Group, Cork, Ireland; Murphy Surveys Ltd, Cork, Ireland; Datech (Ireland), Cork, Ireland","McKenna, T., Department of Civil, Structural and Environmental Engineering, Cork Institute of Technology, Ireland; Minehane, M., Department of Civil, Structural and Environmental Engineering, Cork Institute of Technology, Ireland, RPS Group, Cork, Ireland; O'Keeffe, B., Murphy Surveys Ltd, Cork, Ireland; O'Sullivan, G., Datech (Ireland), Cork, Ireland; Ruane, K., Department of Civil, Structural and Environmental Engineering, Cork Institute of Technology, Ireland, RPS Group, Cork, Ireland","Bridge information modelling (BrIM) invokes stakeholder collaboration, supported by policy and process frameworks, combined with interoperable technology, to manage information and enable effective decision making throughout the lifecycle of a bridge asset. This paper considers the application of BrIM for the proposed rehabilitation of a heritage listed viaduct. The structure under consideration is the landmark Chetwynd viaduct in Cork (Ireland), which formed part of the Cork-Bandon railway infrastructure constructed in 1851 and decommissioned in 1961. As with infrastructure of its type, few as-built records exist. Consequently, the geometry, material properties and condition of the existing structure are required to inform the initial feasibility assessment and subsequent design, construction and operation of this viaduct asset. Respective BrIM and traditional approaches to the data capture phase are outlined and compared in terms of time, expertise and deliverables. The significant deliverables from the traditional approach include a three-dimensional (3D) solid model and independent 2D drawings. Significant deliverables achieved using a BrIM approach include an intelligent parametric 3D model and associated 2D drawings, as well as integrated datasets representative of the 'as-is' structure. Based on reported research, the initial effort and time expended on model creation in particular will enable significant future benefits. © 2016 ICE Publishing: All rights reserved.","building information modelling (BIM); rehabilitation, reclamation & renovation/viaducts","Bridges; Decision making; Information theory; Railroad transportation; Building Information Modelling; Existing structure; Feasibility assessment; Information modelling; Interoperable technologies; Railway infrastructure; Three-dimensional (3D) solids; Traditional approaches; Architectural design",,,,,,"The authors would like to acknowledge Cork County Council for permission to use Chetwynd viaduct as the focus for this research and Cork Institute of Technology for supporting the research.",,"Abbas, A.H., (2011) San Francisco-Oakland Bay Bridge Benefits from Bridge Information Modeling, , http://cenews.com/article/8351/san_francisco_oakland_bay_bridge_benefits_from_bridge_information-modeling, (accessed 15/04/2015); Al-Shalabi, F., Turkan, Y., Laflamme, S., BRIM implementation for documentation of bridge condition for inspection, 2015 (2015) Proceedings of 5th International/11th Construction Specialty Conference, pp. 262261-262268. , Vancouver, BC, Canada; Barlish, K., Sullivan, K., How to measure the benefits of BIM - A case study approach (2012) Automation in Construction, 24, pp. 149-159; (2007) BS 1192:2007+A2:2016: Collaborative Production of Architectural, Engineering and Construction Information-Code of Practice, , BSI BSI, London, UK; (2013) PAS 1192-2: Specification for Information Management for the Capital/delivery Phase of Construction Projects Using Building Information Modelling, , BSI BSI, London, UK; (2014) PAS 1192-3: Specification for Information Management for the Operational Phase of Assets Using Building Information Modelling, , BSI BSI, London, UK; (2014) BS 1192-4: Collaborative Production of Information Part 4: Fulfilling Employer's Information Exchange Requirements Using COBie-Code of Practice, , BSI BSI, London, UK; (2015) PAS 1192-5: Specification for Security Minded Building Information Modelling, Digital Built Environments and Smart Asset Management, , BSI BSI, London, UK; Cox, R., Gould, M., (2003) Ireland's Bridges., , Wolfhound Press, Dublin, Ireland; Dore, C., Murphy, M., Semi-automatic generation of as-built BIM façade geometry from laser and image data (2014) Journal of Information Technology in Construction, 19, pp. 20-46; Eastman, C., Teicholz, P., Sacks, R., Liston, K., (2011) BIM Case Studies. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, , Wiley, Hoboken, NJ, USA; Hichri, N., Stefani, C., De Luca, L., Veron, P., Review of the 'as-built BIM' approaches (2013) InternationalArchives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W1, pp. 107-112; (2015) Digital Built Britain-Level 3 Building Information Modelling-Strategic Plan, , HM Government HM Government, London, UK; (2013) Heritage Bridges of County Cork, , HUCCC (Heritage Unit of Cork County Council) HUCCC, Cork, Ireland; (1851) Opening of the Cork and Bandon Railway, 19, p. 733. , ILN (Illustrated London News) Illustrated London News; Jung, J., Hong, S., Jeong, S., Productive modeling for development of as-built BIM of existing indoor structures (2014) Automation in Construction, 42, pp. 68-77; Marzouk, M.M., Hisham, M., Bridge information modeling in sustainable bridge management (2011) Proceedings of International Conference On Sustainable Design and Construction (ICSDC) 2011, pp. 457-466. , (Chong WKO and Hermreck C (eds)). American Society of Civil Engineers, Kansas City, MO, USA; Marzouk, M., Hisham, M., Implementing earned value management using bridge information modeling (2014) KSCE Journal of Civil Engineering, 18 (5), pp. 1302-1313; Marzouk, M., Cairo University, E., Hisham, M., Cairo University, E., Applications of building information modeling in cost estimation of infrastructure bridges (2015) International Journal of 3-D Information Modeling, 1 (2), pp. 17-29; (2008) Eirspan System Manual No. 3 Principal Inspection, Revision C, , NRA (National Roads Authority) NRA, Dublin, Ireland; (2013) BD21-The Assessment of Road Bridges and Structures Ireland, , NRA NRA, Dublin, Ireland; O'Keeffe, A., The state of the art of bridge information modelling from conceptual design through to operation (2014) International Journal of 3-D Information Modeling, 3 (1), pp. 29-39; Randall, T., Construction engineering requirements for integrating laser scanning technology and building information modeling (2011) Journal of Construction Engineering & Management, 137 (10), pp. 797-805; Randall, T., Client Guide to 3D Scanning and Data Capture (2013) The Building Information Modelling Task Group, , London, UK; Slattery, D.K., Slattery, K.T., (2010) Evaluation of 3D Laser Scanning for Construction Application, , Illinois Center for Transportation, Southern Illinois University Edwardsville, Edwardsville, IL, USA; Volk, R., Stengel, J., Schultmann, F., Building information modeling (BIM) for existing buildings-literature review and future needs (2014) Automation in Construction, 38, pp. 109-127; Werner, T., Morris, D., 3D laser scanning for masonry arch bridges (2010) Proceedings of FIG Congress, Sydney, Australia, , http://www.fig.net/resources/proceedings/fig_proceedings/fig2010/papers/ts04d/ts04d_werner_morris_4436.pdf, accessed 12/10/2016; Xiong, X., Adan, A., Akinci, B., Huber, D., Automatic creation of semantically rich 3D building models from laser scanner data (2013) Automation in Construction, 31, pp. 325-337; Zhu, Z., Brilakis, I., Comparison of optical sensor-based spatial data collection techniques for civil infrastructure modeling (2009) Journal of Computing in Civil Engineering, 23 (3), pp. 170-177","McKenna, T.; Department of Civil, Ireland; email: ted.mckenna@cit.ie",,,"ICE Publishing",,,,,14784637,,,,"English","Proc. Inst. Civ. Eng. Bridge Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85038376198
"Jeong S., Hou R., Lynch J.P., Sohn H., Law K.H.","56893042300;57190580657;57199678735;7201426396;55671078700;","A scalable cloud-based cyberinfrastructure platform for bridge monitoring",2019,"Structure and Infrastructure Engineering","15","1",,"82","102",,14,"10.1080/15732479.2018.1500617","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059017514&doi=10.1080%2f15732479.2018.1500617&partnerID=40&md5=cd0e352a0deadbf6c32af07cd77d8bce","Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States; Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","Jeong, S., Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States; Hou, R., Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Lynch, J.P., Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Sohn, H., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Law, K.H., Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States","Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of data. Appropriate use of cloud computing infrastructure can enhance the long-term deployment of a structural health monitoring (SHM) system which would incur significant amount of data of different types. This paper presents a cloud-based cyberinfrastructure platform designed to support bridge monitoring. The cyberinfrastructure platform enables scalable management of SHM data and facilitates effective information sharing and data utilisation. A cloud-based platform comprises of virtual machines, distributed database and web servers. The peer-to-peer distributed database architecture provides a scalable and fault-tolerant data management system. Platform-neutral web services designed in compliant with the Representational State Transfer (REST) standard enables easy access to the cloud resources and SHM data. For data interoperability, a bridge information model for bridge monitoring applications is adopted. For demonstration, the scalable cloud-based platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cloud-based cyberinfrastructure platform can effectively manage the sensor data and bridge information and facilitate efficient access of the data as well as the bridge monitoring software services. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.","bridge information modelling; bridge monitoring; Cloud computing; interoperability; scalability; web services","Cloud computing; Digital storage; Distributed database systems; Information theory; Internet of things; Interoperability; Monitoring; Peer to peer networks; Scalability; Structural health monitoring; Web services; Websites; Bridge monitoring; Cloud computing infrastructures; Data interoperability; Data management system; Information modelling; Internet of Things (IOT); Representational state transfer; Structural health monitoring (SHM); Information management",,,,,"National Science Foundation, NSF: CMMI-1362513, ECCS-1446330, ECCS-1446521; Michigan Department of Transportation, MDOT; Stanford University, SU; University of Michigan, U-M; Ministry of Land, Infrastructure and Transport, MOLIT; Korea Agency for Infrastructure Technology Advancement, KAIA","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) and is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge, Newburg Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. While certain commercial systems are identified in this paper, such identification does not imply recommendation or endorsement by the authors, NSF, MOLIT, MDOT or KAIA; nor does it imply that the products identified are necessarily the best available for the purpose. Furthermore, any opinions, findings, conclusions or recommendations expressed in this paper are solely those of the authors and do not necessarily reflect the views of NSF, MOLIT, MDOT, KAIA or any other organisations and collaborators.","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) and is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan).","Agrawal, D., Das, S., Abbadi, A.E., Big data and cloud computing: Current state and future opportunities (2011) Proceedings of the 14Th International Conference on Extending Database Technology (EDBT/ICDT '11), pp. 530-533. , New York, NY; Alampalli, S., Alampalli, S., Ettouney, M., Big data and high-performance analytics in structural health monitoring for bridge management (2016) Proceedings of the SPIE Smart Structures/Nde Conference, , Las Vegas, NV, March 20–24; Arumugam, R., Enti, V.R., Bingbing, L., Xiaojun, W., Baskaran, K., Kong, F.F., Kumar, A.S., Kit, G.W., DAvinCi: A cloud computing framework for service robots (2010) 2010 IEEE International Conference on Robotics and Automation, pp. 3084-3089. , Anchorage, AK; Bartholomew, M., Blasen, B., Koc, A., (2015) Bridge information modeling (BrIM) using open parametric objects, , (Report No. FHWA-HI F-16-010). 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Infrastructure Eng.",Article,"Final","",Scopus,2-s2.0-85059017514
"Nili M.H., Taghaddos H., Zahraie B.","57220864570;26031827800;57203578183;","Integrating discrete event simulation and genetic algorithm optimization for bridge maintenance planning",2021,"Automation in Construction","122",,"103513","","",,13,"10.1016/j.autcon.2020.103513","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097744936&doi=10.1016%2fj.autcon.2020.103513&partnerID=40&md5=80471cef4422a0d61caae245e1d9a8cd","School of Civil Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran","Nili, M.H., School of Civil Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran; Taghaddos, H., School of Civil Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran; Zahraie, B., School of Civil Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran","To minimize agency and user costs in a bridge repair project, a bridge maintenance manager should develop an appropriate project schedule considering real-world constraints such as resource limitations (e.g., workspace and crew). This paper presents a new framework called Simulation-based Bridge Maintenance Optimization (SiBMO) by integrating Genetic Algorithm (GA) and Discrete Event Simulation (DES) to identify the optimum maintenance plan taking into account crew limitations. The framework optimizes the sequence of repair-activities in the repair interventions considering workspace limitations and predecessor relationships. SiBMO also develops a high-level schedule of the interventions regarding the project calendar and the Traffic Management Plan (TMP). The Bridge Information Model (BrIM) based user interface developed in this study visualizes the high-level schedule. The results of applying SiBMO on a real case study demonstrates its capability in finding the optimum maintenance plan, its efficiency in optimizing the high-level schedule, and its accuracy in estimating user costs. © 2020 Elsevier B.V.","Bridge Information Modeling (BrIM); Bridge maintenance plan; bridge maintenance schedule; Discrete Event Simulation (DES); Genetic Algorithm (GA); resource limitation; user costs","Bridges; Costs; Discrete event simulation; Genetic algorithms; Planning; Silicon; User interfaces; Bridge maintenance; Genetic-algorithm optimizations; Information Modeling; Maintenance plans; Project schedules; Real world constraints; Resource limitations; Traffic Management Plans; Repair",,,,,,,,"Ghodoosi, F., Bagchi, A., Zayed, T., Hosseini, M.R., Method for developing and updating deterioration models for concrete bridge decks using GPR data (2018) Autom. 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"Rashidi A., Karan E.","36683238400;26423065800;","Video to BrIM: Automated 3D As-Built Documentation of Bridges",2018,"Journal of Performance of Constructed Facilities","32","3","04018026","","",,13,"10.1061/(ASCE)CF.1943-5509.0001163","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045195282&doi=10.1061%2f%28ASCE%29CF.1943-5509.0001163&partnerID=40&md5=a7d473074f6fa6c3ff2e3013461bf411","Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT  84112, United States; Dept. of Applied Engineering, Safety and Technology, Millersville Univ., Millersville, PA  17551, United States","Rashidi, A., Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT  84112, United States; Karan, E., Dept. of Applied Engineering, Safety and Technology, Millersville Univ., Millersville, PA  17551, United States","Labeling and mapping existing infrastructure is one of the grand challenges for civil engineers in the 21st century. The challenge remains in finding an appropriate data collection method that rapidly collects structural and geometrical information of bridges and automatically converts it into three-dimensional (3D) models. Over the last decade, there has been a tremendous effort to develop prototypes for capturing the as-is condition of a bridge and converting it into 3D bridge-information models (BrIMs). Bridge-information models are 3D-information-rich data models that can be used in various phases of bridge design, construction, operations, and maintenance. As an alternative solution, researchers are now studying the processing of videos to capture the required 3D information (videogrammetry) and using algorithms to automatically extract 3D objects and convert the results into a BrIM. This study evaluates the applicability of a novel videogrammetric pipeline for automatically documenting the physical condition of bridges. It also describes the results of three case studies of highway bridge assessment and modeling in which 3D information is extracted from two-dimensional video frames and point cloud data (PCD) are generated. As the next step, the PCD can be converted into a data-rich BrIM object for further processing. © 2018 American Society of Civil Engineers.","Bridge; Bridge information modeling (BrIM); Civil infrastructure; Industry foundation class (IFC); Videogrammetry","Information theory; Alternative solutions; Civil infrastructures; Data collection method; Geometrical informations; Industry Foundation Classes - IFC; Information Modeling; Three-dimensional (3D) model; Videogrammetry; Bridges",,,,,,,,"Adan, A., Huber, D., 3D reconstruction of interior wall surfaces under occlusion and clutter (2011) Proc. 2011 Int. 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"Xia T., Yang J., Chen L.","57300413900;56997727500;57218501068;","Automated semantic segmentation of bridge point cloud based on local descriptor and machine learning",2022,"Automation in Construction","133",,"103992","","",,10,"10.1016/j.autcon.2021.103992","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117420951&doi=10.1016%2fj.autcon.2021.103992&partnerID=40&md5=21701e71190c6cd9042522cd0ad88b1c","Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructures, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Lloyds Register Foundation/Data Centric Engineering Programme, The Alan Turing Institute, London, UK  NW1 2DB, United Kingdom; School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough, LE11 3TU, United Kingdom","Xia, T., Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructures, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Yang, J., Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructures, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Chen, L., Lloyds Register Foundation/Data Centric Engineering Programme, The Alan Turing Institute, London, UK  NW1 2DB, United Kingdom, School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough, LE11 3TU, United Kingdom","In recent years, monitoring the health condition of existing bridges has become a common requirement. By providing an information management system, Bridge Information Model (BrIM) can highly improve the efficiency of health inspection and the reliability of condition evaluation. However, the current modeling processes still largely rely on manual work, where the cost outweighs the benefits. The main barrier lies in the challenging step of semantic segmentation of point clouds. Efforts have been made to identify and segment the structural components of bridges in existing research. But these methods are either dependent on manual data preprocessing or need big training dataset, which, however, has rendered them unpractical in real-world applications. This paper presents a combined local descriptor and machine learning based method to automatically detect structural components of bridges from point clouds. Based on the geometrical features of bridges, we design a multi-scale local descriptor, which is then used to train a deep classification neural network. In the end, a result refinement algorithm is adopted to optimize the segmentation results. Experiments on real-world reinforced concrete (RC) slab and beam-slab bridges show an average precision of 97.26%, recall of 98.00%, and intersection over union (IoU) of 95.38%, which significantly outperforms PointNet. This method has provided a potential solution to semantic segmentation of infrastructures by small sample learning and will contribute to the fulfillment of the automatic BrIM generation of typical highway bridges from the point cloud in the future. © 2021","Bridge information model; Local descriptor; Machine learning; Point cloud; Semantic segmentation","Bridges; Information management; Information theory; Machine components; Machine learning; Reinforced concrete; Semantics; Bridge information model; Cloud-based; Existing bridge; Health condition; Information Modeling; Local descriptors; Point-clouds; Real-world; Semantic segmentation; Structural component; Semantic Segmentation",,,,,"Science and Technology Commission of Shanghai Municipality, STCSM: 18DZ1205603, 20DZ1201300, 21DZ1204704","This work was supported by the Scientific Research Project of Shanghai Science and Technology Commission (No. 18DZ1205603 , 20DZ1201300 , 21DZ1204704 ).",,"ASCE, America's Infrastructure Report Card 2021 (2021), https://infrastructurereportcard.org/wp-content/uploads/2020/12/National_IRC_2021-report.pdf, Available at; Kim, I.-H., Jeon, H., Baek, S.-C., Hong, W.-H., Jung, H.-J., Application of crack identification techniques for an aging concrete bridge inspection using an unmanned aerial vehicle (2018) Sensors, 18 (6), p. 1881; Wang, H.-F., Zhai, L., Huang, H., Guan, L.-M., Mu, K.-N., Wang, G.-P., Measurement for cracks at the bottom of bridges based on tethered creeping unmanned aerial vehicle (2020) Autom. 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"Salamak M., Januszka M.","25028351300;23060889000;","Brim bridge inspections in the context of industry 4.0 trends",2018,"Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges - Proceedings of the 9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018",,,,"2260","2267",,9,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067085093&partnerID=40&md5=f43276e541158f472fd6bf48c7db055a","Silesian University of Technology, Gliwice, Poland","Salamak, M., Silesian University of Technology, Gliwice, Poland; Januszka, M., Silesian University of Technology, Gliwice, Poland","This paper describes two new technologies, Bridge Information Modelling (BrIM) and Augmented Reality (AR), which fit into the cyber-physical devices and cloud computing ideology of Industry 4.0. The rapid development of such technologies will have a significant impact on the design, construction, use, and management of transportation infrastructure, including bridges. This paper highlights difficulties in implementing BrIM technology for infrastructure projects and modelling of bridges. It also shows details of a new concept for inspection of bridges based on BrIM and AR. © 2018 Taylor & Francis Group, London.",,"Augmented reality; Industry 4.0; Life cycle; Maintenance; Safety engineering; Bridge inspection; Cyber physicals; Information modelling; Infrastructure project; Transportation infrastructures; Bridges",,,,,,,,"Abdullah, A., Thai, O.B., Personal digital assistants as a mobile inspection system at construction site (2006) Proceedings of the 6Th Asia-Pacific Structural Engineering and Construction Conference (APSEC 2006), pp. D28-D38. , 5-6 September 2006, Kuala Lumpur, Malaysia; Azuma, R.T., A Survey of Augmented Reality (1997) Teleoperators Virtual Environ, 6 (4-1997), pp. 355-385; Bień, J., Kużawa, M., Bień, B., To See is to Know: Visualization in Bridge Inspection and Management (2010) 5Th International Conference on Bridge Maintenance, Safety and Management, pp. 567-574. , Philadelphia; Bień, J., Rawa, P., Hybrid Knowledge Representation in BMS (2004) Arch. 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Constr, 34 (2013), pp. 37-44; Żarski, M., Płaszczyk, T., Salamak, M., Integrated lifecycle analysis of a concrete bridge (2017) 12Th Central European Congress on Concrete Engineering CCC2017, pp. 140-148. , Tokaj, Hungary",,"Powers N.Frangopol D.M.Al-Mahaidi R.Caprani C.","et al.;IABMAS, International Association for Bridge Maintenance and Safety;Monash University;RMIT University;Swinburne University of Technology;VicRoads","CRC Press/Balkema","9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018","9 July 2018 through 13 July 2018",,226219,,9781138730458,,,"English","Maint., Saf., Risk, Manag. Life-Cycle Perform. Bridges - Proc. Int. Conf. Bridge Maint., Saf. Manag.",Conference Paper,"Final","",Scopus,2-s2.0-85067085093
"Nguyen D.-C., Nguyen T.-Q., Jin R., Jeon C.-H., Shim C.-S.","57223082744;57211376975;56443380400;57189060332;7103280900;","BIM-based mixed-reality application for bridge inspection and maintenance",2022,"Construction Innovation","22","3",,"487","503",,7,"10.1108/CI-04-2021-0069","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114227050&doi=10.1108%2fCI-04-2021-0069&partnerID=40&md5=77b72241b6538221b81d01a5b4793322","Chung-Ang University, Seoul, South Korea; National University of Civil Engineering, Hanoi, Viet Nam; London South Bank University, London, United Kingdom","Nguyen, D.-C., Chung-Ang University, Seoul, South Korea; Nguyen, T.-Q., National University of Civil Engineering, Hanoi, Viet Nam; Jin, R., London South Bank University, London, United Kingdom; Jeon, C.-H., Chung-Ang University, Seoul, South Korea; Shim, C.-S., Chung-Ang University, Seoul, South Korea","Purpose: The purpose of this study is to develop a building information modelling (BIM)-based mixed reality (MR) application to enhance and facilitate the process of managing bridge inspection and maintenance works remotely from office. It aims to address the ineffective decision-making process on maintenance tasks from the conventional method which relies on documents and 2D drawings on visual inspection. This study targets two key issues: creating a BIM-based model for bridge inspection and maintenance; and developing this model in a MR platform based on Microsoft Hololens. Design/methodology/approach: Literature review is conducted to determine the limitation of MR technology in the construction industry and identify the gaps of integration of BIM and MR for bridge inspection works. A new framework for a greater adoption of integrated BIM and Hololens is proposed. It consists of a bridge information model for inspection and a newly-developed Hololens application named “HoloBridge”. This application contains the functional modules that allow users to check and update the progress of inspection and maintenance. The application has been implemented for an existing bridge in South Korea as the case study. Findings: The results from pilot implementation show that the inspection information management can be enhanced because the inspection database can be systematically captured, stored and managed through BIM-based models. The inspection information in MR environment has been improved in interpretation, visualization and visual interpretation of 3D models because of intuitively interactive in real-time simulation. Originality/value: The proposed framework through “HoloBridge” application explores the potential of integrating BIM and MR technology by using Hololens. It provides new possibilities for remote inspection of bridge conditions. © 2021, Emerald Publishing Limited.","BIM-based mixed-reality; Bridge inspection; Bridge maintenance; Building information modelling (BIM); Hololens; Integrated BIM and mixed reality; Maintenance; Mixed reality","Architectural design; Construction industry; Decision making; Information management; Information theory; Inspection; Maintenance; Mixed reality; Three dimensional computer graphics; Building Information Modelling; Conventional methods; Decision making process; Design/methodology/approach; Inspection and maintenance; Inspection information; Real time simulations; Visual interpretation; Bridges",,,,,"Teesside University; Ministry of Land, Infrastructure and Transport, MOLIT; Korea Agency for Infrastructure Technology Advancement, KAIA","This is a substantially extended and enhanced version of the paper presented at The 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). We would like to acknowledge the editorial contributions of Professor Nashwan Dawood and Dr. Farzad Rahimian of Teesside University in the publication of this paper. Funding : This research was conducted with the support of the “National R&D Project for Smart Construction Technology (No.21SMIP-A158708-02)” funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation.","Funding: This research was conducted with the support of the “National R&D Project for Smart Construction Technology (No.21SMIP-A158708-02)” funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation.","Abdelkader, E.M., On the hybridization of pre-trained deep learning and differential evolution algorithms for semantic crack detection and recognition in ensemble of infrastructures (2021) Smart and Sustainable Built Environment; Al-Adhami, M., Wu, S., Ma, L., Extended reality approach for construction quality control (2019) Proceedings of CIB World Building Congress 2019, , Hong Kong; Al-Shalabi, F.A., Turkan, Y., Laflamme, S., BrIM implementation for documentation of bridge condition for inspection (2015) Proceedings of the Canadian Society for Civil Engineering 5th International/11th Construction Specialty Conference, pp. 7-10. , Vancouver, Canada; Chalhoub, J., Ayer, S.K., Using mixed reality for electrical construction design communication (2018) Automation in Construction, 86, pp. 1-10; Dabous, S.A., Feroz, S., Condition monitoring of bridges with non-contact testing technologies (2020) Automation in Construction, 116, p. 103224; Davidson, J., Fowler, J., Pantazis, C., Sannino, M., Walker, J., Sheikhkhoshkar, M., Rahimian, F.P., Integration of VR with BIM to facilitate real-time creation of bill of quantities during the design phase: a proof of concept study (2020) Frontiers of Engineering Management, 7 (3), pp. 396-403; Demian, P., Walters, D., The advantages of information management through building information modelling (2014) Construction Management and Economics, 32 (12), pp. 1153-1165; Dunston, P.S., Wang, X., Mixed reality-based visualization interfaces for architecture, engineering, and construction industry (2005) Journal of Construction Engineering and Management, 131 (12), pp. 1301-1309; Eastman, C.M., Eastman, C., Teicholz, P., Sacks, R., Liston, K., (2011) BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, , John Wiley and Sons, New York; El Ammari, K., Hammad, A., Remote interactive collaboration in facilities management using BIM-based mixed reality (2019) Automation in Construction, 107, p. 102940; Elghaish, F., Matarneh, S., Talebi, S., Kagioglou, M., Hosseini, M.R., Abrishami, S., Toward digitalization in the construction industry with immersive and drones technologies: a critical literature review (2020) Smart and Sustainable Built Environment; Feng, C.W., Chen, C.W., Using BIM and MR to improve the process of job site construction and inspection (2019) WIT Transactions on the Built Environment, 192, pp. 21-32; Hamzeh, F., Abou-Ibrahim, H., Daou, A., Faloughi, M., Kawwa, N., 3D visualization techniques in the AEC industry: the possible uses of holography (2019) ITcon, 24, pp. 239-255; Hüthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC bridge defect information into BIM models (2018) Journal of Computing in Civil Engineering, 32 (3); Karaaslan, E., Bagci, U., Catbas, F.N., Artificial intelligence assisted infrastructure assessment using mixed reality systems (2019) Transportation Research Record: Journal of the Transportation Research Board, 2673 (12), pp. 413-424; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) Journal of Bridge Engineering, 21 (4), p. 4015076; Mansuri, L.E., Patel, D.A., Artificial intelligence-based automatic visual inspection system for built heritage (2021) Smart and Sustainable Built Environment; Mascareñas, D.D., Ballor, J.P., McClain, O.L., Mellor, M.A., Shen, C.Y., Bleck, B., Morales, J., Martinez, E., Augmented reality for next generation infrastructure inspections (2020) Structural Health Monitoring, 20 (4), pp. 1957-1979; Moreu, F., Bleck, B., Vemuganti, S., Rogers, D., Mascarenas, D., Augmented reality tools for enhanced structural inspection (2017) Proceeding of 11th Int. Workshop on Structural Health Monitoring; Nili, M.H., Taghaddos, H., Zahraie, B., Integrating discrete event simulation and genetic algorithm optimization for bridge maintenance planning (2021) Automation in Construction, 122, p. 103513; Omer, M., Margetts, L., Hadi Mosleh, M., Hewitt, S., Parwaiz, M., Use of gaming technology to bring bridge inspection to the office (2019) Structure and Infrastructure Engineering, 15 (10), pp. 1292-1307; Prabhakaran, A., Mahamadu, A.M., Mahdjoubi, L., Manu, P., An approach for integrating mixed reality into BIM for early stage design coordination (2020) Proceeding of MATEC Web of Conferences, 312; Riexinger, G., Kluth, A., Olbrich, M., Braun, J.D., Bauernhansl, T., Mixed reality for on-site self-instruction and self-inspection with building information models (2018) Proceeding of 51st CIRP Conference on Manufacturing Systems, 72, pp. 1124-1129; Rokhsaritalemi, S., Sadeghi-Niaraki, A., Choi, S.M., A review on mixed reality: current trends, challenges and prospects (2020) Applied Sciences, 10 (2), p. 636; Sacks, R., Kedar, A., Borrmann, A., Ma, L., Brilakis, I., Hüthwohl, P., Daum, S., Barutcu, B.E., See Bridge as next generation bridge inspection: overview, information delivery manual and model view definition (2018) Automation in Construction, 90, pp. 134-145; Salamak, M., Januszka, M., BrIM bridge inspections in the context of industry 4.0 trends (2018) Proceedings of the 9th International Conference on Bridge Maintenance, Safety and Management, IABMAS, , Melbourne, Australia; Sheikhkhoshkar, M., Rahimian, F.P., Kaveh, M.H., Hosseini, M.R., Edwards, D.J., Automated planning of concrete joint layouts with 4D-BIM (2019) Automation in Construction, 107, p. 102943; Shim, C.S., Lee, K.M., Kang, L.S., Hwang, J., Kim, Y., Three-dimensional information model-based bridge engineering in Korea (2012) Structural Engineering International, 22 (1), pp. 8-13; Shim, C.S., Kang, H.R., Dang, N.S., Lee, D.K., Development of BIM-based bridge maintenance system for cable-stayed bridges (2017) Smart Structures and Systems, 20 (6), pp. 697-708; Shim, C.S., Dang, N.S., Lon, S., Jeon, C.H., Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model (2019) Structure and Infrastructure Engineering, 15 (10), pp. 1319-1332","Shim, C.-S.; Chung-Ang UniversitySouth Korea; email: csshim@cau.ac.kr",,,"Emerald Group Holdings Ltd.",,,,,14714175,,,,"English","Constr. Innov.",Article,"Final","All Open Access, Green",Scopus,2-s2.0-85114227050
"Zhang Z., Hamledari H., Billington S., Fischer M.","57205460326;57190003796;7006775408;7402921618;","4D beyond construction: Spatio-temporal and life-cyclic modeling and visualization of infrastructure data",2018,"Journal of Information Technology in Construction","23","1",,"285","304",,7,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060079729&partnerID=40&md5=0e163c97cd09a8c9709cbd1478ac4bd7","Stanford University, Stanford, United States","Zhang, Z., Stanford University, Stanford, United States; Hamledari, H., Stanford University, Stanford, United States; Billington, S., Stanford University, Stanford, United States; Fischer, M., Stanford University, Stanford, United States","SUMMARY: While four-dimensional (4D) technology has been extensively studied for use in the construction phase, there exists a great potential for its successful application in the maintenance, operation, and facility management phases. This paper proposes a novel 4D-based method for life cyclic integration, modeling, and visualization of infrastructure data. Such temporal integration of infrastructure data is particularly crucial due to the ever-increasing demand for maintaining the infrastructure assets in the United States, with approximately 188 million trips occurring across the nation’s structurally deficient bridges. The proposed approach takes the application of 4D technology beyond the construction phase and demonstrates its effectiveness for life cyclic modeling and visualization of infrastructures’ data including condition assessments. In this approach, various data categories such as inspection reports, maintenance schedules and costs, degradation models, operation schedules, and elements’ semantics are integrated with 3D models and using 4D technology, bringing the notion of time and space to infrastructure data; this enables the spatio-temporal exploration and modeling of data at an element level; this is not currently achievable since the existing solutions connect and display just one set of temporal data for one level of detail of a structure. The introduced technique also visualizes the data using a color-coding scheme and provides customized query and information retrieval support. In addition, degradation models can be integrated with the 4D-based system to simulate the condition ratings over time. The technique has been implemented and demonstrated for bridge infrastructure; it has been evaluated in two case study bridges in the state of California, United States, and has shown promise for use in real-life applications. The technique was observed to become more effective with increase in the complexity of maintenance tasks and infrastructure models; it increased the accuracy of maintenance tasks by 20-40% and reduced their duration by 30-50%. © 2018 The author(s).","4D, infrastructure; Bridge information model; Information modeling; Maintenance; Visualization","Data integration; Data visualization; Flow visualization; Information theory; Maintenance; Office buildings; Semantics; Visualization; 4D, infrastructure; Bridge infrastructure; Condition assessments; Information Modeling; Infrastructure assets; Infrastructure models; Real-life applications; Spatio-temporal explorations; Bridges",,,,,"California Department of Transportation, CT","The authors extend their gratitude to Mr. Pete Whitfield, from the California Department of Transportation; Walt Disney Inc.; and CALTRANS engineers and Stanford engineering students who participated in this research. The authors are also grateful to Dr. Kincho Law, Dr. Jack Baker, and Dr. Jean-Claude Latombe from Stanford University for their constructive comments on the work. This research was financially supported by the Thomas V. Jones Stanford Graduate Fellowship, UPS Foundation, John A. Blume Fellowship, and Stanford School of Engineering Fellowship. The findings and opinions expressed in this paper do not necessarily represent the views of the individuals and organizations mentioned above.",,"Adhikari, R.S., Moselhi, O., Bagchi, A., Image-based Change Detection for Bridge Inspection (2013) Proc., 30th International Symposium on Automation and Robotics in Construction (ISARC 2013), , August; Akinci, B., Situational awareness in construction and facility management (2015) Frontiers of Engineering Management, 1 (3), pp. 283-289; Akinci, B., Fischer, M., Kunz, J., Automated generation of work spaces required by construction activities (2002) Journal of Construction Engineering and Management, 128 (4), pp. 306-315; Akutsu, A., Sasaki, E., Takeya, K., Kobayashi, Y., Suzuki, K., Tamura, H., A comprehensive study on development of a small-sized self-propelled robot for bridge inspection (2016) Structure and Infrastructure Engineering, pp. 1-12; (2017) ASCE 2017 Report Card for America'S Infrastructure, , http://www.infrastructurereportcard.org/; 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Principles and methodologies (2011) Automation in Construction, 20 (2), pp. 155-166",,,,"Department of Computer Science",,,,,18744753,,,,"English","J. Inf. Technol. Constr.",Article,"Final","",Scopus,2-s2.0-85060079729
"Markiz N., Jrade A.","55358120700;12804778900;","Integrating fuzzy-logic decision support with a Bridge Information Management System (BRIMS) at the conceptual stage of bridge design",2018,"Journal of Information Technology in Construction","23",,,"92","121",,7,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048048238&partnerID=40&md5=4b047ef74c3fe7968205ad3d1b6ff155","Department of Civil Engineering, University of Ottawa, 161 Louis Pasteur Pvt., Ottawa, ON  K1N 6N5, Canada","Markiz, N., Department of Civil Engineering, University of Ottawa, 161 Louis Pasteur Pvt., Ottawa, ON  K1N 6N5, Canada; Jrade, A., Department of Civil Engineering, University of Ottawa, 161 Louis Pasteur Pvt., Ottawa, ON  K1N 6N5, Canada","In recent years, infrastructure restoration has been backlogged with complex factors that have captured the attention of municipal and federal authorities in North America and Europe. The subjective nature of evaluating bridge conditions and bridge deterioration is one of the main factors that influences bridge maintenance, repair, and replacement (MR&R) decisions. This study presents a stochastic fuzzy logic decision support integrated with a bridge information management system (BrIMS) to forecast bridge deteriorations and prioritize maintenance, repair, and replacement (MR&R) decisions at the conceptual design stage. The proposed system considers numerous factors that influence the prioritization of bridge MR&R decision making including complex time-dependent gamma shock models. A parametric analysis is conducted in order to quantify the degree of accuracy of the system. Implementation of the system platform demonstrated the viability of integrating BrIMS with fuzzy-logic deterioration forecast techniques at the conceptual stage of bridge design. The proposed system is validated through a case study and found to be in agreement with actual bridge deterioration results with a percentage difference of approximately 10 - 15 %. Besides that, the integrated platform may be utilized as a forecasting tool that is capable of predicting and prioritizing MR&R decisions to components for diverse bridge design alternatives. © 2018 The author(s).","Bridge Information Management System; Bridge Information Model; Decision Support; Deterioration Forecast; Fuzzy-logic","Computer circuits; Conceptual design; Decision making; Decision support systems; Deterioration; Forecasting; Fuzzy logic; Information management; Repair; Stochastic systems; Bridge deterioration; Conceptual design stages; Decision supports; Fuzzy logic decisions; Information management systems; Information Modeling; Infrastructure restorations; Parametric -analysis; Bridges",,,,,,,,"Chan, L., Wu, M., A systematic approach to quality function deployment with a full illustrative example (2005) Omega, 33, pp. 119-139. , Elsevier Ltd; Cheng, M., Hoang, N., Risk score inference for bridge maintenance project using evolutionary fuzzy least squares support vector machine (2012) Journal of Computing in Civil Engineering, 28 (3); Edirisinghe, R., Setunge, S., Zhang, G., Application of gamma process for deterioration prediction of buildings from discrete condition data (2013) Sri Lankan Journal of Applied Statistics, Institute of Applied Statistics, 12, pp. 13-26; Frangopol, D., Kong, J., Gharaibeh, E., Reliability-based life-cycle management of highway bridges (2001) Journal of Computing in Civil Engineering, ASCE, 15 (1), pp. 27-34; Golabi, K., Thompson, P., Hyman, W., (1993) PONTIS Version 2.0 Technical Manual: A Network Optimization System for Bridge Improvements and Maintenance, , Report FHWA-SA-94-031, Office of Technology Applications, Washington, DC; Hawk, H., Bridgit: User-friendly approach to bridge management (1999) 8th International Conference on Bridge Management, , Denver, CO, Paper E7; Hwang, C., Lai, Y., Liu, T., A new approach for multiple objective decision making (1993) Computers and Operational Research, 20, pp. 889-899; Johnson, N., Kotz, S., Balakrishnan, N., (1995) Continuous Univariate Distributions, 2. , 2nd Edition, Wiley, New York; Liang, M., Chang, J., Li, Q., Grey and regression models predicting the remaining service life of existing reinforced concrete bridges (2002) Journal of Grey System, 14 (4), pp. 291-310; Lounis, Z., Madanat, S., Integrating mechanistic and statistical deterioration models for effective bridge managements (2002) 7th International Conference on Applications of Advanced Technology in Transportation, pp. 513-520. , ASCE, Boston, MA; Lounis, Z., Reliability-based life prediction of aging concrete bridge decks (2000) Life Prediction and Aging Management of Concrete Structures, pp. 229-238. , RILEM, France; Madanat, S., Karlaftis, M., McCarthy, P., Probabilistic infrastructure deterioration models with panel data (1997) Journal of Infrastructure Systems, ASCE, 3 (1), pp. 4-9; Malekly, H., Mousavi, S., Hashemi, H., A fuzzy integrated methodology for evaluating conceptual bridge design (2010) Expert System with Applications, 37 (7), pp. 4910-4920. , Elsevier Ltd; Otayek, E., Jrade, A., Alkass, S., Integrated decision support system for bridges at conceptual design stage (2012) CIB W78 ‘29th, pp. 334-343. , Beirut, Lebanon; Pandey, M., Van Noortwijk, J., Gamma process model for time-dependent structural reliability analysis (2004) Proceedings of The 2nd International Conference on Bridge Maintenance, pp. 18-22. , Taylor and Francis, London, UK; Peters, D., Bridge information modeling to cover a complete set of processes (2009) CE & CR, Bentley Systems, pp. 84-86; Reddy, C., Ramudu, B., Arithmetico geometric process maintenance model for deteriorating system under random environment (2013) International Journal of Engineering Science and Technology, 5 (3), pp. 460-467; Sasmal, S., Ramanjaneyulu, K., Gopalakrishnan, S., Lakshmanan, N., Fuzzy logic based condition rating of existing reinforced concrete bridges (2006) Journal of Performance of Constructed Facilities, 20 (3), pp. 261-273; Takács, Matrix factorization and neighbor based algorithms for the Netflix prize problem (2008) Proceedings of The 2008 ACM Conference on Recommender Systems, pp. 267-274. , Lausanne, Switzerland; Tee, A., Bowman, M., Sinha, K., A fuzzy mathematical approach for bridge condition evaluation (1988) Civil Engineering Systems, 5 (1), pp. 17-24; Van Noortwijk, J., Van Der Weide, J., Kallen, M., Pandey, M., Gamma processes and peaks-over-threshold distributions for time-dependent reliability (2007) Reliability Engineering & System Safety, ElSevier, 92 (12), pp. 1651-1658; Van Noortwijk, J., Kallen, M., Pandey, M., Gamma processes for time-dependent reliability of structures (2005) Advances in Safety and Reliability, PERGAMON, Canada, 1, pp. 1457-1464; Wang, Y., Elhag, T., An adaptive neuro-fuzzy inference system for bridge risk assessment (2008) Expert Systems with Applications, 34 (4), pp. 3099-3106; Wang, C., Li, Q., Zou, A., Zhang, L., A realistic resistance deterioration model for time-dependent reliability analysis of aging bridges (2015) Journal of Zhejiang University Science A, 16 (7), pp. 513-524; Zhao, Z., Chen, C., A fuzzy system for concrete bridge damage diagnosis (2002) Computers and Structures, 80 (7-8), pp. 629-641",,,,"Department of Computer Science",,,,,18744753,,,,"English","J. Inf. Technol. Constr.",Article,"Final","",Scopus,2-s2.0-85048048238
"Zhao Y.-P., Vela P.A.","36462199400;8250110600;","Scan2BrIM: IFC Model Generation of Concrete Bridges from Point Clouds",2019,"Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",,,,"455","463",,6,"10.1061/9780784482421.058","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068771887&doi=10.1061%2f9780784482421.058&partnerID=40&md5=d70374aed84d15929f5de4b3684c2611","IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States","Zhao, Y.-P., IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States; Vela, P.A., IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States","Generating a semantically enriched solid model of a structure from point cloud data is time-consuming. Many reinforced concrete bridges consist of a specific set of structures for which a large part of the processing from scan to bridge information model (BrIM) can be automated with today's algorithms. We contribute a pipeline for going from a laser scan point cloud to a BrIM for simple concrete bridges (girder, box girder, and slab). The procedure consists of four major steps: (1) top-down partitioning of the bridges, (2) bottom-up segmentation of the component surface elements, (3) recognition of components from surface elements, and (4) reconstruction of the components. The top-down partitioning step informs machine learning methods for identifying the bridge component type and its geometric model. Application of the pipeline to two bridges demonstrates that conversion to BrIM at level of detail 200 is possible. The pipeline takes less than 1 hour of user time, which is less than scanning time, thus inverting the Scan2BrIM labor ratio. © 2019 American Society of Civil Engineers.",,"Box girder bridges; Bridge components; Bromine compounds; Concrete beams and girders; Concrete bridges; Information theory; Pipelines; Reinforced concrete; Visualization; Geometric modeling; Information Modeling; Level of detail; Machine learning methods; Model generation; Partitioning step; Point cloud data; Surface elements; Learning systems",,,,,,,,"Ahmed, M.F., Haas, C.T., Haas, R., Automatic detection of cylindrical objects in built facilities (2014) Journal of Computing in Civil Engineering, 28 (3), p. 04014009; Anagnostopoulos, I., Belsky, M., Brilakis, I., Object boundaries and room detection in as-is BIM models from point cloud data (2016) Int. Conference on Computing in Civil and Building Engineering, , Paper presented at the; Anagnostopoulos, I., Pǎtrǎucean, V., Brilakis, I., Vela, P., Detection of walls, floors, and ceilings in point cloud data (2016) Construction Research Congress 2016; Bosché, F., Ahmed, M., Turkan, Y., Haas, C.T., Haas, R., The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components (2015) Automation in Construction, 49, pp. 201-213; Chen, J., Fang, Y.H., Cho, Y.K., Unsupervised recognition of volumetric structural components from building point clouds (2017) Int. Workshop on Computing in Civil Engineering, pp. 34-42; Lu, R., Brilakis, I., Recursive segmentation for as-is bridge information modelling (2017) Joint Conference on Computing in Construction, , Paper presented at the, Heraklion, Greece; Lu, R., Brilakis, I., Middleton, C.R., Detection of structural components in point clouds of existing RC bridges (2018) Computer-Aided Civil and Infrastructure Engineering; Pǎtrǎucean, V., Armeni, I., Nahangi, M., Yeung, J., Brilakis, I., Haas, C., State of research in automatic as-built modelling (2015) Advanced Engineering Informatics, 29 (2), pp. 162-171; Riveiro, B., DeJong, M.J., Conde, B., Automated processing of large point clouds for structural health monitoring of masonry arch bridges (2016) Automation in Construction, 72, pp. 258-268; Son, H., Bosché, F., Kim, C., As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure: A survey (2015) Advanced Engineering Informatics, 29 (2), pp. 172-183; Thomson, C., (2016) From Point Cloud to Building Information Model: Capturing and Processing Survey Data Towards Automation for High Quality 3D Models to Aid A BIM Process, , University College London; Thomson, C., Boehm, J., Automatic geometry generation from point clouds for BIM (2015) Remote Sensing, 7 (9), pp. 11753-11775; Wang, C., Cho, Y.K., Kim, C., Automatic BIM component extraction from point clouds of existing buildings for sustainability applications (2015) Automation in Construction, 56, pp. 1-13; Yan, Y., Guldur, B., Hajjar, J.F., Automated structural modelling of bridges from laser scanning (2017) Structures Congress, pp. 457-468; Zhang, G., Vela, P.A., Brilakis, I., Detecting, fitting, and classifying surface primitives for infrastructure point cloud data (2013) Int. Workshop on Computing in Civil Engineering, pp. 589-596; Zhang, G., Vela, P.A., Brilakis, I., Automatic generation of as-built geometric civil infrastructure models from point cloud data (2014) Int. Workshop Computing in Civil and Building Engineering, pp. 406-413; Zhao, Y., Wu, H., Vela, P.A., Top-down partitioning of reinforced concrete bridge components (2019) International Conference on Computing in Civil Engineering, , Paper presented at the, Atlanta, GA",,"Cho Y.K.Leite F.Behzadan A.Wang C.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","ASCE International Conference on Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation, i3CE 2019","17 June 2019 through 19 June 2019",,148901,,9780784482421,,,"English","Comput. Civ. Eng.: Vis., Inf. Model., Simul. - Sel. Pap. ASCE Int. Conf. Comput. Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85068771887
"Isailović D., Petronijević M., Hajdin R.","57205293410;57208599686;6507346536;","The future of BIM and Bridge Management Systems",2019,"IABSE Symposium, Guimaraes 2019: Towards a Resilient Built Environment Risk and Asset Management - Report",,,,"1673","1680",,6,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065253196&partnerID=40&md5=e23707eae1440524d408da7caff880a2","Faculty of Civil Engineering, University of Belgrade, Serbia","Isailović, D., Faculty of Civil Engineering, University of Belgrade, Serbia; Petronijević, M., Faculty of Civil Engineering, University of Belgrade, Serbia; Hajdin, R., Faculty of Civil Engineering, University of Belgrade, Serbia","It is foreseeable that in not so distant future, Building Information Models (BIM) of both newly built and existing bridges will be available. These models can and will be included into the Bridge Management System (BMS) and will significantly enhance the quantity of useful information in future BMS. Apart from exact semantic and spatial specification, BIM can embed realistic structural system of a bridge as well as the relevant load situations. The evaluation of the reliability or safety/serviceability would be therefore possible quasi, on-the-fly within the future BMS, provided that the observations and results from SHM can be adequately integrated in BIM. In principle, the inspection results can be directly captured in the BIM using photogrammetry or some other procedure. Cracks, spalling, deformation, and other defects will be a part of a BIM, which in the most cases alter the BIM geometry. The data stored in future BMS include also other changes that a bridge experience during its life span. This includes strengthening, widening, seismic retrofit and other structural changes. In short fBMS is similar to the 6D BIM or Asset Information Model, which continues to be updated during the whole service life of a bridge. The paper discusses the BIM requirements of owner and operators and shows where these deviate from design and construction needs. It presents conceptual framework for integration of BIM in BMS developed by the authors in recent years. © 2019 IABSE. All rights reserved.","BIM; BMS; BrIM; Inspection","Asset management; Environmental management; Information management; Information theory; Inspection; Semantics; Bridge management system; BrIM; Building Information Model - BIM; Conceptual frameworks; Design and construction; Information Modeling; Seismic retrofits; Structural systems; Architectural design",,,,,"Ministry of Education, MOE; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja: TR-36038","The authors thank Peter Bonsma and RDF for making the prototype software development possible by providing the IFCEngine DLL, as well as the tremendous help in using this useful toolbox. Also thank to the Public Enterprise Roads of Serbia for providing the graphic documentation of the case bridge. This work is partly funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia under grant TR-36038. It is a part of the project ‘Development of the method for the production of MEP design and construction documents compatible with BIM process and related standards.’","since the entity identifiers ?STEP Id ? are changed The authors thank Peter Bonsma and RDF for during the model export 縁?ee ? ? ? ? ? The mmetakihnodg the prototype software development would be applied to export model in Figure ??possiblebyprovidingtheIFCEngineDLL?aswellas Currently? the method is being developed by the tremendous help in using this useful toolbox ? exploitingthedifferencesbetweentheimportand Also thank tothePublicEnterprise Roadsof Serbia export model? The entities that need to be for providing the graphic documentation of the investigatedareidentifiedbya timestampthatis case bridge ? This work is partly funded by the generated by the application that changes the Ministry of Education ? Science and Technological importedmodel ? DevelopmentoftheRepublicofSerbia undergrant TR???????It isa partoftheproject RDevelopment of the method for the production of MEP design andconstructiondocumentscompatiblewithBIM processandrelatedstandards??","Mašović, Hajdin, R., Planiranje održavan putnih mostova (2014) ZBORNIK RADOVA Pr Srpski Kongres O Putevima, , Belgrade; (2016) Bridge Informatio Modeling Standardization Report, , S. Department of Transportaton, Feder Highway Administration; National Building Information Modeling Guid for Owners, , https://www.nibs.org/; buildingSMARTInternational, , https://www.buildingsmart.org/; (2004) ISO 10303-11:2004 Industrial Automatio Systems and Integration - Product Da Representation and Exchange - Part 1 Description Methods: The EXPRESS Languag Reference Manual, , International Organization for Standardizatio ISO, Geneva; Liebich, IFC 2x Edition 3 Model Implementatio Guide (2009) buildingSMART International; Ryall, J., (2010) Bridge Management, , Amsterdam Elsevier; Mirzaei, Adey, B., Klatter, L., Thompso, P., The IABMaS bridge management committe overview of existing bridge managemen systems (2014) International Association for Bridg Maintenance and Safety - IABMAS; (2011) Government Constructio Strategy 2011-15, , a. Authority UK Government, Londo; Hajdin, Kušar, M., Mašović, S., Linneberg, P., Amado, Tanasić, N., WG3 technical repo establishment of a quality control plan (2018) COS Action TU1406; (2007) Sustainable Bridges Assessment for Future Traffic Demands An Longer Lives, , http://sustainablebridges.net, stainableBridges Online. Availabl; Sacks, Kedar, A., Borrmann, A., Ma, L., Brilaki, I., Hüthwohl, P., Daum, S., Muhic, S., SeeBridg as next generation bridge inspection: Overview information delivery manual and model vie definitio (2018) Automation in Construction, pp. 134-145; Stojanović, Richter, R., Döllner, J., Trap, M., Comparative visualization of BIM geometry an corresponding Point Clouds (2018) Internation Journal of Sustainable Development An Planning, 13 (1), pp. 12-23; IFC4Add Documentation, , http://www.buildingsmarttech.org/ifc/IFC4/Add2/html/; Hüthwohl, Brilakis, I., Borrmann, A., Sack, R., Integrating RC bridge defect information int BIM models (2018) Journal of Computing in Civ Engineering, 32 (3); Rosenthaler, Koch, R., Hajdin, R., Botze, M., (2015) Zeitaspekte und Historisierung. Schriftenreih 1516, , Eidgenössisches Departement fü Umwelt, Verkehr, Energie und Kommunikatio UVEK, Bundesamt für Strassen, Bern","Hajdin, R.; Faculty of Civil Engineering, Serbia; email: rade.hajdin@grf.bg.ac.rs",,"Allplan;Brisa;Maurer;S and P","International Association for Bridge and Structural Engineering (IABSE)","IABSE Symposium 2019 Guimaraes: Towards a Resilient Built Environment - Risk and Asset Management","27 March 2019 through 29 March 2019",,147396,,9783857481635,,,"English","IABSE Symp., Guimaraes: Towards Resilient Built Environ. Risk Asset Manag. - Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85065253196
"Hajdin R.","6507346536;","Managing existing bridges - on the brink of an exciting future",2018,"Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges - Proceedings of the 9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018",,,,"63","87",,6,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065289745&partnerID=40&md5=ab481f8ad8c47cdeccfc6e755e961933","Infrastructure Management Consultants GmbH, Zurich, Switzerland; Faculty of Civil Engineering, University of Belgrade","Hajdin, R., Infrastructure Management Consultants GmbH, Zurich, Switzerland, Faculty of Civil Engineering, University of Belgrade","It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition state, which is based upon observable damages recorded during inspections. Condition state is at best, only loosely correlated to safety and serviceability. It would be more reasonable to address safety and serviceability in inspection process directly, using the information on bridge performance obtained during the design and construction. The future Bridge Management Systems (fBMS) should therefore include this information allowing assessment of safety and serviceability based on inspection results. By including Bridge Information Models that are currently being developed and Structural Health Monitoring, the fBMS will become an invaluable decision-support tool not only for maintenance planning but also for issuing special permits, specification of heavy vehicle corridors, risk assessment due to natural hazards, etc. © 2018 Taylor & Francis Group, London, UK.","Bridges; Maintenance; Performance Indicators; Reliability; Safety; Service life; Serviceability","Accident prevention; Decision support systems; Health hazards; Health risks; Information management; Inspection; Life cycle; Maintenance; Reliability; Risk assessment; Service life; Structural health monitoring; Bridge management system; Bridge performance; Decision support tools; Design and construction; Inspection process; Maintenance planning; Performance indicators; Serviceability; Bridges",,,,,"Bundesanstalt für Straßenwesen, BASt: FE 15.0628/2016/LRB","This paper is partially based upon work supported by the German Federal Highway Research Institute under grant FE 15.0628/2016/LRB. Parts of paper address the work from COST Action TU-1406, Quality specifications for roadway bridges, standardization at a European level (BridgeSpec), supported by COST (European Cooperation in Science and Technology). The author is the leader of the Working Group 3 of the COST Action TU1406.",,"Adey, B., Hajdin, R., Methodology for determination of financial needs of gradually deteriorating bridges (2011) Journal of Structure and Infrastructure Engineering, 77 (8), pp. 645-660; Adey, B., Hajdin, R., Brühwiler, E., Supply and Demand System Approach to the Development of Bridge Management Strategies (2003) ASCE Journal of Infrastructure Systems, 3 (3), pp. 117-131; Adey, B., Hajdin, R., Van Linn, A., Welte, U., (2009) Effectiveness and Efficiency of Interventions on Highway Structures (In German), , Zurich: VSS, Report 625; Adey, B., Methodology and Base Cost Models to Determine the Total Benefits of Preservation Interventions and Road Sections in Switzerland (2012) Journal of Structure and Infrastructure Engineering, 8 (7), pp. 639-654; Alnaggar, M., Di Luzio, G., Cusatis, G., Modeling Time-Dependent Behavior of Concrete Affected by Alkali Silica Reaction in Variable Environmental Conditions (2017) Materials, 10 (5), p. 471; (2006) The Benefit of Transportation - Subproject: Contribution of Transportation to Value Creation in Switzerland (Der Nutzen Des Verkehrs - Teilprojekt: Beitrag Des Verkehrs Zur Wertschöpfung in Der Schweiz), , Bern: Federal Office for Spatial Development and Federal Roads Office; Management of natural hazards on NHS (In German: Management von Naturgefahren auf den Nationalstrassen), Guidelines (2014) Bern: Swiss Federal Roads Office; (2015) Phase Plan for Digital Planning and Constructing(Stufenplan Digitales Planen Und Bauen), , Berlin: Federal Ministry of Transport and Digital Infrastructure; Part 3: Analysis of existing road bridges due to special transports (2016) Provisions and Guidelines for Analysis and Diemsnioning of Structures (In German), , Bonn: Fedral Ministry of Transport and Digital Infrastructure; Bocchini, P., Frangopol, D.M., Ummenhofer, T., Zinke, T., Resilience and Sustainability of Civil Infrastructure: Toward a Unified Approach (2014) ASCE Journal of Infrastructure Systems, 20 (2); Braml, T., Wurzer, O., Probabilistic analysis methods as an additional component for the integrated assessment of existing bridges (In German) (2012) Beton-Und Stahlbetonbau, 10710, pp. 654-668; Bruneau, M., A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities (2003) Earthquake Spectra, 19 (4), pp. 733-752; (2018) Ifcstructuralanalysismodel, , http://www.buildingsmarttech.org/ifc/IFC2x3/TC1/html/ifcstructuralanalysisdomain/lexical/ifcstructuralanalysismodel.htm, [Zugriff am 02 01 2018]; Calgaro, J.-A., Sedlacek, G., (1992) EC1: Traffic Loads on Road Bridges, p. 65. , IABSE reports, Band; Caprani, C., Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification (2013) ASCE Journal of Bridge Engineering, 189, pp. 901-909; Cawley, P., Structural health monitoring: Closing the gap between research and industral development (2018) Structural Health Monitoring, pp. 1-20; Cen, E.N., (1990) 2002. Basis of Structural Design, , Brussels: European Committee for Standardisation; Chipman, T., Bridge Information Modeling Standardization (2016) Report No. FHWA-HIF-16-011, , Washington D. C.: FHWA; Das, P., Development of a comprehensive structures management methodology for the Highways Agency (1999) Management of Highway Structures, , London: ICE, Highways Agency; Enright, B., O'brien, E.J., Monte Carlo simulation of extreme traffic loading on short and medium span bridges (2013) Structure and Infrastructure Engineering, 912, pp. 1267-1282; Faber, M.H., (2009) Methodological Basis for Comparative Risk Assessment (In German), p. 618. , VSS, Report; Faber, M.H., Qin, J., Miraglia, S., Thöns, S., (2016) 2017. on the Probabilistic Characterization of Robustness and Resilience. Procedia Engineering,, 198, Special Issue, pp. 1070-1083. , Urban Transitions Conference, Shanghai; Freundt, U., Bönning, S., Traffic load models for recalculation of existing (Verkehrslastmodelle für die Nachrechnung von Straßenbrücken im Bestand) (2011) Bonn: Federal Highway Institute; Frischmann, B.M., Infrastructure - the social value of shared resources (2012) New York: Oxford University Press; Hajdin, R., Visual inspections and key performance indicators - Bridging the gap. Transportation Research Circular (2017) 11Th International Bridge and Structures Management Conference, , October, Issue E-C224; Hajdin, R., (2017) Bridge Resilience, , Zurich: IMC GmbH (unpublished manustript); Hajdin, R., Despot, Z., TRUCK - Bridge Rating Software (1999) International Bridge Management Conference, Denver, , Colorado, April 26-28, 1999. Washington D. C.: Transportation Research Board; Hajdin, R., Holst, R., Büchel, B., Rabe, R., A new practice-oriented approach for relibability-based bridge inspections (To be published) (2018) The Sixth International Symposium on Life-Cycle Civil Engineering; Hajdin, R., Peeters, L., Bridging Data Voids: Advanced Statistical Methods for Bridge Management in KUBA (2008) 10Th International Bridge and Structure Management Conference, Buffalo, New York, pp. 90-104. , TRB Circular E-C128, October; Heitzler, M., A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures (2017) Cartographica: The International Journal for Geographic Information and Geovisualization, 52 (4), pp. 349-353; Hüthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC Bridge Defect Information into BIM Models (2018) ASCE Journal of Computing in Civil Engineering, 32 (3). , 04018013; (2013) Probabilistic Model Code, , Lyngby: Joint Committee for Structural Safety; Kurte, J., Esser, K., Benefit of road traffic (Nu zen des Straßenverkehres) (2008) ADAC Study on Mobility (In German), , Munich: ADAC (Ed.); Lethanh, N., Hackl, J., Adey, B., Determination of Markov Transition Probabilities to be Used in Bridge Management from Mechanistic-Empirical Models (2017) ASCE Joournal of Bridge Engineering, 22 (10); Linneberg, P., Mašović, S., Hajdin, R., (2017) Quality Control Plans for Girder and Frame Bridges, , IABSE Symposium, Vancouver; Lou, P., Nassif, H., Truban, P., Development of live load model for strenght II limit state in AASHTO LRFD design specifications (2018) Transportation Reserach Board, Annual Meeting; Mandić Ivanković, A., Skokandić, D., Žnidarič, A., Kreslin, M., Bridge performance indicators based on traffic load monitoring (2017) Structure and Infrastructure Engineering, pp. 1-13; Mertz, D., (2005) Load Rating by Load and Resistance Factor Evaluation Method, , Washington D. C.: Transportation Research Board; Meystre, T., Hirt, M., (2006) Examination of Existing Road Bridges with Updated Road Loads (Überprpfung Bestehnder Strassenbrücken Mit Aktualisierten Strassenlasten), , Bern: Swiss Federal Roads Office; (1997) Concrete Details Vulnerability Manual, , Albany, NY: New York State Departement of Transportation; Padgett, J., Dennemann, K., Ghosh, J., Risk-based seismic life-cycle cost-benefit (LCC-B) analysis for bridge (2010) Structural Safety, 32 (3), pp. 165-173; Roelfstra, G., Hajdin, R., Adey, B., Brühwiler, E., Condition Evolution in Bridge Management Systems and Corrosion-Induced Deterioration (2004) ASCE Journal of Bridge Engineering, 9 (3), pp. 268-277; Schiffmann, F., Hajdin, R., (2017) Lont-Term Work Zone Planning for Highway Infrastructure. World Conference on Pavement and Asset Management, , WCPAM2017, June; (2011) SIA 269 - Maintenance of Existing Structures, , Zurich: Swiss Engineers and Architects Association; Tanasic, N., Hajdin, R., Management of Bridges with Shallow Foundations Exposed to Local Scour (2017) Journal of Structure and Infrastructure Engineering, Special Issue on IABMAS 2016; Treacy, M.A., Brühwiler, E., Are current bridge load modelling techniques realistic for existing road bridges? (2014) Bridge Maintenance, Safety, Management and Life Extension, 7Th International Conference on Bridge Maintenance, Safety and Management (IABMAS), pp. 340-347. , F. &. R. Chen, London: Taylor & Francis Group; (2015) Industry Snapshots: Uses of Transportation, , Wahsington D.C.: U.S. Departement of Transportation; (2003) Swiss Norm 640 904: Evaluation of Pavements, Road Structures and Equipment: Substance and Utilization Values, Zurich: Swiss Association of Road and Transport Experts, , https://en.wikipedia.org/wiki/6D_BIM, Wikipedia, 2017. 6D BIM., [Accessed 21 February 2018]","Hajdin, R.; Infrastructure Management Consultants GmbHSwitzerland","Powers N.Frangopol D.M.Al-Mahaidi R.Caprani C.","et al.;IABMAS, International Association for Bridge Maintenance and Safety;Monash University;RMIT University;Swinburne University of Technology;VicRoads","CRC Press/Balkema","9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018","9 July 2018 through 13 July 2018",,226219,,9781138730458,,,"English","Maint., Saf., Risk, Manag. Life-Cycle Perform. Bridges - Proc. Int. Conf. Bridge Maint., Saf. Manag.",Conference Paper,"Final","",Scopus,2-s2.0-85065289745
"Costin A.M., Eastman C., Issa R.R.A.","55200193500;7102374797;35587852800;","The Need for Taxonomies in the Ontological Approach for Interoperability of Heterogeneous Information Models",2017,"Congress on Computing in Civil Engineering, Proceedings","2017-June",,,"9","17",,6,"10.1061/9780784480830.002","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026862114&doi=10.1061%2f9780784480830.002&partnerID=40&md5=279cb7179ce4081a609cb1165a282c58","M. E. Rinker, Sr. School of Construction Management, Univ. of Florida, P.O. Box 115703, Gainesville, FL  32611, United States; School of Architecture, Georgia Institute of Technology, United States","Costin, A.M., M. E. Rinker, Sr. School of Construction Management, Univ. of Florida, P.O. Box 115703, Gainesville, FL  32611, United States; Eastman, C., School of Architecture, Georgia Institute of Technology, United States; Issa, R.R.A., M. E. Rinker, Sr. School of Construction Management, Univ. of Florida, P.O. Box 115703, Gainesville, FL  32611, United States","With the future becoming more technologically advanced with the modeling of all types of information across varying domains, it is imperative that the information contained in the models can be shared and exchanged seamlessly and effortlessly by the end user. The purpose of this research is to develop a methodology that would enable the interoperability of multi-disciplinary information models. Current methods of producing information models have been mostly dependent on proprietary software programs, non-compatible program languages, or standards specific to only a single domain. Therefore, the objective is to have a methodology that applies across the heterogeneous landscape of information modeling. Although the approach is extendable to other domains, the scope for this paper is for bridge information modeling (BrIM) and the architecture, engineering, construction, and operations (AECO) industry. This research is motivated by the fundamental issues of interoperability, such as semantics, logic, and software issues. The use of an ontology, the formal naming and definition of the types, properties, and interrelationships of the entities in a domain, has been shown to facilitate the sharing of knowledge. This paper builds on the assertion that a well-established taxonomy, a formal hierarchical classification of terms, is the imperative first step in defining an ontology. Therefore, the focuses of this paper is a discussion of defining and organizing a taxonomy. An ongoing case study with a joint industry subcommittee of the American Association of State Highway and Transportation Officials (AASHTO) and the National Steel Bridge Alliance (NSBA) is used to evaluate and validate the methodology. Preliminary results of taxonomy being developed by the case study is presented to show the importance of defining the semantic and syntactic information in a natural language to promote interoperability. By reducing semantic issues and maintaining consistency of terminology at the software level, reliable, automatic, and standardized electronic exchange of data can be ultimately achieved. © 2017 ASCE.","Information modeling; Interoperability; Ontology; Semantic and syntactic information; Taxonomy","Computation theory; Information theory; Interoperability; Ontology; Semantics; Syntactics; Taxonomies; American Association of State Highway and Transportation Officials; Heterogeneous information; Heterogeneous landscapes; Hierarchical classification; Information Modeling; Ontological approach; Proprietary software; Syntactic information; Bridges",,,,,,,,"Cheng, C.P., Lau, G.T., Law, K.H., Pan, J., Jones, A., Regulation retrieval using industry specific taxonomies (2008) Artificial Intelligence and Law, 16 (3), pp. 277-303; Costin, A., (2016) A New Methodology for Interoperability of Heterogeneous Bridge Information Models, , PhD Diss., School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA; Eastman, C.M., Chapter four: Modeling concepts (1999) Building Product Models: Computer Environments, Supporting Design and Construction, , CRC press; El-Diraby, T.E., Osman, H., A domain ontology for construction concepts in urban infrastructure products (2011) Automation in Construction, 20 (8), pp. 1120-1132; El-Diraby, T.E., Lima, C., Feis, B., Domain taxonomy for construction concepts: Toward a formal ontology for construction knowledge (2005) J. Comput. Civ. Eng., 19 (4), pp. 394-406; El-Diraby, T.E., Zhang, J., A semantic framework to support corporate memory management in building construction (2006) Automation in Construction, 15 (4), pp. 504-521; El-Diraby, T.E., Domain ontology for construction knowledge (2013) J. Constr. Eng. Manage., 139 (7), pp. 768-784; El-Gohary, N.M., El-Diraby, T.E., Domain ontology for processes in infrastructure and construction (2010) J. of Constr. Eng. Mgmt., 136 (70), pp. 730-744; Hu, H., (2014) Development of Interoperable Data Protocol for Integrated Bridge Project Delivery, , Ph.D. Dissertation, Dept. of Civil, Structural, and Environmental Engineering, University at Buffalo; Issa, R.R., Mutis, I., (2015) Ontology in the AEC Industry, , ASCE Press; Li, S., Sun, Y., Soergel, D., A new method for automatically constructing domain-oriented term taxonomy based on weighted word co-occurrence analysis (2015) Scientometrics, 103 (3), pp. 1023-1042; Lin, H.K., Harding, J.A., A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration (2007) Computers in Industry, 58 (5), pp. 428-437; Meijer, K., Frasincar, F., Hogenboom, F., A semantic approach for extracting domain taxonomies from text (2014) Decision Support Systems, 62, pp. 78-93; (2015) United States National Building Information Modeling Standard Version 3, , National Institute of Building Sciences (NIBS). The Northern American Chapter of buildingSMART International (bSI); Niu, J., Issa, R.R., Conceptualizing methodology for building an ontology for construction claim knowledge (2013) ASCE International Conference on Computing in Civil Engineering; Uschold, M., Gruninger, M., Ontologies: Principles, methods and applications (1996) Knowl. Eng. Rev., 11 (2), pp. 93-155; Venugopal, M., Eastman, C., Teizer, J., An ontological approach to building information model exchanges in the precast/pre-stressed concrete industry (2012) Construction Research Congress; Zhang, J., El-Diraby, T.E., Sswp: A social semantic web portal for effective communication in construction (2009) J. of Computers, Academy Publisher, 4 (4), pp. 330-337; Zhang, S., Boukamp, F., Teizer, J., Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA) (2015) Automation in Construction, 52, pp. 29-41",,"Lin K.-Y.El-Gohary N.Tang P.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017","25 June 2017 through 27 June 2017",,129092,,9780784480830,CCENE,,"English","Comput Civ Eng (New York)",Conference Paper,"Final","",Scopus,2-s2.0-85026862114
"Markiz N., Jrade A.","55358120700;12804778900;","Integrating an expert system with BrIMS, cost estimation, and linear scheduling at conceptual design stage of bridge projects",2022,"International Journal of Construction Management","22","5",,"913","928",,5,"10.1080/15623599.2019.1661572","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073835810&doi=10.1080%2f15623599.2019.1661572&partnerID=40&md5=3d0292b27cc3b37441cd755a4588ed66","Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada","Markiz, N., Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada; Jrade, A.","Highway networks are a major infrastructure system, most crucially major bridges and motorways. Proper handling of highway networks plays a significant role in enhancing the functionality of a bridge network. Besides that, estimating bridge construction costs is an increasing necessity at the conceptual design stage for accurate budgeting and effective funding. The degree of subjectivity involved in decision making of bridge projects is the main factor that influences bridge cost estimation and linear scheduling at the conceptual design stage. Objectives of this study are intended to demonstrate the viability of integrating a decision support system comprising qualitative objective functions with a bridge information management system (BrIMS) in order to overcome subjectivity in decision makings. An external data interchange protocol is implemented in synchrony with interoperability standards. The deployment of the proposed system shall include an all-in-one bridge construction cost estimation tool that can provide users with recommendations for bridge design alternatives. An integration of an expert system, cost estimation, and linear scheduling is proposed by automating cost and time scheduling techniques at the conceptual design stage. Successful implementation of such a system is a technological achievement of novelty to the integration of BrIMS solutions with probabilistic fuzzy logic strategic approaches. © 2019 Informa UK Limited, trading as Taylor & Francis Group.","bridge information management system (BrIM); cost estimation; Expert system; linear schedule",,,,,,,,,"Agrawal, K., Benoit, A.M.L., Robert, Y., Scheduling algorithms for linear workflow optimization (2010) 24th IEEE International Symposium on Parallel and Distributed Processing (IPDPS), pp. 19-23. , Atlanta, Georgia; An, S.H., Kim, G.H., Kang, K.I., A case-based reasoning cost estimating model using experience by analytic hierarchy process (2007) Build Environ, 42 (7), pp. 2573-2579. , Elsevier; Ding, L., Zhou, Y., Akinci, E., Building information modeling (BIM) application framework: The process of expanding 3D to computable nD (2014) Automat Constr, 46, pp. 82-93. , Elsevier; Elbeltagi, E., Dawood, M., Integrated visualized time control system for repetitive construction projects (2011) Automat Constr, 20 (7), pp. 940-953; Hinze, J., (2008) Construction planning and scheduling, , 3rd ed, Upper Saddle River (NJ): Pearson Prentice Hall; Jeong, W.S., Chang, S., Son, J.W., BIM-Integrated construction operation simulation for just-in-time production management (2016) Sustain Multidiscip Dig Publ Inst (MDPI), 8 (11), pp. 1-25; Kim, K.J., Yun, W.G., Cho, N., Ha, J., Life cycle assessment based environmental impact estimation model for pre-stressed concrete beam bridge in the early design phase (2017) Environ Imp Assess Rev, 64, pp. 47-56. , Elsevier; Kivimäki, T., Heikkilä, R., (2009) Integrating 5D product modelling to on-Site 3D surveying of bridges, pp. 445-450. , ISARC ‘26th’, Austin (TX; Lee, K.M., Lee, Y.B., Shim, C.S., Park, K.L., Bridge information models for construction of a concrete box-girder bridge (2012) Struct Infrastruct Eng, 8 (7), pp. 687-703; Liu, W., Flood, I., Issa, R., Simulation and optimization of linear construction projects (2005) International Conference on Computing in Civil Engineering, ASCE; Cancun, Mexico, pp. 1-11; Makovsek, D., Systematic construction risk, cost estimation mechanism and unit price movements (2014) Transport Pol, 35, pp. 135-145. , Elsevier; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) J Bridge Eng, 21 (4), p. 04015076; Peurifoy, R., Oberlender, G., (2002) Estimating construction costs, , 5th ed, New York, United States: McGraw Hill Education; Shim, C., Yun, N., Song, H., Application of 3D bridge information modeling to design and construction of bridges (2011) Proc Eng, 14, pp. 95-99. , Elsevier; Shirole, A.M., Riordan, T.J., Chen, S.S., Gao, Q., Hu, H., Puckett, J.A., BrIM for project delivery and the life-cycle: state of the art (2009) Bridge Struct, 5 (4), pp. 173-187; Song, L., Lee, S.-H., Rachmat, F., Stochastic look-ahead scheduling method for linear construction projects (2012) JRACR, 2 (4), pp. 252-260; Su, Y., Lucko, G., Linear scheduling with multiple crews based on line-of-balance and productivity scheduling method with singularity functions (2016) Automat Construct, 70, pp. 38-50. , Elsevier; Tang, Y., Liu, R., Wang, H.L., Sun, Q., Schedule control model for linear projects based on linear scheduling method and constraint programming (2014) Automat Construct, 37, pp. 22-37","Markiz, N.; Department of Civil Engineering, Canada; email: nmark086@uottawa.ca",,,"Taylor and Francis Ltd.",,,,,15623599,,,,"English","Int. J. Constr. Manage.",Article,"Final","",Scopus,2-s2.0-85073835810
"Wei J., Chen G., Huang J., Xu L., Yang Y., Wang J., Sadick A.-M.","8912426300;57226068758;56135543200;57199907218;57192551695;55671780900;56548806100;","Bim and gis applications in bridge projects: A critical review",2021,"Applied Sciences (Switzerland)","11","13","6207","","",,4,"10.3390/app11136207","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110277221&doi=10.3390%2fapp11136207&partnerID=40&md5=d31cfe62e67b5cfc21048f2e1c36ff2c","College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China; College of Civil Engineering, Fujian University of Technology, Fuzhou, 350116, China; School of Architecture and Built Environment, Deakin University, Geelong, 3220, Australia","Wei, J., College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China, College of Civil Engineering, Fujian University of Technology, Fuzhou, 350116, China; Chen, G., College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China; Huang, J., College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China; Xu, L., College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China; Yang, Y., College of Civil Engineering, Fuzhou University, Fuzhou, 350116, China; Wang, J., School of Architecture and Built Environment, Deakin University, Geelong, 3220, Australia; Sadick, A.-M., School of Architecture and Built Environment, Deakin University, Geelong, 3220, Australia","In recent years, interest in BIM and GIS applications in civil engineering has been growing. For bridge engineering, BIM/GIS applications such as simulation, visualization, and secondary development have been used to assist practitioners in managing bridge construction and decision-making, including selection of bridge location maintenance decisions. In situ 3D modelling of existing bridges with detailed images from UAV camera has allowed engineers to conduct remote condition assessments of bridges and decide on required maintenance actions. Several studies have investigated the applications of BIM/GIS technology on bridge projects. However, there has been limited focus on reviewing the outcomes of these studies to identify the limitations of BIM and GIS applications on bridge projects. Therefore, the aim of this study was to review the research on BIM/GIS technology applications in bridge projects over the last decade. Using a systematic review process, a total of 90 publications that met the inclusion criteria were reviewed in this study. The review identified the state-of-the-art methods of BIM and GIS applications, respectively, at the planning and design, construction, and operation and maintenance phases of bridge projects. However, the findings point to segregated application of BIM and GIS at all phases of bridge projects. The findings of this study will contribute to guiding practitioners in selecting appropriate BIM and GIS technologies for different aspects of bridge projects. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.","Application; Bridge; Bridge Information Modelling (BrIM); Building Information Modelling (BIM); Geographical Information System (GIS)",,,,,,"Australian Research Council, ARC: LP180100222; National Natural Science Foundation of China, NSFC: 51878172; 2019H6020","This research was funded by the National Natural Science Foundation (Grant No. 51878172), Australian Research Council’s Linkage Project funding scheme (project LP180100222), university industry research cooperation project in Fujian Province (Grant No. 2019H6020), and The Program for Innovative Research Teams in Science and Technology in Fujian Province University.",,"Liu, W.P., Guo, H.L., Li, H., Li, Y., Using BIM to Improve the Design and Construction of Bridge Projects: A Case Study of a Long-span Steel-box Arch Bridge Project (2014) Int. J. Adv. 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Appl, 5, pp. 57-73; Fanning, B., Clevenger, C.M., Ozbek, M.E., Mahmoud, H., Implementing BIM on Infrastructure: Comparison of Two Bridge Construction Projects (2015) Pract. Period. Struct. Des. Constr, 20, p. 04014044. , [CrossRef]; Shim, C.S., Lee, K.M., Kang, L.S., Hwang, J., Kim, Y., Three-Dimensional Information Model-Based Bridge Engineering in Korea (2012) Struct. Eng. Int, 22, pp. 8-13. , [CrossRef]; Vilventhan, A., Rajadurai, R., 4D Bridge Information Modelling for management of bridge projects: A case study from India (2020) Built Environ. Proj. Asset Manag, 10, pp. 423-435. , [CrossRef]; Sakdirat, K., Jessada, S., Zhihao, Z., Sustainability-Based Lifecycle Management for Bridge Infrastructure Using 6D BIM (2020) Sustain-ability, 12, p. 2436; Dang, N.S., Rho, G.T., Shim, C.S., A Master Digital Model for Suspension Bridges (2020) Appl. 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Softw, 130, pp. 24-40. , [CrossRef]; Changsu, S., Hwirang, K., Son, D.N., Deokkeun, L., Development of BIM-based bridge maintenance system for cable-stayed bridges (2017) Smart Struct. Syst, 20, pp. 697-708; Hong, J.H., Kuo, C.L., A semi-automatic lightweight ontology bridging for the semantic integration of cross-domain geospatial information (2015) Int. J. Geogr. Inf. Sci, 29, pp. 2223-2247. , [CrossRef]; Park, S., Park, J., Kim, B.G., Lee, S.H., Improving Applicability for Information Model of an IFC-Based Steel Bridge in the Design Phase Using Functional Meanings of Bridge Components (2018) Appl. Sci, 8, p. 2531. , [CrossRef]; Floros, G.S., Boyes, G., Owens, D., Ellul, C., Developing ifc for infrastructure: A case study of three highway entities (2019) ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci, IV-4, pp. 59-66. , [CrossRef]; Mohamed, M., Mohamed, H., A hybrid model for selecting location of mobile cranes in bridge construction projects (2013) Balt. J. 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Eng, 32, p. 04018013. , [CrossRef]; Davila Delgado, J.M., Butler, L.J., Gibbons, N., Brilakis, I., Elshafie, M.Z., Middleton, C., Management of structural monitoring data of bridges using BIM (2017) Bridge Eng, 170, pp. 204-218. , [CrossRef]; Lee, J.H., Park, J.J., Yoon, H., Automatic Bridge Design Parameter Extraction for Scan-to-BIM (2020) Appl. Sci, 10, p. 7346. , [CrossRef]; Sedek, M., Serwa, A., Development of new system for detection of bridges construction defects using terrestrial laser remote sensing technology (2016) Egypt. J. Remote Sens. Space Sci, 19, pp. 273-283. , [CrossRef]; McKenna, T., Minehane, M., O’Keeffe, B., O’Sullivan, G., Ruane, K., Bridge information modelling (BrIM) for a listed viaduct (2017) Bridge Eng, 170, pp. 192-203. , [CrossRef]; Ali, N., Chen, S.S., Srikonda, R., Hu, H., Development of Concrete Bridge Data Schema for Interoperability (2014) Transp. Res. Rec. J. Transp. Res. Board, 2406, pp. 87-97. , [CrossRef]; Abbas, R., Ebrahim, K., Video to BrIM: Automated 3D As-Built Documentation of Bridges (2018) J. Perform. Constr. Facil, 32, p. 04018026; Lu, R., Brilakis, I., Digital twinning of existing reinforced concrete bridges from labelled point clusters (2019) Automat. Constr, 105, p. 102837. , [CrossRef]; Ziboon, A.R.T., Qasim, Z.I., Falih, K.T., Gis application to evaluate transportations network in nasiriyah city (2017) J. Eng. Sustain. Dev, 21, pp. 75-87; Almumaiz, M.O., Improvement of Transportation Network of Al-Muwaffaqiyah Town Using Gis (2014) J. Eng. Dev, 18, pp. 229-245; Liu, Y.L., Xu, K.H., GIS for Highway Engineering Bearing Capacity Evaluation (2014) J. Highw. Transp. Res. Dev, 8, pp. 28-33. , [CrossRef]; Ardeshir, A., Mohseni, N., Behzadian, K., Errington, M., Selection of a Bridge Construction Site Using Fuzzy Analytical Hierarchy Process in Geographic Information System (2014) Arab. J. Sci. 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Geogr, 112, p. 102095. , [CrossRef]; Junxiang, Z., Xiangyu, W., Peng, W., Zhiyou, W., Mi Jeong, K., Integration of BIM and GIS: Geometry from IFC to shapefile using open-source technology (2019) Automat. Constr, 102, pp. 105-119; Chong, H.Y., Lopez, R., Wang, J., Wang, X., Zhao, Z., Comparative analysis on the adoption and use of BIM in road infrastructure projects (2016) J. Manag. Eng, 32, p. 05016021. , [CrossRef]; Wang, J., Sun, W., Shou, W., Wang, X., Wu, C., Chong, H.Y., Liu, Y., Sun, C., Integrating BIM and LiDAR for real-time construction quality control (2015) J. Intel. Robot. Syst, 79, pp. 417-432. , [CrossRef]; Zhu, J., Wright, G., Wang, J., Wang, X., A critical review of the integration of geographic information system and building information modelling at the data level (2018) ISPRS Int. J. Geo-Inform, 7, p. 66. , [CrossRef]; Xu, S., Wang, J., Shou, W., Ngo, T., Sadick, A.M., Wang, X., Computer vision techniques in construction: A critical review (2020) Arch. Comput. Methods Eng, pp. 1-15. , [CrossRef]; Tsai, Y.H., Wang, J., Chien, W.T., Wei, C.Y., Wang, X., Hsieh, S.H., A BIM-based approach for predicting corrosion under insulation (2019) Automat. Constr, 107, p. 102923. , [CrossRef]","Wang, J.; School of Architecture and Built Environment, Australia; email: jun.wang1@deakin.edu.au",,,"MDPI AG",,,,,20763417,,,,"English","Appl. Sci.",Article,"Final","All Open Access, Gold",Scopus,2-s2.0-85110277221
"Nili M.H., Zahraie B., Taghaddos H.","57220864570;57203578183;26031827800;","BrDSS: A decision support system for bridge maintenance planning employing bridge information modeling",2020,"Smart Structures and Systems","26","4",,"533","544",,4,"10.12989/sss.2020.26.4.533","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098057627&doi=10.12989%2fsss.2020.26.4.533&partnerID=40&md5=63438cb4a4881aeef2b5e5d954c55513","School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran","Nili, M.H., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Zahraie, B., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Taghaddos, H., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran","Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran. Copyright © 2020 Techno-Press, Ltd.","Bridge Information Modeling (BrIM); Bridge maintenance management; Decision Support System (DSS); Genetic Algorithm (GA); Maintenance optimization","3D modeling; Decision making; Decision support systems; Genetic algorithms; Information theory; Life cycle; Maintenance; Planning; Bridge maintenance management; Decision support system (dss); Infeasible solutions; Information Modeling; Maintenance planning; Optimization modeling; Optimization module; Parametric modeling; Bridges",,,,,,,,"Adhikari, R.S., Bagchi, A., Moselhi, O., Automated condition assessment of concrete bridges with digital imaging (2014) Smart Struct. Syst., Int. J, 13 (6), pp. 901-925. , https://doi.org/10.12989/sss.2014.13.6.901; Adibfar, A., Costin, A., (2019) Advances in Informatics and Computing in Civil and Construction Engineering, , Springer, Switzerland; Akhoundan, M.R., Khademi, K., Bahmanoo, S., Wakil, K., Mohamad, E.T., Khorami, M., Practical use of computational building information modeling in repairing and maintenance of hospital building-case study (2018) Smart Struct. Syst., Int. J, 22 (5), pp. 575-586. , http://dx.doi.org/10.12989/sss.2018.22.5.575; Alikhani, H., Alvanchi, A., Using genetic algorithms for long-term planning of network of bridges (2017) Scientia Iranica, 26 (5), pp. 2653-2664. , http://dx.doi.org/10.24200/sci.2017.4604; Bazzucchi, F., Restuccia, L., Ferro, G.A., Considerations over the Italian road bridge infrastructure safety after the polcevera viaduct collapse: Past errors and future perspectives (2018) Frattura Integr. 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Facil, 30 (2), p. 04015005. , https://doi.org/10.1061/(ASCE)CF.1943-5509.0000731; Eastman, C., Eastman, C.M., Teicholz, P., Sacks, R., (2011) BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, , John Wiley & Sons, New Jersey, USA; Ehlen, M.A., (2003) BridgeLCC 2.0 Users-Manual, , US Department of Commerce, National Institute of Standards and Technology, Maryland, USA; Elbehairy, H., Hegazy, T., Soudki, K., Integrated multiple-element bridge management system (2009) J. Bridge Eng, 14 (3), pp. 179-187. , https://doi.org/10.1061/(ASCE)1084-0702(2009)14:3(179); Farran, M., Zayed, T., Fitness-oriented multi-objective optimisation for infrastructures rehabilitations (2015) Struct. Infrastruct. Eng, 11 (6), pp. 761-775. , http://dx.doi.org/10.1080/15732479.2014.905964; Frangopol, D.M., Liu, M., Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost (2007) Struct. 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J, 24 (5), pp. 669-681. , https://doi.org/10.12989/sss.2019.24.5.669; Kyle, B.R., Vanier, D.J., Kosovac, B., Froese, T.M., Lounis, Z., Visualizer: An interactive, graphical, decision-support tool for service life prediction for asset managers (2002) Proceedings of the 9th International Conference on Durability of Building Materials and Components, , Brisbane, Australia, March; Maier, F., Brinckerhoff, P., (2012) Bridge information modeling: Opportunities, limitations, and spanning the chasm with current tools, , Report No. CI1529, Autodesk University, USA; Marzouk, M., Hisham, M., Bridge information modeling in sustainable bridge management (2011) Proceedings of the International Conference on Sustainable Design and Construction, , https://doi.org/10.1061/41204(426)57, Missouri, USA, March; Marzouk, M.M., Hisham, M., Al-Gahtani, K., Applications of bridge information modeling in bridges life cycle (2014) Smart Struct. Syst., Int. J, 13 (3), pp. 407-418. , https://doi.org/10.12989/sss.2014.13.3.407; Mawlana, M., Vahdatikhaki, F., Doriani, A., Hammad, A., Integrating 4D modeling and discrete event simulation for phasing evaluation of elevated urban highway reconstruction projects (2015) Autom. Constr, 60, pp. 25-38. , https://doi.org/10.1016/j.autcon.2015.09.005; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) J. Bridge Eng, 21 (4), p. 04015076. , https://doi.org/10.1061/(ASCE)BE.1943-5592.0000850; (2016) NBI Rating Guideline, , https://www.michigan.gov, MDOT Michigan, USA; Morcous, G., Lounis, Z., Maintenance optimization of infrastructure networks using genetic algorithms (2005) Autom. Constr, 14 (1), pp. 129-142. , https://doi.org/10.1016/j.autcon.2004.08.014; O’Keeffe, A., The state of the art of bridge information modelling from conceptual design through to operation (2014) Int. J. 3D Inf. 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Eng, 33 (11), pp. 926-942. , https://doi.org/10.1111/mice.12378; Zambon, I., Vidovic, A., Strauss, A., Matos, J., Friedl, N., Prediction of the remaining service life of existing concrete bridges in infrastructural networks based on carbonation and chloride ingress (2018) Smart Struct. Syst., Int. J, 21 (3), pp. 305-320. , http://dx.doi.org/10.12989/sss.2018.21.3.305; Zhu, J., Liu, B., Performance life cost-based maintenance strategy optimization for reinforced concrete girder bridges (2011) J. Bridge Eng, 18 (2), pp. 172-178. , https://doi.org/10.1061/(ASCE)BE.1943-5592.0000344","Zahraie, B.; School of Civil Engineering, Iran; email: bzahraie@ut.ac.ir",,,"Techno-Press",,,,,17381584,,,,"English","Smart Struct. Syst.",Article,"Final","",Scopus,2-s2.0-85098057627
"Vilventhan A., Rajadurai R.","55358249800;57204707245;","4D Bridge Information Modelling for management of bridge projects: a case study from India",2020,"Built Environment Project and Asset Management","10","3",,"423","435",,4,"10.1108/BEPAM-05-2019-0045","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076537231&doi=10.1108%2fBEPAM-05-2019-0045&partnerID=40&md5=cbf9f16e811202c8f6ed018a32fd5188","Department of Civil Engineering, National Institute of Technology WarangalTelangana, India","Vilventhan, A., Department of Civil Engineering, National Institute of Technology WarangalTelangana, India; Rajadurai, R., Department of Civil Engineering, National Institute of Technology WarangalTelangana, India","Purpose: The rapid development of the construction industry requires effective ways to monitor and control the project, and the use of 4D BIM is found to be very efficient. The purpose of this paper is to consider development, application and evaluation of 4D Bridge Information Modelling (BrIM) models for an ongoing bridge project. Design/methodology/approach: An ethnographic action-based case study research methodology is adopted in this study. An ongoing bridge construction project in India is chosen and the 4D BrIM application is evaluated both quantitatively and qualitatively using planned percentage complete (PPC) measurements and semi-structured interviews, respectively. Findings: The evaluation of the case study shows an increase in PPC values from 26.5 to 56.4 per cent after implementation of 4D BrIM in the project. The application of 4D BrIM in the construction phase benefits the project team in material delivery planning, project monitoring and control, construction schedule improvement, documentation and coordination. Practical implications: The developed models are practically applied to the ongoing project and the positive benefits are observed. It is shown that 4D BrIM has the potential to improve the construction of bridge projects. Originality/value: Studies have contributed towards the development and implementation of 3D BrIM models for bridge projects. Limited efforts have been taken to analyse how 4D BrIM models help in the overall management of bridge projects. This study adds value to the existing literature through development, implementation and systematic qualitative and quantitative evaluation of 4D BrIM models. © 2019, Emerald Publishing Limited.","4D modelling; BIM; Bridge Information Modelling; Bridge management; Case study; Project monitoring and control",,,,,,"Science and Engineering Research Board, SERB: ECR/2017/000002","The authors acknowledge the financial grant received from the Science and Engineering Research Board, India, for executing this project (File No. ECR/2017/000002).","Unanticipated delays and negligence in consideration of surrounding environment during the planning phase create inconvenience towards the public and its surrounding environment, thereby reducing the societal value of the infrastructure being built. The application of the 4D BrIM enables identification of potential key issues hampering the flow of work prior to the commencement of construction, reduced delays and chances of such unanticipated encounters during the course of construction. The collaboration platform developed through 4D BrIM facilitates sharing of individual ideas towards the improvements of projects performance. This develops a sense of involvement between project stakeholders in achieving the collective goals of the project. The ability of the 4D BrIM to visualise and monitor the entire structure horizontally adds value to the practitioners in visually coordinating and disseminating project information to their stakeholders. Efforts concerning BrIM adoption through academic and industry cases are identified in both developed and developing countries across the globe. However, the adoption rate of BrIM in India is feeble in case of industry cases and academic research on BrIM adoption is negligible. In case of India, industrial applications of BrIM are identified only in pre-construction phases, involving clash detection, quantity estimation and 3D visualisation. This paper presented a case study where 4D BrIM models were developed and applied to an ongoing bridge project, and their applicability in the construction phase was evaluated. According to the implementation, it was shown that 4D BrIM models has the potential to improve the schedule and effectively improve the progress of construction. Through the application of these technologies, it was found that there were positive effects in the progress of the project. PPC standards are adopted to measure the improvement of the project progress and PPC values are measured before and after application of 4D BrIM. An increase in the values of PPC from 26.5 to 56.39 per cent was measured before and after the application of 4D BrIM, respectively. Furthermore, a semi-structured interview was conducted to assess the applicability and benefits of 4D BrIM. All the stakeholders who participated in this research and evaluated the 4D BrIM models agreed to the fact that 4D BrIM models were very helpful to improve communication and coordination, optimise material delivery schedule, enhance progress monitoring and control, improve construction schedule and enable better documentation. The considered study has some limitations. The 4D BrIM models were applied to a single case project and the future work will focus on the application of the 4D BrIM models to many such bridge construction projects to quantitatively assess the benefits of the 4D applications. Future studies will also include the integration of 4D BrIM with Lean Construction tools for assessing the improvements in productivity. The authors acknowledge the financial grant received from the Science and Engineering Research Board, India, for executing this project (File No. ECR/2017/000002). Figure 1 Research methodology Figure 2 Developed 3D model of the bridge Figure 3 4D Simulation Figure 4 Schedule logical error identification Figure 5 Comparison of PPC values before and after 4D BrIM Plate 1 Case study of ongoing bridge project Table I Case study details Content Description Project title Project Vandalur Road Over Bridge Location Vandalur, Chennai, Tamil Nadu, India Estimated budget 55 crores Estimated duration 2 years Purpose To reduce traffic congestion","Abanda, F.H., Vidalakis, C., Oti, A.H., Tah, J.H.M., A critical analysis of building information modelling systems used in construction projects (2015) Advances in Engineering Software, 90, pp. 183-201; Al-shalabi, F.A., Turkan, Y., Laflamme, S., BrIM implementation for documentation of bridge condition for inspection (2015) 5th International/11th Construction Specialty Conference, University of British Columbia, Canadian Society for Civil Engineering, , Vancouver: p. 262; Aziz, N.D., Nawawi, A.H., Ariff, N.R.M., Building information modelling (BIM) in facilities management: opportunities to be considered by facility managers (2016) Procedia-Social and Behavioral Sciences, 234, pp. 353-362; Beary, T.M., Abdelhamid, T.S., Production planning process in residential construction using Lean Construction and Six Sigma principles (2005) Construction Research Congress 2005: Broadening Perspectives in San Diego, California, pp. 1-10. , Tommelein, I.D. (Ed.), ASCE; Bradley, A., Li, H., Lark, R., Dunn, S., BIM for infrastructure: an overall review and constructor perspective (2016) Automation in Construction, 71, pp. 139-152; Chen, L., Luo, H., A BIM-based construction quality management model and its applications (2014) Automation in Construction, 46, pp. 64-73; Cheng, J.C.P., Lu, Q., Deng, Y., Analytical review and evaluation of civil information modeling (2016) Automation in Construction, 67, pp. 31-47; Chiu, C.T., Hsu, T.H., Wang, M.T., Chiu, H.Y., Simulation for steel bridge erection by using BIM tools (2011) 28th International Symposium on Automation and Robotics in Construction, ISARC 2011 in Seoul, pp. 560-563; Chong, H.Y., Lopez, R., Wang, J., Wang, X., Zhao, Z., Comparative analysis on the adoption and use of BIM in road infrastructure projects (2016) Journal of Management in Engineering, 32 (6), p. 05016021; Fanning, B., Clevenger, C.M., Ozbek, M.E., Mahmoud, H., Implementing BIM on infrastructure: comparison of two bridge construction projects (2014) Practice Periodical on Structural Design Construction, 20 (4), p. 04014044; Gao, S., Low, S.P., The last planner system in China’s construction industry – a SWOT analysis on implementation (2014) International Journal of Project Management, 32 (7), pp. 1260-1272; Hallberg, D., Tarandi, V., On the use of open BIM and 4D visualisation in a predictive life cycle management system for construction works (2011) Journal of Information Technology in Construction, 16, pp. 445-466; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., An information modeling framework for bridge monitoring (2017) Advances in Engineering Software, 114, pp. 11-31; Ji, Y., Borrmann, A., Beetz, J., Obergrießer, M., Exchange of parametric bridge models using a neutral data format (2013) Journal of Computing in Civil Engineering, 27 (6), pp. 593-606; Kamardeen, I., 8D BIM modelling tool for accident prevention through design (2010) 26th Annual Conference-ARCOM in Leeds, UK, pp. 281-289. , Egbu, C.O. and Lou, E.C.,(Eds), Association of ResearchersConstruction Management, Reading; Kang, L., Pyeon, J., Moon, H., Kim, C., Kang, M., Development of improved 4D CAD system for horizontal works in civil engineering projects (2013) Journal of Computing in Civil Engineering, 27 (3), pp. 212-230; Kang, L.S., Kim, H.S., Moon, H.S., Kim, S.K., Managing construction schedule by telepresence: integration of site video feed with an active nD CAD simulation (2016) Automation in Construction, 68, pp. 32-43; Kim, C., Kim, H., Park, T., Kim, M.K., Applicability of 4D CAD in civil engineering construction: case study of a cable-stayed bridge project (2011) Journal of Computing in Civil Engineering, 25 (1), pp. 98-107; Lee, K.M., Lee, Y.B., Shim, C.S., Park, K.L., Bridge information models for construction of a concrete box-girder bridge (2012) Structure and Infrastructure Engineering, 8 (7), pp. 687-703; Liu, M., Ballard, G., Ibbs, W., Work flow variation and labor productivity: case study (2011) Journal of Management in Engineering, 27 (4), pp. 236-242; Liu, W., Guo, H., Li, H., Li, Y., Using BIM to improve the design and construction of bridge projects: a case study of a long-span steel-box arch bridge project (2014) International Journal of Advanced Robotic Systems, 11 (8), pp. 1-11; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) Journal of Bridge Engineering, 21 (4), p. 04015076; Mahalingam, A., Yadav, A.K., Varaprasad, J., Investigating the role of lean practices in enabling BIM adoption: evidence from two Indian cases (2015) Journal of Construction Engineering and Management, 141 (7), p. 05015006; Marzouk, M., Hisham, M., Applications of building information modeling in cost estimation of infrastructure bridges (2012) International Journal of 3-D Information Modeling, 1 (2), pp. 17-29; Marzouk, M., Hisham, M., Implementing earned value management using bridge information modeling (2014) KSCE Journal of Civil Engineering, 18 (5), pp. 1302-1313; Marzouk, M., Hisham, M., Ismail, S., Youssef, M., Seif, O., On the use of building information modelling in infrastructure bridges (2010) 27th International Conference-Applications of IT in the AEC Industry in Cairo, Egypt 2010, CIB W78, pp. 1-10; Moon, H., Dawood, N., Kang, L., Development of workspace conflict visualization system using 4D object of work schedule (2014) Advanced Engineering Informatics, 28 (1), pp. 50-65; Olde Scholtenhuis, L.L., Hartmann, T., Dorée, A.G., Testing the value of 4D visualizations for enhancing mindfulness in utility reconstruction works (2016) Journal of Construction Engineering and Management, 142 (7), p. 04016015; Shim, C.S., Lee, K.M., Kang, L.S., Hwang, J., Kim, Y., Three-dimensional information model-based bridge engineering in Korea (2012) Structural Engineering International, 22 (1), pp. 8-13; Smith, P., BIM & the 5D project cost manager (2014) Procedia – Social and Behavioral Sciences, 119, pp. 475-484; Xiao, R., Yu, L., Sun, B., Zhao, X., Tang, P., Method of bridge structural analysis based on bridge information modeling (2017) Computing in Civil Engineering in Seattle, pp. 92-100. , Lin, K.-Y., El-Gohary, N. and Tang, P., and,(Eds), ASCE, Washington, DC; Xu, Y., Turkan, Y., Bridge inspection using bridge information modeling (BrIM) and unmanned aerial system (UAS) (2019) Advances in Informatics and Computing in Civil and Construction Engineering, pp. 617-624. , Mutis, I. and Hartmann, T. and,(Eds), Springer, Cham; Yin, R.K., (1994) Case Study Research Design and Methods, , 2nd ed., Sage Publications, Thousand Oaks, CA; Zou, Y., Kiviniemi, A., Jones, S.W., Developing a tailored RBS linking to BIM for risk management of bridge projects (2016) Engineering, Construction and Architectural Management, 23 (6), pp. 727-750","Vilventhan, A.; Department of Civil Engineering, India; email: aneethavils@gmail.com",,,"Emerald Group Holdings Ltd.",,,,,2044124X,,,,"English","Built Environ. Proj. Asset Manage.",Article,"Final","",Scopus,2-s2.0-85076537231
"Zhao Y.-P., Wu H., Vela P.A.","36462199400;57209681746;8250110600;","Top-Down Partitioning of Reinforced Concrete Bridge Components",2019,"Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",,,,"275","283",,4,"10.1061/9780784482445.035","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068775047&doi=10.1061%2f9780784482445.035&partnerID=40&md5=920456f0d6e7ebfd326d79ff249da167","IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States; National Engineering Laboratory for Robotic Perception and Control, School of Electrical and Information Engineering, Hunan Univ.410082, China","Zhao, Y.-P., IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States; Wu, H., National Engineering Laboratory for Robotic Perception and Control, School of Electrical and Information Engineering, Hunan Univ.410082, China; Vela, P.A., IVALab, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA  30332-0250, United States","Raw point clouds of build structures do not provide semantic nor component level information. Automatic bridge information model generation from point cloud data would remedy this issue. This paper describes, applies, and evaluates a strategy for top-down partitioning of reinforced concrete bridges into structurally distinct component regions for girder, box girder, and slab bridges. The first phase is a user-guided denoising and coordinate frame specification process. The second phase utilizes the reference frame and geometric heuristics to identify the individual spans and whether the bridge contains AASHTO girders or not. It identifies cutting surfaces to apply for partitioning the bridge. The third phase identifies the substructure, superstructure, and deck components. This process either merges partitioned regions or further partitions regions to isolate bridge components with different functions. Isolated components include the girders/boxes/slabs, the piers, the abutments, the diaphragms, the road, and the parapets. The final coarse bridge model has a level of detail from 100 to 200. Application to four bridges demonstrates the low processing time and high partitioning accuracy, and provides visualizations of the IFC bridge model output. © 2019 American Society of Civil Engineers.",,"Beams and girders; Box girder bridges; Bridge components; Concrete bridges; Railroad bridges; Semantics; Smart city; Sustainable development; Component levels; Information Modeling; Level of detail; Point cloud data; Processing time; Reference frame; Slab bridges; Specification process; Reinforced concrete",,,,,,,,"Arias, P., Riveiro, B., Armesto, J., Solla, M., Terrestrial laser scanning and non parametric methods in masonry arches inspection (2010) International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38. , Commission V Symposium; Barazzetti, L., Banfi, F., Brumana, R., Gusmeroli, G., Oreni, D., Previtali, M., Roncoroni, F., Schiantarelli, G., BIM from laser clouds and finite element analysis: Combining structural analysis and geometric complexity (2015) Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, pp. 345-350; Bosché, F., Ahmed, M., Turkan, Y., Haas, C.T., Haas, R., The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components (2015) Automation in Construction, 49, pp. 201-213; Dimitrov, A., Golparvar-Fard, M., Segmentation of building point cloud models including detailed architectural/structural features and MEP systems (2015) Automation in Construction, 51, pp. 32-45; Lu, R., Brilakis, I., Recursive segmentation for as-is bridge information modelling (2017) Joint Conference on Computing in Construction, , Heraklion, Greece; Lu, R., Brilakis, I., Middleton, C.R., Detection of structural components in point clouds of existing RC bridges (2018) Computer-Aided Civil and Infrastructure Engineering; Truong-Hong, L., Laefer, D., Application of terrestrial laser scanner in bridge inspection: Review and an opportunity (2014) IABSE Symposium: Engineering for Progress, Nature, and People, , Madrid, Spain; Zhang, G., Vela, P.A., Brilakis, I., Detecting, fitting, and classifying surface primitives for infrastructure point cloud data (2013) Int. Workshop on Computing in Civil Engineering; Zhang, G., Vela, P.A., Karasev, P., Brilakis, I., A sparsity-inducing optimization-based algorithm for planar patches extraction from noisy point-cloud data (2015) Computer-Aided Civil and Infrastructure Engineering, 30 (2), pp. 85-102; Zhu, D., Dong, X., Wang, Y., Substructure model updating through iterative minimization of modal dynamic residual (2014) Proceedings of SPIE, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security, , San Diego, California, USA",,"Cho Y.K.Leite F.Behzadan A.Wang C.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019","17 June 2019 through 19 June 2019",,148902,,9780784482445,,,"English","Comput. Civ. Eng.: Smart Cities, Sustain., Resil. - Sel. Pap. ASCE Int. Conf. Comput. Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85068775047
"Adibfar A., Costin A.M.","57202945239;55200193500;","Evaluation of IFC for the Augmentation of Intelligent Transportation Systems (ITS) into Bridge Information Models (BrIM)",2019,"Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",,,,"177","184",,3,"10.1061/9780784482421.023","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068748129&doi=10.1061%2f9780784482421.023&partnerID=40&md5=8c0cd48042b7f7acdbd08ee4c44bfabd","M. E. Rinker Sr. School of Construction Management, Univ. of Florida, PO Box 115703, Gainesville, FL, United States","Adibfar, A., M. E. Rinker Sr. School of Construction Management, Univ. of Florida, PO Box 115703, Gainesville, FL, United States; Costin, A.M., M. E. Rinker Sr. School of Construction Management, Univ. of Florida, PO Box 115703, Gainesville, FL, United States","Intelligent transportation systems (ITS) produce valuable data by using various sensors incorporated with transportation infrastructure. The use of ITS has transformed infrastructure management by making it easier and more efficient. Quality and comprehensiveness of the ITS data have direct impact on the effectiveness of planning, design, and maintenance activities. Previous research suggested that the fusion of ITS data with bridge information modeling (BrIM) can provide a reliable visual database that can satisfy design and maintenance needs while enhances the integration and management of databases. However, one major challenge identified is the lack of interoperability between the various software and systems required for the fusion. The industry foundation classes (IFC) is an international data exchange standard for building information modeling (BIM) that has been developed for the exchange of data within the building industry. Recently, IFC has been developed to include the required elements for modeling transportation infrastructure including bridges, highways, and tunnels. This research investigates the use of IFC to include the data that have been produced through ITS and are needed for the full exchange of information between transportation stakeholders. The scope of this paper is to provide a high-level evaluation of IFC to determine the feasibility and applicability of the augmentation of BrIM and ITS fusion data. The result of this research will help in the improvement of communication and collaboration between designers and stakeholders that can eventually help the management of transportation infrastructure. © 2019 American Society of Civil Engineers.","BIM; Bridge information modeling (BrIM); Industry Foundation Class (IFC); Intelligent Transportation Systems (ITS); management and maintenance","Architectural design; Construction industry; Electronic data interchange; Highway planning; Information management; Information theory; Intelligent systems; Intelligent vehicle highway systems; Interoperability; Maintenance; Visualization; Building Information Model - BIM; Communication and collaborations; Exchange of information; Industry Foundation Classes - IFC; Information Modeling; Infrastructure managements; Intelligent transportation systems; Transportation infrastructures; Bridges",,,,,,,,"Adibfar, A., Costin, A., Next generation of transportation infrastructure management: Fusion of Intelligent transportation systems (ITS) and Bridge information modeling (BrIM) (2019) Advances in Information and Computing in Civil and Construction Engineering, pp. 43-50; (2016) Ifc Sensor Type Enum, , http://www.buildingsmartech.org/ifc/IFC4/Add2/html/schema/ifcbuildingcontrolsdomain/lexical/ifcsensortypeenum.htm, (Nov. 01, 2018); Costin, A., (2016) A New Methodology for Interoperability of Heterogeneous Bridge Information Models, , http://hdl.handle.net/1853/55012, PhD Diss., CEE, Georgia Institute of Technology, Atlanta, GA; Costin, A., Adibfar, A., Hu, H., Chen, S., Building information modeling for transportation infrastructure - literature review, applications, challenges, and recommendations (2018) Automation in Construction, 94, pp. 257-281; Costin, A., Eastman, C., The need for interoperability to enable seamless information exchanges in smart and sustainable urban systems (2019) Journal of Computing in Civil Engineering, , [In Press]; Costin, A., Teizer, J., Fusing passive RFID and BIM for increased accuracy in Indoor localization (2015) Visualization in Engineering, 3 (1), p. 17; Costin, A., Teizer, J., Schoner, B., RFID and BIM-enabled worker location tracking support real-time building protocol control and data visualization on a large hospital project (2015) J. Information Technology in Construction (ITcon), 40, pp. 495-517; Gungor, O., Al-Qadi, I., Mann, J., Detect and charge: Machine learning based fully data-driven framework for computing overweight vehicle fee for bridges (2018) Automation in Construction, 96, pp. 200-210; Hosseini, M., Banihashemi, S., Zaeri, F., Adibfar, A., Advanced ICT methodologies (AIM) in the construction industry (2017) Encyclopedia of Information Science and Technology, pp. 539-550. , Fourth Edition - Chapter 47, IGI Global; Lebegue, E., IFC bridge & IFC for roads (2013) Building Smart Infrastructure Room, , Oct. 8th, 2013, Munich, Germany; Lee, Y.C., Eastman, C., Lee, J.K., Validation for ensuring the interoperability of data exchange of a building information model (2015) Automation in Construction, 58, pp. 176-195; Lee, Y.C., Ghannad, P., Lee, J.K., Reusability and its limitations of the module of existing BIM data exchange requirements for new MVDs (2019) Advances in Informatics and Computing in Civil and Construction Engineering, pp. 103-110; Theiler, M., Smarsly, K., IFC monitor- an IFC schema extension for modeling structural health monitoring systems (2018) Advanced Engineering Informatics, pp. 54-65; Venugopal, M., Eastman, C., Sacks, R., Teizer, J., Semantics of model views for information exchange using the industry foundation class schema (2012) Advanced Engineering Informatics, 26, pp. 411-428",,"Cho Y.K.Leite F.Behzadan A.Wang C.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","ASCE International Conference on Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation, i3CE 2019","17 June 2019 through 19 June 2019",,148901,,9780784482421,,,"English","Comput. Civ. Eng.: Vis., Inf. Model., Simul. - Sel. Pap. ASCE Int. Conf. Comput. Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85068748129
"Xiao R., Lian Y., Sun B., Zhao X., Liu Z., Tang P.","55943264200;57191973966;54948457000;57771011000;57194708326;24170157800;","Method of bridge structural analysis based on bridge information modeling",2017,"Congress on Computing in Civil Engineering, Proceedings",,,,"92","100",,3,"10.1061/9780784480823.012","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021699076&doi=10.1061%2f9780784480823.012&partnerID=40&md5=8e3d7717f2c5db7fdc5579abb26e622c","College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, ST  200092, China; Sichuan Development and Reform Commission, 156 East Binjiang Rd., Chengdu, ST  610021, China; Shanghai Municipal Engineering Design Institute (Group) Ltd., 901 North Zhongshan Rd., Shanghai, ST  200092, China; School of Sustainable Engineering and the Built Environment, Arizona State Univ., P.O. Box 873005, Tempe, AZ  85287-3005, United States","Xiao, R., College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, ST  200092, China; Lian, Y., Sichuan Development and Reform Commission, 156 East Binjiang Rd., Chengdu, ST  610021, China; Sun, B., College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, ST  200092, China; Zhao, X., College of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, ST  200092, China; Liu, Z., Shanghai Municipal Engineering Design Institute (Group) Ltd., 901 North Zhongshan Rd., Shanghai, ST  200092, China; Tang, P., School of Sustainable Engineering and the Built Environment, Arizona State Univ., P.O. Box 873005, Tempe, AZ  85287-3005, United States","Aiming at releasing the potential of BrIM model for improving the efficiency of bridge design and structural analysis, this paper analyzed the combined parametric method of BrIM models and built up structure properties for FEM, thereby established a three-class modeling frame and a new method of bridge analysis based on BrIM. To overcome the gap between BrIM and FEM in bridge structural analysis, the information of bridge structures and special analysis characteristics are set up to establish the reservoir of bridge structure analysis. The mesh controls of the bridge structural information is standardized and preset. The processing generates the corresponding switch file which file type is compatible with a variety of FEM analysis software tools. The seamless transition from BrIM to FEM greatly accelerated the design and analysis of bridges. The smooth parameter flow from the BrIM to FEM is also formed for quick information modification and mechanical analysis of bridge structures. © 2017 American Society of Civil Engineers.",,"Structural analysis; Bridge structural analysis; Bridge structure analysis; Built-up structures; Design and analysis; Information Modeling; Mechanical analysis; Seamless transition; Structural information; Bridges",,,,,,,,"Barazzetti, L., Banfi, F., Cloud-to-BIM-to-FEM: Structural simulation with accurate historic BIM from laser scans (2015) Simulation Modelling Practice and Theory, 57, pp. 71-87; Lee, S.H., Park, S.I., Open BIM-based information modeling of railway bridges and its application concept (2014) Computing in Civil and Building Engineering (2014), pp. 504-511; Moon, H.S., Kim, H.S., Kang, L.S., Development strategies and feasibility evaluation of maintenance operation system for railway bridge based on UbiquitousBIM technology (2012) JOURNAL of the Korean Society for Railway, 15 (5), pp. 459-466; Marzouk, M., Hisham, M., Implementing earned value management using bridge information modeling (2014) KSCE JOURNAL of CIVIL ENGINEERING, 18 (5), pp. 1302-1313; Monedero, J., Parametric design: A review and some experiences (2000) AUTOMATION in CONSTRUCTION, 9 (4), pp. 369-377; Mun, D., Han, S., A set of standard modeling commands for the history-based parametric approach (2003) Computer-Aided Design, 35 (13), pp. 1171-1179; Shim, C.S., Yun, N.R., Application of 3D bridge information modeling to design and construction of bridges (2011) Procedia Engineering, 14, pp. 95-99; Shin, H.M., Lee, H.M., Analysis and design of reinforced concrete bridge column based on BIM (2011) Procedia Engineering, 14, pp. 2160-2163; Chun, K.S., Park, W.T., BIM system development for conceptual design and pre-feasibility study of cable-stayed bridge (2015) Journal of Korea Academia-Industrial Cooperation Society, 16 (10), pp. 7204-7210",,"Lin K.-Y.Lin K.-Y.El-Gohary N.El-Gohary N.Tang P.Tang P.","Computing and Information Technology Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017","25 June 2017 through 27 June 2017",,128224,,9780784480823; 9780784480847; 9780784480823,CCENE,,"English","Comput Civ Eng (New York)",Conference Paper,"Final","",Scopus,2-s2.0-85021699076
"Dayan V., Chileshe N., Hassanli R.","57780760900;12808688300;56743319900;","A Scoping Review of Information-Modeling Development in Bridge Management Systems",2022,"Journal of Construction Engineering and Management","148","9","03122006","","",,2,"10.1061/(ASCE)CO.1943-7862.0002340","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133489568&doi=10.1061%2f%28ASCE%29CO.1943-7862.0002340&partnerID=40&md5=aae50b5d9cbb9713dd4d228c4d275195","UniSA STEM, Univ. of South Australia, City East Campus, 108 North Terrace, Adelaide, SA  5001, Australia; Construction and Project Management, UniSA STEM, Univ. of South Australia, Mawson Lakes Campus, Mawson Lakes Blvd.,Mawson Lakes, Mawson Lakes, SA  5095, Australia","Dayan, V., UniSA STEM, Univ. of South Australia, City East Campus, 108 North Terrace, Adelaide, SA  5001, Australia; Chileshe, N., Construction and Project Management, UniSA STEM, Univ. of South Australia, Mawson Lakes Campus, Mawson Lakes Blvd.,Mawson Lakes, Mawson Lakes, SA  5095, Australia; Hassanli, R., Construction and Project Management, UniSA STEM, Univ. of South Australia, Mawson Lakes Campus, Mawson Lakes Blvd.,Mawson Lakes, Mawson Lakes, SA  5095, Australia","Transportation assets represent a critical element of public infrastructures, and bridge networks are an essential part of these assets. A system that includes several tools for managing the bridges is called a bridge management system (BMS). BMSs are built up to provide long-term health verification for bridges and assure safe serviceability. With the advent of powerful computers in the mid-1980s, BMSs became more electronic and, consequently, capable of processing more data than a paper system. Building information modeling (BIM) is an emerging technology with commanding visualization and informatization ability, making it a perfect tool for generating modern management systems. Bridge information modeling (BrIM) is a developed concept extracted from BIM that concentrates on bridges. In this paper, the use of BrIM in the development of bridge management systems during the recent decade is verified through a scoping review of the state-of-the-art literature. The broad nature of the scoping review provides chances for rapidly reviewing evidence in emerging topics and analyzing knowledge gaps; it is used to capture the cutting-edge concept of information modeling in the body of literature. In this study, search resulted in a final refined list of 78 journal articles published in the recent decade, categorized into six different topic areas. This paper aims to verify different aspects of using information modeling in bridge management and identify the knowledge gaps, limitations, and emergent works for industrial and academic investigators. Descriptive and content analyses are presented to clarify the researchers’ focal points in this review, which shows trending keywords, leading journals, and articles’ frequency in each field. This study indicates that the concentration of BrIM researchers is on new inspection and test methods and maintenance optimization with a particular focus on concrete structures. © 2022 American Society of Civil Engineers.","Bridge information modeling (BrIM); Bridge inspection; Bridge management system (BMS); Building information modeling (BIM); Computer vision approaches; Cost management; Image processing; Maintenance optimization; Scoping review; Structural assessment","Architectural design; Data handling; Information management; Testing; Bridge information modeling; Bridge inspection; Bridge management system; Building information modeling; Building Information Modelling; Computer vision approach; Cost management; Images processing; Information Modeling; Maintenance optimization; Scoping review; Structural assessments; Computer vision",,,,,"University of South Australia, UniSA","The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Australian government’s financial support through an Australian Government Research Training Program domestic (RTPd) Fee Offset Scholarship for Ph.D. studies and support from the University of South Australia is acknowledged.",,"Abé, M., Shimamura, M., Fujino, Y., Risk management and monitoring of Japanese railway bridges (2014) Proc. Inst. Civ. Eng. Forensic Eng., 167 (2), pp. 88-98. , https://doi.org/10.1680/feng.13.00022; Ahmed, H., La, H.M., Tran, K., Rebar detection and localization for bridge deck inspection and evaluation using deep residual networks (2020) Autom. Constr., 120 (Dec), p. 103393. , https://doi.org/10.1016/j.autcon.2020.103393; Akgul, F., Bridge management in Turkey: A BMS design with customised functionalities (2016) Struct. Infrastruct. Eng., 12 (5), pp. 647-666. , https://doi.org/10.1080/15732479.2015.1035284; Akgul, F., Inspection and evaluation of a network of concrete bridges based on multiple NDT techniques (2020) Struct. Infrastruct. Eng., 17 (8), pp. 1076-1095. , https://doi.org/10.1080/15732479.2020.1790016; Almomani, H., Almutairi, O.N., Life-cycle maintenance management strategies for bridges in Kuwait (2020) J. Environ. Treat. Tech., 8 (4), pp. 1556-1562. , https://doi.org/10.47277/JETT/8(4)1562; Alsharqawi, M., Zayed, T., Abu Dabous, S., Integrated condition rating and forecasting method for bridge decks using visual inspection and ground penetrating radar (2018) Autom. Constr., 89 (May), pp. 135-145. , https://doi.org/10.1016/j.autcon.2018.01.016; Alsharqawi, M., Zayed, T., Abu Dabous, S., Integrated condition-based rating model for sustainable bridge management (2020) J. Perform. Constr. Facil., 34 (5), p. 4020091. , https://doi.org/10.1061/(ASCE)CF.1943-5509.0001490; (2005) Basis for design of structures—Assessment of existing structures, , ISO 13822:2001, MOD). AS ISO 13822. Sydney, NSW: Standards Australia; Assaad, R., El-Adaway, I.H., Bridge infrastructure asset management system: Comparative computational machine learning approach for evaluating and predicting deck deterioration conditions (2020) J. Infrastruct. Syst., 26 (3), p. 4020032. , https://doi.org/10.1061/(ASCE)IS.1943-555X.0000572; Banerji, P., Chikermane, S., Scott, R., Surre, F., Sun, T., Grattan, K.T.V., Longthorne, J., Structural monitoring for asset management of railway bridges (2014) Proc. Inst. Civ. Eng. Bridge Eng., 167 (3), pp. 157-169. , https://doi.org/10.1680/bren.13.00011; Bekic, D., Kerin, I., Michalis, P., McKeogh, E., Cahill, P., Pakrashi, V., Bridge SMS: Intelligent bridge maintenance and management system (2017) Proc., Joint Cost TU1402–Cost TU1406–IABSE WC1 Workshop: The Value of Structural Health Monitoring for the Reliable Bridge Management, pp. 953-978. , Zagreb, Croatia: Univ. of Zagreb; Bennetts, J., Vardanega, P.J., Taylor, C.A., Denton, S.R., Survey of the use of data in UK bridge asset management (2020) Proc. Inst. Civ. Eng. 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"de Freitas Bello V.S., Popescu C., Blanksvärd T., Täljsten B., Popescu C.","57338405600;56272949500;20336636900;8703323300;56272949500;","Bridge management systems: Overview and framework for smart management",2021,"IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs",,,,"1014","1022",,2,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119042894&partnerID=40&md5=75c4a853545c7db896e261b5018e91e0","Luleå University of Technology (LTU), Luleå, Sweden; SINTEF Narvik AS, Narvik, 8517, Norway","de Freitas Bello, V.S., Luleå University of Technology (LTU), Luleå, Sweden; Popescu, C., Luleå University of Technology (LTU), Luleå, Sweden, SINTEF Narvik AS, Narvik, 8517, Norway; Blanksvärd, T., Luleå University of Technology (LTU), Luleå, Sweden; Täljsten, B., Luleå University of Technology (LTU), Luleå, Sweden; Popescu, C., Luleå University of Technology (LTU), Luleå, Sweden, SINTEF Narvik AS, Narvik, 8517, Norway","Throughout the world, many medieval and historic bridges remain in operation. Deterioration and failures have increased in the already aging bridges due to consistent growth in traffic volume and axle loads. Therefore, the importance of Bridge Management Systems (BMS) to ensure safety of operation and maximize maintenance investments has also increased. Recent improvements in technology also contribute to the demand for optimized and more resource-efficient BMS. In this study, a literature review was performed to map current bridge management practices and systems in operation in the world. The outcomes identified Bridge Information Modelling (BrIM) and Digital Twins as novel approaches that enable efficient management of the whole lifecycle of a bridge. From these outcomes, a framework of an ideal BMS is proposed to achieve automated and smart management of bridges. © 2021 IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs. All rights reserved.","BMS; Bridge management systems; Bridges; BrIM; Review","Deterioration; Life cycle; Maintenance; Structural design; Axle loads; Bridge information modeling; Bridge management system; Historic bridges; Information Modeling; Maintenance investments; Resource-efficient; Traffic volumes; Volume loads; Bridges",,,,,"Energimyndigheten","This work was carried out within the strategic innovation program InfraSweden2030, a joint venture by Vinnova, Formas and The Swedish Energy Agency, the work is also funded by SBUF (construction industry's organisation for research and development in Sweden) and Skanska Sweden.",,"Hurt, M., Schrock, S., Chapter 1 - Introduction (2016) Highway Bridge Maintenance Planning and Scheduling, pp. 1-30; Khan, M. A., (2015) Accelerated Bridge Construction, pp. 53-102. , Boston: Butterworth-Heinemann; Powers, N., Frangopol, D. 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C., O'Reilly, M., Bevc, L., Znidaric, A., O'Brien, E., Jordan, R., Cost 345 - Procedures required for the assessment of highway structures - Final report European Co-operation in the Field of Scientific and Technical Research; Hallberg, D., Racutanu, G., Development of the Swedish bridge management system by introducing a LMS concept (2007) Materials and Structures, 40, pp. 627-639; Isailovic, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R., Döllner, J., Bridge damage: Detection, IFC-based semantic enrichment and visualization (2020) Automation in Construction, 112. , (103088); Marzouk, M. M., Hisham, M., Bridge information modelling in sustainable bridge management (2011) Proceedings of the 2011 International Conference on Sustainable Design and Construction - ICSDC 2011: Integrating Sustainability Practices in the Construction Industry, pp. 457-466; Dibernardo, S., Integrated modelling systems for bridge asset management - case study (2012) Proceedings of the 2012 Structures Congress, pp. 483-493; Wan, C., Zhou, Z., Li, S., Ding, Y., Xu, Z., Yang, Z., Xia, Y., Yin, F., Development of a bridge management system based on the building information modelling technology (2019) Sustainability, 11 (4583); Zhao, Z., Gao, Y., Hu, X., Zhou, Y., Zhao, L., Qin, G., Guo, J., Han, D., Integrating BIM and IoT for smart bridge management (2019) IOP Conference Series: Earth and Environmental Science, 371. , (022034); Zhu, J., Tan, Y., Wang, X., Wu, P., BIM/GIS integration for web GIS-based bridge management (2020) Annals of GIS, 27 (1), pp. 99-109; Boddupalli, C., Sadhu, A., Rezazadeh Azar, E., Pattyson, S., Improved visualization of infrastructure monitoring data using building information modelling (2019) Structure and Infrastructure Engineering, 15 (9), pp. 1247-1263; Riveiro, B., Jauregui, D. V., Arias, P., Armesto, J., Jiang, R., An innovative method for remote measurement of minimum vertical underclearance in routine bridge inspection (2012) Automation in Construction, 25, pp. 34-40; Huthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC bridge defect information into BIM models (2018) Journal of Computing in Civil Engineering, 32 (3), p. 04018013. , 1-04018013-14; Lu, R., Brilakis, I., Digital twinning of existing reinforced concrete bridges from labelled point clusters (2019) Automation in Construction, 105. , (102837); Borin, P., Cavazzini, F., Condition assessment of RC bridges - Integrating machine learning, photogrammetry and BIM (2019) International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, pp. 201-208. , XLII-2/W15; Morgenthal, G., Hallermann, N., Kersten, J., Taraben, J., Debus, P., Helmrich, M., Rodehorst, V., Framework for automated UAS-based structural condition assessment of bridges (2019) Automation in Construction, 97, pp. 77-95; Khajavi, S. H., Motlagh, N. H., Jaribion, A., Werner, L. C., Holmstrom, J., Digital twin: Vision, benefits, boundaries, and creation for buildings (2019) IEEE Access, 7, pp. 147406-147419; Zou, Y., Kiviniemi, A., Jones, S. W., Developing a tailored RBS linking to BIM for risk management of bridge projects (2016) Engineering, Construction and Architectural Management, 23 (6), pp. 727-750; Zou, Y., Kiviniemi, A., Jones, S. W., Walsh, J., Risk information management for bridges by integrating risk breakdown structure into 3D/4D BIM (2019) KSCE Journal of Civil Engineering, 23 (2), pp. 467-480","de Freitas Bello, V.S.; Luleå University of Technology (LTU)Sweden; email: vanessa.saback.de.freitas@ltu.se","Snijder H.H.De Pauw B.De Pauw B.van Alphen S.F.C.Mengeot P.","Allplan;et al.;Greisch;Infrabel;Royal HaskoningDHV;TUC RAIL","International Association for Bridge and Structural Engineering (IABSE)","IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs","22 September 2021 through 24 September 2021",,172892,,,,,"English","IABSE Congr., Ghent: Struct. Eng. Future Soc. Needs",Conference Paper,"Final","",Scopus,2-s2.0-85119042894
"Törmä S., Toivola P., Kiviniemi M., Puntila P., Lampi M., Mätäsniemi T.","6602149776;12782596400;6602426056;57215330840;55416083100;6504155486;","Ontology-based sharing of structural health monitoring data",2019,"20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report",,,,"2214","2221",,2,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074453225&partnerID=40&md5=f55afd0ddd1b66419b9819998cf10957","VisuaLynk, Espoo, Finland; Savcor Helsinki, Finland; VTT, Espoo, Finland; Trimble Solutions, Espoo, Finland; VTT, Tampere, Finland","Törmä, S., VisuaLynk, Espoo, Finland; Toivola, P., Savcor Helsinki, Finland; Kiviniemi, M., VTT, Espoo, Finland; Puntila, P., Trimble Solutions, Espoo, Finland; Lampi, M., Savcor Helsinki, Finland; Mätäsniemi, T., VTT, Tampere, Finland","A structural health monitoring system installed in a bridge produces a vast amount of sensor data that is analyzed and periodically reported to a bridge owner at an aggregate level. The data itself typically remains in the monitoring service of a service provider; it may be accessible to clients and third parties through a dedicated user interface and API. This paper presents an ontology to defining the monitoring model based on the Semantic Sensor Network Ontology by W3C. The goal is to enable an asset owner to utilize preferred tools to view and access monitoring data from different service providers, and in longer term, increase the utilization of monitoring data in facility management. The ultimate aim is to use BrIM as a digital twin of a bridge and to link external datasets to improve information management and maintenance over its lifecycle. © 20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report. All rights reserved.","Bridge information model; Facility management; Linked data; Monitoring; Ontology","Application programming interfaces (API); Information management; Life cycle; Linked data; Office buildings; Ontology; Semantics; Sensor networks; Structural health monitoring; User interfaces; Access monitoring; Different services; Facility management; Information Modeling; Monitoring models; Monitoring services; Service provider; Structural health monitoring systems; Monitoring",,,,,"City, University of London, City","This research belongs to a collaborative research project SmartBridgeFM (2017-2019), partially funded by Business Finland. Special thanks for City of Helsinki for providing the BrIMs of Crusell bridge.",,"Endsley, M.R., Toward a theory of situation awareness in dynamic systems (1995) Human Factors, 37 (1), pp. 85-104; W3C Data Activity, , https://www.w3.org/2013/data/, W3C; Dijkstra, E., On the role of scientific thought (1982) Selected Writings on Computing: A Personal Perspective, pp. 60-66. , NY, Springer; (2017) OPC Unified Architecture, , https://opcfoundation.org/ua/, OPC Foundation; Cyganiak, R., Wood, D., Lanthaler, M., (2014) RDF 1.1 Concepts and Abstract Syntax, W3C Recommendation, , https://www.w3.org/TR/rdf11-concepts/; (2012) OWL 2 Web Ontology LanguageDocument Overview, , https://www.w3.org/TR/owl-overview/, W3C Recommendation; Berners-Lee, T., (2006) Linked Data -Design Issues, W3C Note, , http://www.w3.org/DesignIssues/LinkedData.html; Linked Open Vocabularies, , https://lov.linkeddata.es/dataset/lov/; Törmä, S., Semantic linking of building information models (2013) IEEE Seventh International Conference on Semantic Computing, , Irvine, CA; Pauwels, P., Supporting decision-making in the building life-cycle using linked building data (2014) Buildings, 4 (3), pp. 549-579; Beetz, J., Van Leeuwen, J., De Vries, B., IFCOwl: A case of transforming EXPRESS schemas into ontologies (2009) AI EDAM, 23 (1), pp. 89-101; Pauwels, P., Terkaj, W., EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology (2016) Automation in Construction, 63, pp. 100-133; Hoang, N.V., Törmä, S., Implementation and experiments with an IFC-to-linked data converter (2015) 32nd International Conference of CIB W78; Bonduel, M., Oraskari, J., Pauwels, P., Vergauwen, M., Klein, R., The IFC to linked building data converter - Current status (2018) 6th Linked Data in Architecture and Construction Workshop, , London; Haller, A., Janowicz, K., Cox, S., Le Phuoc, D., Taylor, K., Lefrançois, M., Semantic Sensor Network Ontology, W3C Recommendation, , https://www.w3.org/TR/vocab-ssn/, W3C; Cox, S., (2018) Extensions to the Semantic Sensor Network Ontology, , https://www.w3.org/TR/vocab-ssn-ext/, W3C; Turunen, M., Pulkkinen, P., Toivola, P., Structural health monitoring of Crusell bridge (2016) 19th IABSE Congress, , Stockholm; Crusell Bridge Trimble, , https://www.tekla.com/references/crusellbridge","Kiviniemi, M.; VTTFinland; email: markku.kiviniemi@vtt.fi",,"Allplan (Gala);et al.;Hardesty and Hanover;Silman;Wiss, Janney, Elstner Associates, Inc.;WSP","International Association for Bridge and Structural Engineering (IABSE)","20th IABSE Congress, New York City 2019: The Evolving Metropolis","4 September 2019 through 6 September 2019",,152767,,9783857481659,,,"English","Congr. IABSE, New York City: Evol. Metropolis - Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85074453225
"Qin Y., Xiao R., Wang Y., Law K.H.","57013923900;55943264200;56002644400;55671078700;","A Bridge Information Modeling Framework for Model Interoperability",2019,"Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019",,,,"447","454",,2,"10.1061/9780784482421.057","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068739821&doi=10.1061%2f9780784482421.057&partnerID=40&md5=00919d71ede8c6ab60ddc8f7178aff0d","Dept. of Bridge Engineering, School of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, 200092, China; School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr. NW, Atlanta, GA  30332-0355, United States; Dept. of Civil and Environmental Engineering, Stanford Univ., 473 Via Ortega, Stanford, CA  94305-4020, United States","Qin, Y., Dept. of Bridge Engineering, School of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, 200092, China; Xiao, R., Dept. of Bridge Engineering, School of Civil Engineering, Tongji Univ., 1239 Siping Rd., Shanghai, 200092, China; Wang, Y., School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr. NW, Atlanta, GA  30332-0355, United States; Law, K.H., Dept. of Civil and Environmental Engineering, Stanford Univ., 473 Via Ortega, Stanford, CA  94305-4020, United States","Bridge information modeling (BrIM) techniques have been developed to integrate information from architecture, engineering, construction, and operation. The models developed by these different stakeholders, however, are oftentimes not interoperable. To address the challenge, this paper proposes a BrIM framework to ensure consistent data exchange. Designed as the central hub for data exchange, the Python program translates between the BrIM model and Mongo database, a NoSQL (Not Only SQL) database. The unifying Python framework is demonstrated with the BrIM model of a steel pedestrian bridge located in Atlanta, Georgia. In this case study, the OpenBrIM standard is employed to create the geometry model and the finite element model of the bridge structure with visualization. If change is made in either the OpenBrIM model or the Mongo database, the Python program can automatically synchronize the changes to the others. © 2019 American Society of Civil Engineers.",,"Database systems; Electronic data interchange; Footbridges; High level languages; Information theory; Visualization; Atlanta; Bridge structures; Geometry model; Georgia; Information Modeling; Information modeling frameworks; Model interoperability; Computer software",,,,,"China Scholarship Council, CSC: 201706260136","The authors would like to acknowledge Mr. Seongwoon Jeong for the many contributions and valuable discussions on this study. The first author is supported by Chinese Scholarship Council (#201706260136). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the sponsors.",,"Al-Shalabi, F.A., Turkan, Y., Laflamme, S., BrIM implementation for documentation of bridge condition for inspection (2015) Proceedings of the Canadian Society for Civil Engineering 5th International/11th Construction Specialty Conference, pp. 7-10. , University of British Columbia, Vancouver, Canada. June; Bartholomew, M., Blasen, B., Koc, A., (2015) Bridge Information Modeling (BrIM) Using Open Parametric Objects, FHWA-HIF-16-010, , Federal Highway Administration; Chen, S.S., Shirole, A.M., Integration of information and automation technologies in bridge engineering and management - Extending the state of the art (2006) Design of Structures, 2006 (1976), pp. 3-12; Costin, A., Adibfar, A., Hu, H.J., Chen, S.S., Building information modeling (BIM) for transportation infrastructure - literature review, applications, challenges, and recommendations (2018) Automation in Construction, 94, pp. 257-281; Jardim-Goncalves, R., Grilo, A., Building information modeling and interoperability (2010) Automation in Construction, 19 (4), p. 387; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., An information modeling framework for bridge monitoring (2017) Advances in Engineering Software, 114, pp. 11-31; Jeong, S., Zhang, Y.L., Lynch, J.P., Sohn, H., Law, K.H., A NoSQL-based data management infrastructure for bridge monitoring database (2015) Structural Health Monitoring 2015: System Reliability for Verification and Implementation, 1-2, pp. 1567-1574; (2007) National Building Information Modeling Standard, Version 1, Part 1: Overview, Principles, and Methodologies, p. 162. , National Institute of Building Sciences (NIBS) Facility Information Council (FIC), Washington, DC; Steel, J., Drogemuller, R., Toth, B., Model interoperability in building information modelling (2010) Software & Systems Modeling, 11 (1), pp. 99-109; Succar, B., Building information modelling framework: A research and delivery foundation for industry stakeholders (2009) Automation in Construction, 18 (3), pp. 357-375; Yalcinkaya, M., Singh, V., Patterns and trends in building information modeling (BIM) research: A latent semantic analysis (2015) Automation in Construction, 59, pp. 68-80",,"Cho Y.K.Leite F.Behzadan A.Wang C.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","ASCE International Conference on Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation, i3CE 2019","17 June 2019 through 19 June 2019",,148901,,9780784482421,,,"English","Comput. Civ. Eng.: Vis., Inf. Model., Simul. - Sel. Pap. ASCE Int. Conf. Comput. Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85068739821
"Adibfar A., Costin A.M.","57202945239;55200193500;","Creation of a Mock-up Bridge Digital Twin by Fusing Intelligent Transportation Systems (ITS) Data into Bridge Information Model (BrIM)",2022,"Journal of Construction Engineering and Management","148","9","04022094","","",,1,"10.1061/(ASCE)CO.1943-7862.0002332","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134403624&doi=10.1061%2f%28ASCE%29CO.1943-7862.0002332&partnerID=40&md5=81bebad90f75679dc41e7666aec0daa2","M.E. Rinker Sr. School Of Construction Management, Univ. Of Florida, 323 Rinker Hall, Gainesville, FL  32603, United States","Adibfar, A., M.E. Rinker Sr. School Of Construction Management, Univ. Of Florida, 323 Rinker Hall, Gainesville, FL  32603, United States; Costin, A.M., M.E. Rinker Sr. School Of Construction Management, Univ. Of Florida, 323 Rinker Hall, Gainesville, FL  32603, United States","Passage of overweighted commercial vehicles is one of the significant causes of damage to the pavement and structural components of bridges. Weigh-in-motion (WIM) systems can currently detect real-time traffic data; however, these data are stored in standalone databases. Building information modeling (BIM) has transformed the construction industry by injecting ""information""into the building model and integrating different databases. BIM capabilities for bilateral exchange of data led to the inception of digital twin. This research investigates the feasibility of developing a digital twin of a mock-up bridge by integrating WIM data into a bridge information model (BrIM). The system was validated by first creating a mock-up bridge with affixed weight sensors attached to microcomputers and then developing a BrIM model and passing scaled vehicles over in real time with varying weight capacities. This study showed the feasibility of creating digital twins, ultimately enabling future research. © 2022 American Society of Civil Engineers.","Bridge; Case study; Digital Twin; Infrastructure; Internet of Things","Architectural design; Commercial vehicles; Construction industry; Data integration; Intelligent systems; Mockups; Office buildings; Real time systems; Building Information Modelling; Building model; Case-studies; Information Modeling; Infrastructure; Intelligent transportation systems; Mock up; Real-time traffic datum; Structural component; Weigh-in-motion systems; Internet of things",,,,,,,,"Adibfar, A., (2020) Bridge digital twins: Fusion of intelligent transportation systems (ITS) sensor data and bridge information modeling (BrIM) for interoperability, , Doctoral dissertation, M. E. Rinker Sr School of Construction Management, Dept. of Design, Construction, and Planning, Univ. of Florida; Adibfar, A., Costin, A., (2019) Advances in informatics and computing in civil and construction engineering, pp. 43-50. , a. "" Next generation of transportation infrastructure management: Fusion of intelligent transportation systems (ITS) and bridge information modeling (BrIM)."" In, Cham, Switzerland: Springer; Adibfar, A., Costin, A., (2019) Evaluation of IFC for the augmentation of intelligent transportation systems (ITS) into bridge information models (BrIM), , b. "" "" In Proc. ASCE Int. Conf. on Computing in Civil Engineering. Reston, VA: ASCE; Adibfar, A., Costin, A., (2021) Integrated management of bridge infrastructure through bridge digital twins: A preliminary case study, , a. "" "" In Proc. ASCE Int. Conf. on Computing in Civil Engineering 2021. 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Struct., 30 (9), pp. 2347-2359. , https://doi.org/10.1016/j.engstruct.2008.01.013; Chen, Y., Modeling and analysis methods of bridges and their effects on seismic responses: II-implementation (1996) Comput. Struct., 59 (1), pp. 99-114. , https://doi.org/10.1016/0045-7949(95)00226-X; Costin, A., (2016) A new methodology for interoperability of heterogeneous bridge information models, , Ph.D. Dissertation, School of Civil & Environmental Engineering, Georgia Institute of Technology; Costin, A., Adibfar, A., Hu, H., Chen, S., Building information modeling (BIM) for transportation infrastructure-Literature review, applications, challenges, and recommendations (2018) Autom. Constr., 94 (3), pp. 257-281. , https://doi.org/10.1016/j.autcon.2018.07.001; Costin, A., Adibfar, A., Nawari, N., Eastman, C.M., (2019) Preliminary evaluation of the industry foundation classes (IFC) to enable smart city applications, , In Proc. 21st CIB World Building Congress-Constructing smart Cities. 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Procedia, 50 (10), pp. 121-129. , https://doi.org/10.1016/j.trpro.2020.10.015; Elnabwy, M., Kaloop, M., Elbeltagi, E., Talkha steel highway bridge monitoring and movement identification using RTK-GPS technique (2013) Measurement, 46 (9), pp. 4282-4292. , https://doi.org/10.1016/j.measurement.2013.08.014; (2018) Truck size and weight research pooled fund project TPF-5(283): The influence of vehicular live loads on bridge performance, , https://highways.dot.gov/bridges-and-structure/long-term-bridge-performance/truck-size-and-weight-research, FHWA. "" "" Accessed October 27, 2019; Fortino, S., Genoese, A., Genoese, A., Nunes, L., Palma, P., Numerical modeling of the hygro-thermal response of timber bridges during their service life: A monitoring case-study (2013) Constr. Build. Mater., 47 (6), pp. 1225-1234. , https://doi.org/10.1016/j.conbuildmat.2013.06.009; Hofmann, W., Branding, F., Implementation of an IoT and cloud-based digital twin for real-time decision support in port operations (2019) IFAC PapersOnLine, 52 (13), pp. 2104-2109. , https://doi.org/10.1016/j.ifacol.2019.11.516; Hüthwohl, P., Lu, R., Brilakis, I., (2016) Challenges of bridge maintenance inspection, pp. 51-58. , In Proc. 16th Int. Conf. on Computing in Civil and Building Engineering (ICCCBE2016), edited by N. Yabuki and K. Makanae, Osaka, Japan: ICCCBE2016 Organizing Committee; Jeong, S., Byun, J., Kimb, D., Sohn, H., Bae, I.H., Law, K.H., (2015) A data management infrastructure for bridge monitoring, , In Proc. SPIE 9435, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2015, 94350P. 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"Hosamo H.H., Hosamo M.H.","57222252101;57821152300;","Digital Twin Technology for Bridge Maintenance using 3D Laser Scanning: A Review",2022,"Advances in Civil Engineering","2022",,"2194949","","",,1,"10.1155/2022/2194949","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135059036&doi=10.1155%2f2022%2f2194949&partnerID=40&md5=84672885aa5cbb405f0581b333c3b0c2","University of Agder, Jon Lilletuns vei 9, Grimstad, 4879, Norway; HCO Cyber Security, Advania, Oslo, Norway","Hosamo, H.H., University of Agder, Jon Lilletuns vei 9, Grimstad, 4879, Norway; Hosamo, M.H., HCO Cyber Security, Advania, Oslo, Norway","There has been a significant surge in the interest in adopting cutting-edge new technologies in the civil engineering industry in recent times that monitor the Internet of Things (IoT) data and control automation systems. By combining the real and digital worlds, digital technologies, such as Digital Twin, provide a high-level depiction of bridges and their assets. The inspection, evaluation, and management of infrastructure have experienced profound changes in technological advancement over the last decade. Technologies like laser scanners have emerged as a viable replacement for labor-intensive, costly, and dangerous traditional methods that risk health and safety. The new maintenance techniques have increased their use in the construction section, particularly regarding bridges. This review paper aims to present a comprehensive and state-of-the-art review upon using laser scanners in bridge maintenance and engineering and looking deeper into the study field in focus and researchers' suggestions in this field. Moreover, the review was conducted to gather, evaluate, and analyze the papers collected in the years from 2017 to 2022. The interaction of research networks, dominant subfields, the co-occurrence of keywords, and countries were all examined. Four main categories were presented, namely machine learning, bridge management system (BMS), bridge information modeling (BrIM), and 3D modeling. The findings demonstrate that information standardization is the first significant obstacle to be addressed before the construction sector can benefit from the usage of Digital Twin. 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Proceedings of the International Symposium on Automation and Robotics in Construction, 29; Laefer, D.F., Truong-Hong, L., Carr, H., Singh, M., Crack detection limits in unit based masonry with terrestrial laser scanning (2014) NDT & e International, 62, pp. 66-76. , 2-s2.0-84890779641; Cabaleiro, M., Lindenbergh, R., Gard, W.F., Arias, P., Van De Kuilen, J.W.G., Algorithm for automatic detection and analysis of cracks in timber beams from LiDAR data (2017) Construction and Building Materials, 130, pp. 41-53. , 2-s2.0-84997079941; Barazzetti, L., Parametric as-built model generation of complex shapes from point clouds (2016) Advanced Engineering Informatics, 30 (3), pp. 298-311. , 2-s2.0-84966430627; Cheng, L., Chen, S., Liu, X., Xu, H., Wu, Y., Li, M., Chen, Y., Registration of laser scanning point clouds: A review (2018) Sensors, 18, p. 1641. , 2-s2.0-85047327614; Gómez, G.B., Jaime, E.Z., Raúl, F., Automated Registration of 3D Scans Using Geometric Features and Normalized Color Data (2013) Computer-Aided Civil and Infrastructure Engineering, 28, pp. 98-111; Wu, Q., Xu, K., Wang, J., Constructing 3D CSG Models from 3D Raw Point Clouds (2018) Computer Graphics Forum, 37, pp. 221-232; Xiong, X., Adan, A., Akinci, B., Huber, D., Automatic creation of semantically rich 3D building models from laser scanner data (2013) Automation in Construction, 31, pp. 325-337. , 2-s2.0-84873283130; Son, H., Kim, C., Kim, C., 3D reconstruction of as-built industrial instrumentation models from laser-scan data and a 3D CAD database based on prior knowledge (2015) Automation in Construction, 49, pp. 193-200. , 2-s2.0-85027921229; Shugen, W., Qiuyuan, G., Mingwei, S., Simple Building Reconstruction from Lidar Data and Aerial Imagery, , Proceedings of the 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering June 2012 Nanjing, China; Laefer, D.F., Harnessing remote sensing for civil engineering: Then, now, and tomorrow (2020) Lecture Notes in Civil Engineering, Lecture Notes in Civil Engineering, 33; Yan, Y., Guldur, B., Hajjar, J.F., (2017) Automated Structural Modelling of Bridges from Laser Scanning, , Colorado, USA Structures Congress","Hosamo, H.H.; University of Agder, Jon Lilletuns vei 9, Norway; email: haidar.hosamo@uia.no",,,"Hindawi Limited",,,,,16878086,,,,"English","Adv. Civ. Eng.",Review,"Final","All Open Access, Gold",Scopus,2-s2.0-85135059036
"Samadi D., Taghaddos H., Nili M.H., Noghabaei M.","57484188500;26031827800;57220864570;57202532070;","Development of a Bridge Maintenance System Using Bridge Information Modeling",2021,"Civil Engineering Infrastructures Journal","54","2",,"351","364",,1,"10.22059/CEIJ.2020.298837.1661","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126118772&doi=10.22059%2fCEIJ.2020.298837.1661&partnerID=40&md5=34888372c21e87eaede10b4ec24a3d8c","M.Sc., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, United States","Samadi, D., M.Sc., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Taghaddos, H., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Nili, M.H., School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran; Noghabaei, M., Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, United States","Bridges play a critical role in the transportation system network; accordingly, assuring satisfaction with the service level of these structures is vital for bridge maintenance managers. Thus, it is vital to determine the optimum bridge maintenance plan (i.e., the optimum timing and type of repair activities applied to the bridge elements) considering the budget limitations. To optimize the bridge maintenance plan, some researchers have focused on developing optimization models, including the Genetic Algorithm (GA). However, a few studies have employed Bridge Information Modeling (BrIM) to enhance bridge maintenance management. This study focuses on developing an integrated framework based on BrIM and bridge maintenance optimization to utilize visualization capabilities of BrIM to assist maintenance managers in making decisions. The presented framework optimizes the bridge maintenance plan at the sub-element level. The BrIM automatically feeds into the developed GA optimization system. The introduced framework is successfully verified using a real-world case study. © University of Tehran 2021","Bridge Information Modeling (BrIM); Bridge Maintenance Plan; Genetic Algorithm (GA); Maintenance Optimization",,,,,,,,,"Akbari, R., Maalek, S., A road map for civil engineers towards bridge engineering through academic education and professional training (2017) Civil Engineering Infrastructures Journal, 50 (1), pp. 51-73; Alikhani, H., Alvanchi, A., Using genetic algorithms for long-term planning of network of bridges (2019) Scientia Iranica A, 26 (5), pp. 2653-2664; Becerik-Gerber, B., Jazizadeh, F., Li, N., Calis, G., Application areas and data requirements for BIM-enabled facilities management (2011) Journal of Construction Engineering and Management, 138 (3), pp. 431-442; Chan, B., Guan, H., Hou, L., Jo, J., Blumenstein, M., Wang, J., Defining a conceptual framework for the integration of modelling and advanced imaging for improving the reliability and efficiency of bridge assessments (2016) Journal of Civil Structural Health Monitoring, 6 (4), pp. 703-714; Chassiakos, A., Vagiotas, P., Theodorakopoulos, D., A knowledge-based system for maintenance planning of highway concrete bridges (2005) Advances in Engineering Software, 36 (11), pp. 740-749; Chen, H.-M., Wang, Y.-H., A 3-dimensional visualized approach for maintenance and management of facilities (2009) Proceedings of ISARC09, pp. 468-475. , Austin, Texas, USA; Chen, W.-F., Duan, L., (2014) Bridge engineering handbook: Construction and maintenance, , CRC Press, Boca Raton, Florida, USA; De Brito, J., Branco, F., Thoft-Christensen, P., Sørensen, J.D., An expert system for concrete bridge management (1997) Engineering Structures, 19 (7), pp. 519-526; Eastman, C., Eastman, C.M., Teicholz, P., Sacks, R., (2011) BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors, , John Wiley & Sons, Hoboken, New Jersey, USA; Elbehairy, H., Hegazy, T., Soudki, K., Integrated multiple-element bridge management system (2009) Journal of Bridge Engineering, 14 (3), pp. 179-187; Evans, D., (2018) Bridge inspection report, 2018 Inspection Year, , https://www.princeedwardisland.ca/sites/default/files/publications/bridgeinspection2018.pdf, Government of Prince Edward Island, (Access Date: 2020 June 10); Farran, M., Zayed, T., Fitness-oriented multi-objective optimisation for infrastructures rehabilitations (2015) Structure and Infrastructure Engineering, 11 (6), pp. 761-775; Frangopol, D.M., Liu, M., Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost (2007) Structure and Infrastructure Engineering, 3 (1), pp. 29-41; Frangopol, D.M., Soliman, M., Life-cycle of structural systems: Recent achievements and future directions (2016) Structure and Infrastructure Engineering, 12 (1), pp. 1-20; Furuta, H., Kameda, T., Fukuda, Y., Frangopol, D.M., Life-cycle cost analysis for infrastructure systems: Life cycle cost vs. safety level vs. service life (2004) Life-cycle Performance of Deteriorating Structures: Assessment, Design and Management, pp. 19-25. , Lausanne, Switzerland; Furuta, H., Kameda, T., Nakahara, K., Takahashi, Y., Frangopol, D.M., Optimal bridge maintenance planning using improved multi-objective genetic algorithm (2006) Structure and Infrastructure Engineering, 2 (1), pp. 33-41; Ghadiri Mohghaddam, D., (2014) Framework for Integrating Bridge Inspection Data with Bridge Information Model, , https://spectrum.library.concordia.ca/978607/, MSc. Dissertation, Concordia University, (Access Date: 2020 June 10); Gholami, M., Sam, A.R.B.M., Yatim, J.M., Assessment of bridge management system in Iran (2013) Procedia Engineering, 54, pp. 573-583; Hammad, A., Zhang, C., Hu, Y., Mozaffari, E., Mobile model-based bridge lifecycle management system (2006) Computer-Aided Civil and Infrastructure Engineering, 21 (7), pp. 530-547; Hong, T., Hastak, M., Evaluation and determination of optimal MR&R strategies in concrete bridge decks (2007) Automation in Construction, 16 (2), pp. 165-175; Huang, Y.-H., Huang, H.-Y., A model for concurrent maintenance of bridge elements (2012) Automation in Construction, 21, pp. 74-80; Ilter, D., Ergen, E., BIM for building refurbishment and maintenance: current status and research directions (2015) Structural Survey, 33 (3), pp. 228-256; Kim, S., Frangopol, D.M., Soliman, M., Generalized probabilistic framework for optimum inspection and maintenance planning (2013) Journal of Structural Engineering, 139 (3), pp. 435-447; Lin, Y.-C., Su, Y.-C., Developing mobile-and BIM-based integrated visual facility maintenance management system (2013) The Scientific World Journal, 2013 (7), p. 124249; Liu, R., Issa, R., Automatically updating maintenance information from a BIM database (2012) Proeedings of International Conference on Computing in Civil Engineering, pp. 373-380. , Florida, USA; Marzouk, M., Abdelaty, A., BIM-based framework for managing performance of subway stations (2014) Automation in Construction, 41, pp. 70-77; Marzouk, M., Hisham, M., Bridge information modeling in sustainable bridge management (2011) Proceedings of ICSDC, pp. 457-466. , Lawrence, Kansas, USA; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) Journal of Bridge Engineering, 21 (4), p. 04015076; Mirzaei, Z., Adey, B.T., Determination of the most sustainable bridge work programs through the improved structure level considerations (2018) Structure and Infrastructure Engineering, 14 (8), pp. 1123-1139; Miyamoto, A., Kawamura, K., Nakamura, H., Bridge management system and maintenance optimization for existing bridges (2000) Computer‐Aided Civil and Infrastructure Engineering, 15 (1), pp. 45-55; Miyamoto, A., Motoshita, M., Development and practical application of a bridge management system (J-BMS) in Japan (2015) Civil Engineering Infrastructures Journal, 48 (1), pp. 189-216; Morcous, G., Lounis, Z., Maintenance optimization of infrastructure networks using genetic algorithms (2005) Automation in Construction, 14 (1), pp. 129-142; Motamedi, A., Hammad, A., Asen, Y., Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management (2014) Automation in Construction, 43, pp. 73-83; (2008) United States national building information modeling standard, version 1, Part 1: Overview, principles, and methodologies, , NIBS Nantional Institute of Building Sciences, USA; Nili, M.H., Zahraie, B., Taghaddos, H., BrDSS: A decision support system for bridge maintenance planning employing bridge information modeling (2020) Smart Structures and Systems, 26 (4), pp. 533-544; Sahrapeyma, A., Hosseini, A., Strategic planning for the national bridge stock of Iran (2013) Civil Engineering Infrastructures Journal, 46 (1), pp. 51-68; (2016) NBI rating guideline, , https://www.michigan.gov/documents/mdot/BIR_Ratings_Guide_Combined_2016-3-15_517075_7.pdf, Michigan Department of Transportation (Access Date: 2020 June 5); Yanev, B., Testa, R.B., Life-cycle performance of bridge components in New York City (1997) Recent Advances in Bridge Engineering, pp. 385-392","Taghaddos, H.; School of Civil Engineering, Iran; email: htaghaddos@ut.ac.ir",,,"University of Tehran",,,,,23222093,,,,"English","Civ. Eng. Infrastruct. J.",Article,"Final","",Scopus,2-s2.0-85126118772
"Patel N., Parikh K., Patel B.","57223107709;57223111041;57223103465;","Bridge information modeling and ar using terrestrial laser scanner",2021,"Reliability: Theory and Applications","16",,,"17","23",,1,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104840855&partnerID=40&md5=41ffb44b9e51d4cc0b68c0e3de6da9d9","Faculty of Technology, Cept University Ahmedabad, Khodiyar Cad Center, Ahmedabad, India","Patel, N., Faculty of Technology, Cept University Ahmedabad, Khodiyar Cad Center, Ahmedabad, India; Parikh, K., Faculty of Technology, Cept University Ahmedabad, Khodiyar Cad Center, Ahmedabad, India; Patel, B., Faculty of Technology, Cept University Ahmedabad, Khodiyar Cad Center, Ahmedabad, India","There are many incidents where bridges collapse before its life span is over or just after it is built or even during construction, so all this calls for its routine inspection and methods to do it as efficiently as possible. One of the methods to do an inspection is using a terrestrial laser scanner. This paper mainly focuses on studying the methodology for inspecting the bridges using a terrestrial laser scanner and Augmented Reality technology. In this paper, Laser scanning data was used to prepare Bridge Information Model and that model was further processed in Unity to create an Augmented Reality model. All this requires various data processing and post-processing. With the help of this model, one can do bridge inspection at the comfort of the office and reaching those inaccessible areas which are not possible to reach with traditional methods. This paper focuses on finding a different method or approach to do Bridge Information Modeling and get data of bridges for maintenance purposes. Visual inspection was carried out from the model without going to the site. © 2021 Gnedenko Forum. All rights reserved.","Ar technology; Bridge information modeling; Point cloud; Terrestrial laser scanner; Trimble business center; Unity; Visual inspection",,,,,,,,,"Adrain, R., Armour, I., Bach, J., Laser scanning cameras for in-reactor inspection (1987) Sensor Review, 7 (2), pp. 68-76; Alampalli, S., Special Issue on Bridge Inspection and Evaluation (2010) Journal of Bridge Engineering, 15 (4), pp. 349-351; Badenko, V., Volgin, D., Lytkin, S., Deformation monitoring using laser-scanned point clouds and BIM (2018) MATEC Web Of Conferences, 245, p. 01002; Scanning laser is key to the lens inspection system (1988) NDT & E International, 21 (5), p. 354. , Battelle; (2020) BrIM bridge inspections in the context of Industry 4.0 trends, , https://www.academia.edu/38617273/BrIM-bridge-inspections-in-the-context-of-Industry-4.0-trends, Retrieved 30 April 2020, from; Cha, G., Park, S., Oh, T., A Terrestrial LiDAR-Based Detection of Shape Deformation for Maintenance of Bridge Structures (2019) Journal Of Construction Engineering And Management, 145 (12), p. 04019075; Chao, M., Chiu, H., Lu, C., Jeng, C., Using three-dimensional laser scanning for monitoring a long-span arch bridge launch (2019) Proceedings of the Institution of Civil Engineers-Bridge Engineering, 172 (3), pp. 204-216; Chong, H., Lopez, R., Wang, J., Wang, X., Zhao, Z., Comparative Analysis on the Adoption and Use of BIM in Road Infrastructure Projects (2016) Journal Of Management In Engineering, 32 (6), p. 05016021; Fu, F, Advanced Modelling Techniques In Structural Design, , n.d; Harding, P., Gerard, P., Ryall, M, Bridge Management, , n.d; IANG, Jianjing, Xinzheng, LU, GUO, Jingjun, Study for Real-time Monitoring of Large-Span Bridge Using GPS (2002) Proc. ISSST 2002, ""Progress in Safety Science and Technology, pp. 308-331. , Beijing/New York: Science Press, HUANG P., WANG YJ, LI SC, QIAN XM, eds. Tai'an, Sep. 2002; Mazurek, D., DeWolf, J., Experimental Study of Bridge Monitoring Technique (1990) Journal Of Structural Engineering, 116 (9), pp. 2532-2549; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge Information Modeling for Inspection and Evaluation (2016) Journal of Bridge Engineering, 21 (4); Omer, Muhammad, Margetts, Lee, Mosleh, Mojgan Hadi, Hewitt, Sam, Parwaiz, Muhammad, Use of gaming technology to bring bridge (2020) structure and infrastructure engineering, 15 (10), pp. 1292-1307; Nasrollahi, M., Washer, G., Estimating Inspection Intervals for Bridges Based on Statistical Analysis of National Bridge Inventory Data (2015) Journal of Bridge Engineering, 20 (9); Nikolaou, S., Geographic information systems for ground motion evaluation in seismic bridge analysis (2005) Bridge Structures, 1 (3), pp. 293-306; Olsen, M., In Situ Change Analysis and Monitoring through Terrestrial Laser Scanning (2015) Journal Of Computing In Civil Engineering, 29 (2), p. 04014040; Omer, M., Margetts, L., Hadi Mosleh, M., Hewitt, S., Parwaiz, M., Use of gaming technology to bring bridge inspection to the office (2019) Structure And Infrastructure Engineering, 15 (10), pp. 1292-1307; Roberts, G., Meng, X., Dodson, A., Integrating a Global Positioning System and Accelerometers to Monitor the Deflection of Bridges (2004) Journal Of Surveying Engineering, 130 (2), pp. 65-72; SAMEC, V., Bentley Bridge Information Modelling-Solution for Bridge Information Mobility (2016) IABSE Symposium Report, 106 (14), pp. 24-25; Tah, J., Carr, V., Howes, R., Information modelling for case-based construction planning of highway bridge projects (1999) Advances in Engineering Software, 30 (7), pp. 495-509; Tang, P., Akinci, B., Automated Measurement Extraction from Laser Scanned Point Clouds to Support Bridge Inspection (2008) IABSE Symposium Report, 94 (6), pp. 15-22; Tang, P., Akinci, B., Garrett, J., Laser Scanning for Bridge Inspection and Management (2007) IABSE Symposium Report, 93 (18), pp. 17-24; (2018) Bridge Inspection Manual, pp. 9-11","Patel, N.; Faculty of Technology, India; email: neha2319patel@gmail.com",,,"Gnedenko Forum",,,,,19322321,,,,"English","Reliab., Theory Appl.",Article,"Final","",Scopus,2-s2.0-85104840855
"Mabrich A., Hatami A.","57210161033;55241547700;","Application of 3D bridge information modeling in the life-cycle of bridges",2019,"20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report",,,,"1549","1552",,1,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074449442&partnerID=40&md5=51f7ff393f3a21529791f2fa33788d94","Bentley Systems, Inc, Sunrise, FL, United States","Mabrich, A., Bentley Systems, Inc, Sunrise, FL, United States; Hatami, A., Bentley Systems, Inc, Sunrise, FL, United States","Building information modeling (BIM) is a new technology in the bridge construction industry. 3D models can provide perfect numerical expression of drawings from design results. 3D information models for bridge structures improve design quality in terms of accurate drawings, constructability, and collaboration. However, there are lots of challenges to apply these techniques to actual bridge projects. For instance, bridge engineers are facing the challenge of making the vast information generated by their structural model useful for professionals further down the line in the lifecycle of the bridge. Contractors and inspectors require a 3D model which is created after the design process to add extra information related to activities and store that information in the same model. In this paper, technologies available to generate, manage, and enrich the bridge 3D model with intelligent information from construction to design and inspection are proposed. © 20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report. All rights reserved.","Analysis; BIM; BrIM; CAD; Fabrication; Life-cycle of Bridges; Maintenance; Operating","3D modeling; Architectural design; Computer aided design; Construction industry; Fabrication; Information theory; Life cycle; Maintenance; Structural design; Three dimensional computer graphics; 3d information models; Analysis; Bridge constructions; BrIM; Building Information Model - BIM; Information Modeling; Intelligent information; Operating; Bridges",,,,,,,,"BIM - Building Information - BuildingSmart International Home of OpeBIM, , www.buildingsmart-tech.org; IFC Bridges - BuildingSmart, , www.buildingsmart-tech.org/infrastructure; All Figures Are Extracted from Bentley Software: Open Bridge Modeller®, RM Bridge®, Pro Concrete®, Synchro®, , InspectTech®, Lumen RT®","Hatami, A.; Bentley Systems, United States; email: Afshin.Hatami@bentley.com",,"Allplan (Gala);et al.;Hardesty and Hanover;Silman;Wiss, Janney, Elstner Associates, Inc.;WSP","International Association for Bridge and Structural Engineering (IABSE)","20th IABSE Congress, New York City 2019: The Evolving Metropolis","4 September 2019 through 6 September 2019",,152767,,9783857481659,,,"English","Congr. IABSE, New York City: Evol. Metropolis - Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85074449442
"Park S.I., Kim B.-G., Goh W., Zi G.","57204956510;56125080500;57477961800;6701704145;","Development of Open-Assistant Environment for Integrated Operation of 3D Bridge Model and Engineering Document Information",2022,"Applied Sciences (Switzerland)","12","5","2510","","",,,"10.3390/app12052510","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125817926&doi=10.3390%2fapp12052510&partnerID=40&md5=b577efa2f7bea6f686aed5a5e948801f","Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO  80309, United States; Research Institute for Safety Performance, Korea Authority of Land & Infrastructure Safety, Jinju, 52856, South Korea; Taesung SNI Singapore Branch, Singapore, 208652, Singapore; School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, 02841, South Korea","Park, S.I., Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO  80309, United States, Research Institute for Safety Performance, Korea Authority of Land & Infrastructure Safety, Jinju, 52856, South Korea; Kim, B.-G., Taesung SNI Singapore Branch, Singapore, 208652, Singapore; Goh, W., School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, 02841, South Korea; Zi, G., School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, 02841, South Korea","This study proposes a method for assistant environments to integrate 3D bridge model information and engineering document fragments. The engineering document content varies depend-ing on the process. Therefore, we accept a loose coupling concept to support the independence of each information set instead of using a specific data model for effective integration. The engineering document is translated into an Extensible Markup Language (XML)-based structured format based on the explicit and apparent semantic structure of the document. An extended industry foundation classes (IFC) schema is proposed to manage the bridge information model, as well as document fragments. An information document (iMapDoc) is proposed to manage interim data to connect a 3D digital model, an IFC model, and engineering document fragments. Document fragments on a specific component in the 3D bridge model are retrieved to validate the developed integrated assistant module. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.","3D bridge model; Document fragment; Engineering document; IFC-based bridge model; Integrated operation",,,,,,"National Research Foundation of Korea, NRF; Ministry of Science and ICT, South Korea, MSIT: NRF-2021R1A5A1032433","Funding: This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; No. NRF-2021R1A5A1032433).",,"Tatum, C.B., Integration: Emerging management challenge (1990) J. Manag. Eng, 6, pp. 47-58. , [CrossRef]; Park, S.I., Park, J., Kim, B.G., Lee, S.H., Improving applicability for information model of an IFC-based steel bridge in the design phase using functional meanings of bridge components (2018) Appl. 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Eng, 30, p. 04015014. , [CrossRef]; Song, J., Lee, J.K., Choi, J., Kim, I., Deep learning-based extraction of predicate-argument structure (PAS) in building design rule sentences (2020) J. Comput. Des. Eng, 7, pp. 563-576. , [CrossRef]; Wang, Z., Wang, Y., Gao, K., A new model of document structure analysis (2005) Lecture Notes in Computer Science—Fuzzy Systems and Knowledge Discovery, pp. 658-666. , Wang, L., Jin, Y., Eds.; Springer: Berlin/Heidelberg, Germany; Eastman, C.M., Lee, J.m., Jeong, Y.S., Lee, J.K., Automatic rule-based checking of building designs (2009) Autom. Constr, 18, pp. 1011-1033. , [CrossRef]; Jiang, S., Wang, N., Wu, J., Combining BIM and Ontology to Facilitate Intelligent Green Building Evaluation (2018) J. Comput. Civ. Eng, 32, p. 04018039. , [CrossRef]; Zhou, P., El-Gohary, N.M., Semantic information alignment of BIMs to computer-interpretable regulations using ontologies and deep learning (2021) Adv. Eng. 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Constr, 46, pp. 38-49. , [CrossRef]; Opitz, F., Windisch, R., Scherer, R.J., Integration of document-and model-based information for project management support (2014) Procedia Eng, 85, pp. 403-411. , [CrossRef]; Park, S.I., Lee, S.H., Almasi, A., Song, J.H., Extended IFC-based strong form meshfree collocation analysis of a bridge structure (2020) Autom. Constr, 119, p. 103364. , [CrossRef]; (2017) Industry Foundation Classes Release 4.0.2.1, , https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/, (accessed on 2 July 2021); (2021) Industry Foundation Classes Release 4.3RC4, , https://github.com/bSI-InfraRoom/IFC-Documentation/tree/main/4_3_0_0/rc4, (accessed on 3 July 2021); (2021) Revit—Multidisciplinary BIM Software for Higher-Quality, Coordinated Designs, , https://www.autodesk.com/products/revit/overview, (accessed on 2 July 2021); (2021) DOM, , https://dom.spec.whatwg.org/#what, (accessed on 18 July 2021); Kleene, S.C., (1951) Representation of Events in Nerve Nets and Finite Automata, , https://www.rand.org/content/dam/rand/pubs/research_memoranda/2008/RM704.pdf, U.S. Air Force. (accessed on 20 December 2021); (2017) XML Path Language (XPath) 3.1, , https://www.w3.org/TR/2017/REC-xpath-31-20170321/, (accessed on 10 July 2021); Costin, A., Adibfar, A., Hu, H., Chen, S.S., Building Information Modeling (BIM) for transportation infrastructure—Literature review, applications, challenges, and recommendations (2018) Autom. Constr, 94, pp. 257-281. , [CrossRef]; Merenda, M., Praticò, F.G., Fedele, R., Carotenuto, R., Corte, F.G.D., A Real-Time Decision Platform for the Management of Structures and Infrastructures (2019) Electronics, 8, p. 1180. , [CrossRef]","Zi, G.; School of Civil, South Korea; email: g-zi@korea.ac.kr",,,"MDPI",,,,,20763417,,,,"English","Appl. Sci.",Article,"Final","All Open Access, Gold",Scopus,2-s2.0-85125817926
"Rojas A., Valenzuela M., Peña Á.","57223092534;56645951100;56959863300;","Structural Detailing of Bridges, Making Use of the Brim Methodology (Bridge Information Modeling), through the Creation of Parametric Models and As-Build Plans",2022,"IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation, Report",,,,"912","919",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142917207&partnerID=40&md5=45509a81d236aefbac2d7a2207d7353e","Pontifical Catholic University of Valparaiso, Faculty of Construction Engineering, Valparaiso, Chile","Rojas, A., Pontifical Catholic University of Valparaiso, Faculty of Construction Engineering, Valparaiso, Chile; Valenzuela, M., Pontifical Catholic University of Valparaiso, Faculty of Construction Engineering, Valparaiso, Chile; Peña, Á., Pontifical Catholic University of Valparaiso, Faculty of Construction Engineering, Valparaiso, Chile","Within a project related to the area of bridges, we work with different tools and between this information is usually managed through the use of CAD drawings made basically in 2D. Today, a new concept of BIM applied to bridges called Bridge Information Modeling (BrIM), which well implies being a methodology with different uses and being the solution in helping the different parties to work more collaboratively, effectively and simultaneously. This paper presents the experience of applying one of these uses in the phase of analysis and structural diagnosis of ten bridges in Chile, which demonstrates that this technology becomes a valuable tool for information management through the virtual model worked between the different parties involved in the maintenance and operation of a project. © IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation, Report. All rights reserved.","BIM; bridge; BrIM; modeling of bridges; modeling projects","Architectural design; Computer aided design; Information management; Information theory; BIM; Bridge information modeling; CAD drawings; Information Modeling; Maintenance and operation; Model programs; Modeling of bridge; Parametric models; Structural diagnosis; Virtual models; Bridges",,,,,,,,"Rojas, A., (2019) Detallamiento de uniones para el método de refuerzos de puentes de luces medias por conversión en arco atirantado, planos y especificaciones técnicas, , Chile; (2012) Informe de situación estructural puentes sobre estero Marga Marga comuna de Viña del Mar: Chile; (2010) Bases Técnicas. Estudio de Reparación de Puentes de Vila del Mar, , comuna de Viña del Mar: Chile; Shin, H., Lee, H., Oh, S., Chen, J., Analysis and Design of Reinforced Concrete Bridge Column Based on BIM (2011) Procedia Engineering; Gaitán, J., (2013) Uso de la metodología BrIM (Bridge Information Modeling) como herramienta para la planificación de la construcción de un puente de concreto en Colombia; (2015) Bridge Information Modeling (BrIM) Using Open Parametric Objects, , U.S.Departament of Transportation Federal Highway Administration. United Stated; Herman, G. A., Trotta, B. W., Peterson, J. C., (2012) Bridge information modeling; (2019) Estándar BIM para proyectos públicos, , Intercambio de Información entre solicitante y Proveedores: Chile","Rojas, A.; Pontifical Catholic University of Valparaiso, Chile; email: alvaro.rojas.esc@gmail.com",,,"International Association for Bridge and Structural Engineering (IABSE)","IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation","21 September 2022 through 23 September 2022",,184084,,9783857481840,,,"English","IABSE Congr. Nanjing - Bridg. Struct.: Connect., Integr. Harmon., Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85142917207
"Ravn U.G., Löhning T., Sørensen J.W.","57194165083;15045096200;57985529600;","The First Step Towards BIM Models in Major Bridge Design",2022,"IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation, Report",,,,"894","901",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142863817&partnerID=40&md5=303842cea083a08ba9b57db46282ee5d","COWI A/S, Lyngby, Denmark","Ravn, U.G., COWI A/S, Lyngby, Denmark; Löhning, T., COWI A/S, Lyngby, Denmark; Sørensen, J.W., COWI A/S, Lyngby, Denmark","The design of the world record 1915 Çanakkale Bridge is an example of the first steps towards using a BIM for a major bridge design. The model developed by COWI has been used to create 2D drawings and bar bending schedules, to manage interfaces and to check constructability, as well as health and safety related checks for working in congested space. Furthermore, it has proved to be an effective tool in communication with the project's stakeholders. This paper describes where BIM has been applied in the design of the 1915 Çanakkale Bridge. Here special focus is on the construction of the plinth of the tower foundations where the contractor prefabricated the reinforcement cage for each plinth onshore, including all cast-in items and the steel form work and then lifted the whole assembly (18m in diameter) into place off-shore using a floating crane. © IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation, Report. All rights reserved.","BIM; BrIM; Çanakkale Bridge","Architectural design; Binary alloys; Floating cranes; 2D drawing; BIM; Bridge design; BrIM; Constructability; Health and safety; Major bridges; Safety-Related; World records; Çanakkale bridge; Bridges",,,,,,"This paper is based on the detailed design of the 1915 Çanakkale Bridge undertaken for the contractor DLSY (Daelim, Limak, SK E&C and Yapı Merkezi) by COWI A/S.",,"Vegvesen, Statens, (2019) BIM models at bridge designs, , https://www.vegvesen.no/fag/teknologi/bruer/kontroll-og-godkjenning/modellbasertprosjektering; Pedersen, F.M, Christensen, S. C., Jacobsen, J. S., Izmit Bay Suspension Bridge - Deep Water Tower Foundations (2015) IABSE Conference - Structural Engineering: Providing Solutions to Global Challenges, , September, Geneva, Switzerland; Kroon, I. B., Polk, H., Fuglsang, K., Çanakkale Bridge - Meeting the challenges (1915) The third Istanbul Bridge Conference (IBridge2018), , November, Istanbul, Turkey; 2018","Ravn, U.G.; COWI A/SDenmark; email: ugj@cowi.com",,,"International Association for Bridge and Structural Engineering (IABSE)","IABSE Congress Nanjing 2022 - Bridges and Structures: Connection, Integration and Harmonisation","21 September 2022 through 23 September 2022",,184084,,9783857481840,,,"English","IABSE Congr. Nanjing - Bridg. Struct.: Connect., Integr. Harmon., Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85142863817
"Giorgadze I.M., Vahdatikhaki F., Voordijk J.H.","57870101400;36474119300;15063651000;","Conceptual Modeling of Lifecycle Digital Twin Architecture for Bridges: A Data Structure Approach",2022,"Proceedings of the International Symposium on Automation and Robotics in Construction","2022-July",,,"199","206",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137087198&partnerID=40&md5=6c46bacaaea1e49c698754e43223cec3","Department of Construction Management & Engineering, University of Twente, Netherlands","Giorgadze, I.M., Department of Construction Management & Engineering, University of Twente, Netherlands; Vahdatikhaki, F., Department of Construction Management & Engineering, University of Twente, Netherlands; Voordijk, J.H., Department of Construction Management & Engineering, University of Twente, Netherlands","The concept of Digital Twin (DT) has emerged in recent years to facilitate the use of Building Information Modeling during the entire projects' lifecycle. In the DT concept, cyber-physical system theory is utilized to collect condition data about an existing asset and then integrate this data into the digital model. The major limitation though is that the current scope of DT is limited to the operation and maintenance phase. Nevertheless, the DT concept can be extended to the entire lifecycle of the asset if the relevant sensory and non-sensory data are incorporated into the digital model in an automated and systematic way. However, in the current literature, there is no clear insight about such a holistic and life-cycle DT concept for infrastructure projects. Especially, there is very little understanding about how various sensory and non-sensory data from construction and operation phases can be seamlessly integrated into the 3D BIM models. Therefore, this research aims to develop a conceptual model for the architecture of Lifecycle DT (LDT) focusing on bridges. To this end, an ontological modeling approach is adopted. The proposed ontology is validated through a workshop session where domain experts assessed the results with respect to some competency questions. The outcome of the session indicated that the proposed ontology scored sufficiently in all the criteria and succeeded in satisfying the information needs of the LDT. Overall, the proposed model offers an insight into a lifecycle modeling practice as well as automated data incorporation, enabling a smooth transition towards an upgraded modeling practice. © 2022 International Association on Automation and Robotics in Construction.","Bridge information modelling; Digital twin; Lifecycle digital twin; Ontological modelling","Architectural design; Bridges; Embedded systems; Information theory; Ontology; Robotics; 'current; Bridge information modeling; Building Information Modelling; Conceptual model; Digital modeling; Information Modeling; Lifecycle digital twin; Ontological modeling; Ontology's; Sensory data; Life cycle",,,,,,,,"White paper: National digital twin | Bits & Pieces, , https://global.royalhaskoningdhv.com/digital/resources/publications/national-digital-twin, (accessed Feb. 14, 2022); Borangiu, T., Trentesaux, D., Leitão, P., Boggino, A. G., Botti, V., Studies in Computational Intelligence 853 Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future, , http://www.springer.com/series/7092, [Online]. Available; Stojanovic, V., Trapp, M., Richter, R., Hagedorn, B., Dollner5, J., Semantic Enrichment of Indoor Point Clouds An Overview of Progress towards Digital Twinning; Işikdaǧ, Ü., Enhanced Building Information Models Using IoT Services and Integration Patterns; (1959) Wulfsberg, 1. interdisziplinäre Konferenz zur Zukunft der Wertschöpfung Konferenzband, , J; Becerik-Gerber, B., Jazizadeh, F., Li, N., Calis, G., Application Areas and Data Requirements for BIM-Enabled Facilities Management (2012) Journal of Construction Engineering and Management, 138 (3), pp. 431-442. , Mar; Chen, J., Bulbul, T., Taylor, J. E., Olgun, G., A Case Study of Embedding Real Time Infrastructure Sensor Data to BIM; Glaessgen, E. H., Stargel, D. S., (2012) The digital twin paradigm for future NASA and U.S. Air force vehicles; Haag, S., Anderl, R., Digital twin - Proof of concept (2018) Manufacturing Letters, 15, pp. 64-66. , Jan; Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F., Digital twin-driven product design, manufacturing and service with big data (2018) International Journal of Advanced Manufacturing Technology, 94 (9-12), pp. 3563-3576. , Feb; Opoku, D.-G. J., Perera, S., Osei-Kyei, R., Rashidi, M., Famakinwa, T., Bamdad, K., Drivers for Digital Twin Adoption in the Construction Industry: A Systematic Literature Review (2022) Buildings, 12 (2), p. 113. , Jan; Opoku, D. G. J., Perera, S., Osei-Kyei, R., Rashidi, M., Digital twin application in the construction industry: A literature review (2021) Journal of Building Engineering, 40. , Elsevier Ltd, Aug. 01; Gervasio, H., Dimova, S., Pinto, A., Benchmarking the life-cycle environmental performance of buildings (2018) Sustainability (Switzerland), 10 (5). , May; Hu, W., Zhang, T., Deng, X., Liu, Z., Tan, J., Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges (2021) Journal of Intelligent Manufacturing and Special Equipment, 2 (1), pp. 1-34. , Aug; Jiang, F., Ma, L., Broyd, T., Chen, K., Digital twin and its implementations in the civil engineering sector (2021) Automation in Construction, 130. , Elsevier B.V., Oct. 01; Vahdatikhaki, F., el Ammari, K., Langroodi, A. K., Miller, S., Hammad, A., Doree, A., Beyond data visualization: A context-realistic construction equipment training simulators (2019) Automation in Construction, 106. , Oct; Vahdatikhaki, F., (2015) TOWARDS SMART EARTHWORK SITES USING LOCATIONBASED GUIDANCE AND MULTI-AGENT SYSTEMS; Raad, J., Cruz, C., Cruz, C. A., (2015) A Survey on Ontology Evaluation Methods; Delir Haghighi, P., Burstein, F., Zaslavsky, A., Arbon, P., Development and evaluation of ontology for intelligent decision support in medical emergency management for mass gatherings (2013) Decision Support Systems, 54 (2), pp. 1192-1204. , Jan",,,"Autodesk;Camara Colombiana de la Construccion (CAMACOL);Construsoft;MCad - Training and Consulting","International Association for Automation and Robotics in Construction (IAARC)","39th International Symposium on Automation and Robotics in Construction, ISARC 2022","13 July 2022 through 15 July 2022",,181877,24135844,9789526952420,,,"English","Proc. Int. Symp. Autom. Robot. Constr.",Conference Paper,"Final","",Scopus,2-s2.0-85137087198
"Bień J., Salamak M.","7003571099;25028351300;","The management of bridge structures – challenges and possibilities [Zarządzanie obiektami mostowymi – wyzwania i możliwości]",2022,"Archives of Civil Engineering","68","2",,"5","35",,,"10.24425/ace.2022.140627","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133529116&doi=10.24425%2face.2022.140627&partnerID=40&md5=ae8c85ff7d7dd6b4cf0cebe2404a39f5","Wrocław University of Science and Technology, Faculty of Civil Engineering, Wybrzeże Wyspiańskiego 27, Wrocław, 50-370, Poland; Silesian University of Technology, Faculty of Civil Engineering, ul. Akademicka 5, Gliwice, 44-100, Poland","Bień, J., Wrocław University of Science and Technology, Faculty of Civil Engineering, Wybrzeże Wyspiańskiego 27, Wrocław, 50-370, Poland; Salamak, M., Silesian University of Technology, Faculty of Civil Engineering, ul. Akademicka 5, Gliwice, 44-100, Poland","Bridges are particularly vulnerable elements of transport infrastructures. In many cases, bridge structures may be subject to higher volumes of traffic and higher loads as well as more severe environmental conditions than it was designed. Sound procedures to ensure monitoring, quality control, and preventive maintenance systems are therefore vital. The paper presents main challenges and arriving possibilities in management of bridge structures, including: relationships between environment and bridge infrastructure, improvement of diagnostic technologies, advanced modelling of bridges in computer-based management systems, development of knowledge-based expert systems with application of artificial intelligence, applications of technology of Bridge Information Modelling (BrIM) with augmented and virtual reality techniques. Presented activities are focused on monitoring the safety of bridges for lowering the risk of an unexpected collapse significantly as well as on efficient maintenance of bridges as components of transport infrastructure – by means of integrated management systems. The proposed classification of Bridge Management Systems shows the history of creating such systems and indicates the expected directions of their development, taking into account changing challenges and integrating new developing technologies, including automation of decision-making processes. © 2022. Jan Bień, Marek Salamak.","BIM; bridge; Bridge Management System; diagnostics; environment; management","Bridges; Environmental management; Expert systems; Information management; Life cycle; Preventive maintenance; Virtual reality; BIM; Bridge management system; Bridge structures; Diagnostic; Environment; Environmental conditions; High load; High volumes; Traffic loads; Transport infrastructure; Decision making",,,,,,,,"Pang, B., Yang, P., Wang, Y., Kendall, A., Xie, H., Zhang, Y., Life cycle environmental impact assessment of a bridge with different strengthening schemes (2015) The International Journal of Life Cycle Assessment, 20 (9), pp. 1300-1311; Biondini, F., Frangopol, D.M., (2012) Bridge Maintenance, Safety, Management, Resilience and Sustainability, , Eds., CRC Press; Yehia, S., Abudayyeh, O., Nabulsi, S., Abdelqader, I., Detection of common defects in concrete bridge decks using non-destructive evaluation techniques (2007) Journal of Bridge Engineering, 12 (2), pp. 215-225; Bień, J., (2010) Defects and diagnostics of bridge structures (in Polish), , Warsaw: Transport and Communication Publishers; Hoła, J., Bień, J., Sadowski, L., Schabowicz, K., Non-destructive and semi-destructive diagnostics of concrete structures in assessment of their durability (2015) Bulletin of the Polish Academy of Sciences, Technical Sciences, 63 (1), pp. 87-96; Bień, J., Kamiński, T., Kużawa, M., Taxonomy of non-destructive field tests of bridge materials and structures (2019) Archives of Civil and Mechanical Engineering, 19 (4), pp. 1353-1367; Wang, X., Dou, W., Chen, S., Ribarsky, W., Chang, R., An Interactive Visual Analytics System for Bridge Management (2010) Computer Graphics Forum, 29 (3), pp. 1033-1042; Thompson, P.D., Small, E.P., Johnson, M., Marshall, A.R., The PONTIS Bridge Management System (1998) Structural Engineering International, 8 (4), pp. 303-308; Soderqvist, M.K., Veijola, M., The Finnish Bridge Management System (1998) Structural Engineering International, 8 (4), pp. 315-319; Thompson, P.D., Chetham, A., Merlo, T., Ellis, R., Kerr, B., The New Ontario Bridge Management System (2000) Transportation Research Circular, (498). , F-6/1–15; Bień, J., Modelling of structure geometry in Bridge Management Systems (2011) Archives of Civil and Mechanical Engineering, 11 (3), pp. 519-532; Kamiński, T., Bień, J., Bień, B., An expert tool for assessment of damaged masonry arch bridges (2013) Proc. 7th International Conference on Arch Bridges, pp. 691-698. , Trogir Split, Croatia; Bień, J., Kużawa, M., NDT-based bridge condition assessment supported by expert tools (2015) Proc. International Conference of Numerical Analysis and Applied Mathematics 2015, pp. 1-4. , American Institute of Physics, Rhodes, AIP Publishing, 2016; Vagnoli, M., Remenyte-Prescott, R., Andrews, J., Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges (2017) Structural Health Monitoring, 17 (4), pp. 971-1007; Shim, Ch.-S., Kang, H., Dang, N.S., Lee, D., Development of BIM-based bridge maintenance system for cable-stayed bridges (2017) Smart Structures & Systems, 20 (6), pp. 697-708; Azuma, R.T., A Survey of Augmented Reality (1997) Tele-operators Virtual Environ, 6 (4), pp. 355-385; Bień, J., Kużawa, M., Bień, B., To See is to Know: Visualization in Bridge Inspection and Management (2010) Proc. 5th International Conference on Bridge Maintenance, Safety and Management, pp. 567-574. , Philadelphia; Salamak, M., Januszka, M., BrIM bridge inspections in the context of Industry 4.0 trends (2018) Proc. of IABMAS 2018, Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges, pp. 2260-2267; Wang, X., Love, P.E.D., Jeong Kim, M., Park, C., Sing, C., Hou, L., A conceptual framework for integrating building information modelling with augmented reality (2013) Automation in Construction, 34, pp. 37-44; Chunfeng, W., ZhenweI, Z., Siyuan, L., Youliang, D., Zhao, X., Zegang, Y., Yefei, X., Fangzhou, Y., Development of a Bridge Management System Based on the Building Information Modelling Technology (2019) Sustainability, 11 (17); Olofsson, J., Assessment of European Railway Bridges for Future Traffic Demands and Longer Lives – EC Project “Sustainable Bridges (2005) Journal of Structure and Infrastructure Engineering, 1 (2), pp. 93-100; Matos, J., An overview of the European situation on quality control of existing bridges – COST Action TU1406 (2018) Proc. of the 40th IABSE Symposium, , Nantes, France; Bień, J., Krzyżanowski, J., Rawa, P., Zwolski, J., Dynamic Load Tests in Bridge Management (2004) Archives of Civil and Mechanical Engineering, 4 (2), pp. 63-78; Cunha, A., Caetano, E., Magalhaes, F., Output-Only Dynamic Testing of Bridges and Special Structure (2007) Structural Concrete, 8 (2), pp. 67-85; Wenzel, H., (2009) Health Monitoring of Bridges, , J. Wiley & Sons Ltd; Zwolski, J., Bień, J., Modal analysis of bridge structures by means of Forced Vibration Tests (2011) Journal of Civil Engineering and Management, 17 (4), pp. 590-599; Helmerich, R., Niederleithinger, E., Trela, Ch., Bień, J., Bernardini, G., Multi-tool inspection and numerical analysis of an old masonry arch bridge (2012) Structure and Infrastructure Engineering, 8 (1), pp. 27-39; Middleton, C., Fidler, P.R.A., Vardanega, P.J., (2016) Bridge Monitoring: A Practical Guide, , Eds., ICE Publishing; Bagge, N., Popescu, C., Elfgren, L., Failure tests on concrete bridges: Have we learnt the lesson? (2018) Structure and Infrastructure Engineering, 14 (3), pp. 292-319; Lantsoght, E.L.O., Load Testing of Bridges: Current Practice and Diagnostic Load Testing (2019) Load Testing of Bridges; Proof Load Testing and the Future of Load Testing”, vol. 13. Series: Structures and Infrastructure, 12, pp. 299-376. , Ed., Dan M. Frangopol, Ed. London/Leiden: Taylor and Francis Group, CRC Press, ISBN 978-0-367-21082-3; 978-0-367-21083-0; Maksymowicz, M., Cruz, P., Bień, J., Load capacity of damaged RC slab spans of railway bridges (2011) Archives of Civil and Mechanical Engineering, 11 (4), pp. 963-978; Zwolski, J., Bień, J., Kamiński, T., Kużawa, M., Rawa, P., Experimental vibration analysis of concrete box bridge girders (2013) Proc. 5th International Conference on Experimental Vibration Analysis for Civil Engineering Structures EVACES 2013, pp. 193-200. , Ouro Preto, Brazil; Bień, J., Kamiński, T., Kużawa, M., Validation of numerical models of concrete box bridges based on load test results (2015) Archives of Civil and Mechanical Engineering, 15 (4), pp. 1046-1060; Kużawa, M., Kamiński, T., Bień, J., Fatigue assessment procedure for old riveted road bridges (2018) Archives of Civil and Mechanical Engineering, 18 (4), pp. 1259-1274; Kamiński, T., Kużawa, M., Bień, J., Experimental and numerical assessment of an old backfilled concrete arch bridge (2020) Proc. 9th International Conference on Arch Bridges, Structural Integrity, 11, pp. 194-202. , Springer; Bień, J., Kużawa, M., Gładysz-Bień, M., Kamiński, T., Quality control of road bridges in Poland (2016) Proc. 8th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2016, pp. 971-978. , Foz do Iguaçu, Brasil; Zadeh, L.A., Fuzzy sets and information granularity (1979) Advances in Fuzzy Set Theory and Applications, pp. 3-18. , M. Gupta, R. Ragade, R. Yage, Eds. Amsterdam: North-Holland Publ; Sasmal, S., Ramanjaneyulu, K., Condition evaluation of existing reinforced concrete bridges using fuzzy based analytic hierarchy approach (2008) Expert Systems with Applications, 35 (3), pp. 1430-1443; Li, Z., Burgueño, R., Using soft computing to analyze inspection results for bridge evaluation and management (2010) Journal of Bridge Engineering, 15 (4), pp. 430-439; Kużawa, M., Bień, J., Gładysz-Bień, M., Hybrid knowledge expert tool for load capacity assessment of railway plate girders with defects (2013) Proc. 11th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2013), pp. 1294-1297. , American Institute of Physics, Rhodes; Daniotti, B., (2020) Digital Transformation of the Design, Construction and Management Processes of the Built Environment, , Eds., Springer International Publishing; Baumgartner, S., El-Mahrouk, O., Kop, M., Vill, M., The development of a BIM data structure for bridge maintenance (2021) IABSE Congress Ghent 2021 – Structural Engineering for Future Societal Needs, pp. 949-954. , IABSE Zürich; Saback de Freitas Bello, V., Popescu, C., Blanksvärd, Th., Täljsten, B., Bridge management systems: Overview and framework for smart management (2021) IABSE Congress Ghent 2021 – Structural Engineering for Future Societal Needs, pp. 1014-1022. , IABSE Zürich; Abdullah, A., Thai, O.B., Personal digital assistants as a mobile inspection system at construction site (2006) Proc. of the 6th Asia-Pacific Structural Engineering and Construction Conference (APSEC 2006), pp. D28-D38. , 5-6 September Kuala Lumpur, Malaysia, 2006; Bień, J., Rawa, P., Hybrid Knowledge Representation in BMS (2004) Archives of Civil and Mechanical Engineering, 4 (1), pp. 41-55; Carlson, W., (2013) A Critical History of Computer Graphics and Animation, , Ohio State University; Golparvar-Fard, M., D4AR. 4-Dimensional Augmented Reality (2012) LiDAR Magazine, 2, pp. 11-15; Gołaszewska, M., Salamak, M., Challenges in takeoffs and cost estimating in the BIM technology, based on the example of a road bridge model (2017) Technical Transactions Civil Engineering, 4, pp. 71-79; Hu, Y., Hammad, A., Location-based Mobile Bridge Inspection Support System (2005) Proc. of the 1st CSCE Specialty Conference on Infrastructure Technologies, , Ontario, FR130.1–FR130.10; Januszka, M., Moczulski, W., Acquisition and Knowledge Representation in the Product Development Process with the Use of Augmented Reality (2013) Proc. of the Concurrent Engineering Approaches for Sustainable Product Development in a Multi-Disciplinary Environment, pp. 315-326. , J. Stjepandic, et al., Eds. London: Springer-Verlag; Jasiński, M., Płaszczyk, T., Salamak, M., Visual programming and BIM technology in parametric concrete bridgedesign (2017) Proc.12thCentralEuropeanCongressonConcreteEngineeringCCC2017, pp. 130-138. , Tokaj,Hungary; Milgram, P., Takemura, H., Utsumi, A., Kishino, F., Augmented Reality: A class of displays on the realityvirtuality continuum (1994) Proc. of SPIE - The International Society for Optical Engineering, 2351; Salamak, M., Januszka, M., BIM models and augmented reality for concrete bridge inspections (2015) Proc. 11th Central European Congress on Concrete Engineering CCC 2015, pp. 25-28. , Hainburg",,,,"Polska Akademia Nauk",,,,,12302945,,ACIEE,,"English","Arch Civ Eng",Review,"Final","",Scopus,2-s2.0-85133529116
"Saju S.","57715573800;","Smart Bridges Based on Bridge Information Modelling",2022,"SPICES 2022 - IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems",,,,"279","284",,,"10.1109/SPICES52834.2022.9774179","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130927274&doi=10.1109%2fSPICES52834.2022.9774179&partnerID=40&md5=2838482df3283ad166f81588b44ed91d","Bridges Design Unit, Chief Design Office, Kerala Public Works Department, Trivandrum, India","Saju, S., Bridges Design Unit, Chief Design Office, Kerala Public Works Department, Trivandrum, India","Bridge structures are considered to be the very vulnerable part of civil transportation system that affect directly the public safety and economy. The maintenance of these bridges is many times disregarded in developing counties like India due to lack of maintenance fund, scarcity of experts to rectify problems and so many other reasons. Structural Health Monitoring (SHM) is a method for the diagnosis of damage based on periodically collected data from sensors placed on the structure that lead to characterize the damage and to maintain the health status of the structure. Sufficient expert knowledge is essential for an adequate solution of SHM tasks and Artificial Intelligence (AI) is now being focused on this tasks. Bridge Information Modelling (BrIM) is another digital application in bridge construction industry, which stores and updates the data beyond the design process, enabling engineers with relevant information to carryout fabrication, construction, and maintenance. In this paper a conceptual strategy to integrate the three digital techniques, SHM, AI and BrIM for developing smart bridges for smart cities is proposed. © 2022 IEEE.","AI; BIM; BrIM; SHM; Smart bridges","Architectural design; Bridges; Construction industry; Maintenance; Structural health monitoring; BIM; Bridge information modeling; Bridge structures; Civil transportation; Health status; Information Modeling; Maintenance funds; Public safety; Smart bridge; Transportation system; Information theory",,,,,,,,"Yan, R., Chen, X., Mukhopadhyay, S.C., (2017) Structural Health Monitoring, , Springer, Berlin, Germany; Garrett, J.H., Use of neural networks in detection of structural damage (1992) Computers and Structures, 42 (4). , Elsevier, Burlington, MA, USA; Bartholomew, M., Blasan, B., Koc, A., Bridge Information Modelling (BrIM) using Open Parametric Objects (2015) Report no. FHWA-HIF-16-010, Federal Highway Administration; Reitsema, A., Hordijk, D., Towards a SMART Bridge: A Bridge with Self-Monitoring, Analysing, and-Reporting Technologies (2015) Proceedings of the SMAR 2015: Third Conference on Smart Monitoring, Assessment & Rehabilitation of Civil Structures, pp. 16-19. , Antalya, Turkey October; Rizzo, P., Enshaeian, A., Bridge Health Monitoring in the United States: A Review (2021) Struct. Monit. Maint. Int. J., 8, pp. 1-50. , 2021; Catbas, F.N., Gul, M., Burkett, J.L., Damage assessment using flexibility and flexibility-based curvature for structural health monitoring (2007) SmartMater. Struct; Bazant, Z., Baweja, S., Short form of creep and shrink-age prediction model B3 for structures of medium sensitivity (1996) Mater. Struct, p. 587593; Zolghadri, N., Hailing, M.W., Barr, P.J., Foust, N., (2015) Effects of Temperature on Bridge Dynamic Properties, , Utah State University, Logan, UT, USA, Report no. CAIT-UTC-050; Li, Z.X., Chan, T.H.T., Ko, J.M., Fatigue analysis and life prediction of bridges with structural health monitoring data-Part I: Methodology and strategy (2001) Int. Journal of Fatigue, 23, pp. 45-53; Morris, W., Vico, A., Vazquez, M., De Sanchez, S., Corrosion of reinforcing steel evaluated by means of concrete resistivity measurements (2002) Corros. Set, 44, pp. 81-99; Hunt, B.E., Monitoring Scour Critical Bridges (2009) National Academies of Sciences, Engineering, andMedicine, , Washington, DC, 7X4; El-Tawil, S., Severino, E., Fonseca, P., Vehicle Collision with Bridge Piers (2005) Journal of Bridge Engineering, 10, pp. 345-353; Gonzalez, M.P., Zapico, J.L., Seismic damage identification in buildings using neural networks and modal data (2008) Comput. Struct, 86, pp. 416-426; Comisua, C., Taranub, N., Boacaa, G., Scutaru, M., Structural health monitoring system of bridges (2017) X International Conference on Structural Dynamics, EURODYN 201, , Elsevier, ProcediaEngineering","Saju, S.; Bridges Design Unit, India; email: sajus99@gmail.com",,"Mar Baselios College of Engineering and Technology - Autonomous (MBCETAA)","Institute of Electrical and Electronics Engineers Inc.","2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2022","10 March 2022 through 12 March 2022",,179344,,9781665449403,,,"English","SPICES - IEEE Int. Conf. Signal Process., Informatics, Commun. Energy Syst.",Conference Paper,"Final","",Scopus,2-s2.0-85130927274
"Polania D.R., Tondolo F., Osello A., Fonsati A., De Gaetani C., Trincianti C., Gazulli D.","57388547900;23668913100;55247387300;57203287238;55347405100;57304290000;57388305000;","Digitalization Processes and Bridge Information Modeling for Existing Bridges",2022,"Lecture Notes in Civil Engineering","200 LNCE",,,"944","953",,,"10.1007/978-3-030-91877-4_108","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121915314&doi=10.1007%2f978-3-030-91877-4_108&partnerID=40&md5=27c680062e66337cd68af0dd4bb86ebc","Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy; S.C.R. Piemonte S.p.A., Corso Guglielmo Marconi 10, Turin, 10125, Italy; Lombardi Ingegneria S.r.l., Via Raimondo Montecuccoli 9, Turin, 10121, Italy","Polania, D.R., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Tondolo, F., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Osello, A., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Fonsati, A., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; De Gaetani, C., Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy; Trincianti, C., S.C.R. Piemonte S.p.A., Corso Guglielmo Marconi 10, Turin, 10125, Italy; Gazulli, D., Lombardi Ingegneria S.r.l., Via Raimondo Montecuccoli 9, Turin, 10121, Italy","Bridges constant assessment, monitoring and retrofitting are key aspects to prevent inadequate damage situations. Considering the importance of these processes, a new official guideline for Bridge evaluation, classification and monitoring has been issued in Italy. The usage of BIM methodology comes as a logical solution to store and manage all information related to the bridge surveillance process and create a unique database. In the present work, HBIM methodologies are implemented for the creation of a damage database and new approaches are tested for the application of the guidelines directly on the BIM environment. Using the dismantled structures of Largo Grosseto bridge as a case study and damage information previously recovered as input data, HBIM models are created using two different methodologies: Parametric modelling and Mesh-to-BIM process. Moreover, the utility of the database created is expanded thanks to the usage of visual programming tools. The evaluation of the modelling processes highlights the effectiveness of BIM for infrastructure monitoring and classification. The results obtained demonstrate the way towards a new BIM monitoring standard procedure for infrastructure surveillance processes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.","Bridge inspection; HBIM; Structural Health Monitoring","Architectural design; Computer programming; Database systems; Structural health monitoring; Bridge evaluation; Bridge inspection; Bridge monitoring; Case-studies; Database approaches; Existing bridge; HBIM; Information Modeling; Logical solution; New approaches; Damage detection",,,,,"Allegheny Technologies Incorporated, ATI; Politecnico di Torino, POLITO; Politecnico di Milano; Regione Piemonte","BRIDGE|50 is a research project based on a research agreement among universities, public authorities, and private companies. Members of the Management Committee: S.C.R. Piemonte (President); Politecnico di Milano (Scientific Coordinator); Politecnico di Torino (Scientific Responsible of the Experimental Activities); Lombardi Engineering (Secretary); Piedmont Region; City of Turin; Metropolitan City of Turin; TNE Torino Nuova Economia; ATI Itinera & C.M.B.; ATI Despe & Perino Piero; Quaranta Group. BRIDGE|50 website: http://www. bridge50.org.",,"Song, G., Wang, C., Wang, B., Structural Health Monitoring (SHM) of civil structures (2017) Appl Sci, 7, p. 789. , https://doi.org/10.3390/app7080789; Lynch, J., Loh, K., A summary review of wireless sensors and sensor networks for structural health monitoring (2006) Shock Vib Dig, 38, pp. 91-128; (2020) Linee Guida per La Classificazione E Gestione Del Rischio, , la Valutazione della Sicurezza ed il Monitoraggio dei Ponti Esistenti, Rome, Italy; Shim, C., Yun, N., Song, H., Application of 3D bridge information modelling to design and construction of bridges (2011) Procedia Eng, 14, pp. 95-99; Yang, X., Yi-Chou, L., Murtiyoso, A., Koehl, M., Grussenmeyer, P., HBIM modeling from the surface mesh and its extended capability of knowledge representation (2019) ISPRS Int J Geo-Informat, 8 (7), p. 301. , https://doi.org/10.3390/ijgi8070301; Pocobelli, D.P., Boehm, J., Bryan, P., Still, J., Grau-Bové, J., Building information models for monitoring and simulation data in heritage buildings (2018) Int Archiv Photogrammet Remote Sens Spatial Inf Sci XLII, 2, pp. 909-916. , https://doi.org/10.5194/isprs-archives-XLII-2-909-2018; Simeone, D., Cursi, S., Toldo, I., Carrara, G., (2014) B(H)Im-Built Heritage Information Modelling; Rocha, G., Mateus, L., Fernández, J., Ferreira, V., A scan-to-BIM methodology applied to heritage buildings (2020) Heritage, 3, pp. 47-67. , https://doi.org/10.3390/heritage301000; Sun, Z., Zhang, Y., Using drones and 3D modelling to survey Tibetan architectural heritage: A case study with the multi-door stupa (2018) Sustainability, 10, p. 2259; Barazzetti, L., Banfi, F., Brumana, R., Previtali, M., Creation of parametric BIM objects from point clouds using nurbs (2015) Photogram Rec, 30, pp. 339-362; Santagati, C., Turco, M., Garozzo, R., Reverse information modelling for historic artefacts: Towards the definition of a level of accuracy for ruined heritage (2018) ISPRS – Int Archiv Photogrammet Remote Sens Spatial Inf Sci, 42-2, pp. 1007-1014; Yang, X., Koehl, M., Grussenmeyer, P., Mesh-To-BIM: From segmented mesh elements to BIM model with limited parameters (2018) ISPRS – Int Archiv Photogrammet Remote Sens Spatial Inf Sci, 42-2, pp. 1213-1218. , https://doi.org/10.5194/isprs-archives-XLII-2-1213-2018; Keviczky, L., Bars, R., Hetthéssy, J., Bányász, C., (2019) Case Study. Control Engineering: MAT-LAB Exercises. ATCSP, pp. 265-274. , https://doi.org/10.1007/978-981-10-8321-1_16, Springer, Singapore, pp; Boddupalli, C., Sadhu, A., Azar, E., Pattyson, S., Improved visualization of infrastructure monitoring data using building information modelling (2019) Struct Infrastruct Eng, 15, pp. 1-17. , https://doi.org/10.1080/15732479.2019.1602150; Barazzetti, L., Cloud-to-BIM-to-FEM: Structural simulation with accurate historic BIM from laser scans (2015) Simulat Model Pract Theory, 57, pp. 71-87. , https://doi.org/10.1016/j.simpat.2015.06.004; Zhao, Z., Integrating BIM and IoT for smart bridge management (2019) IOP Conf Ser Earth Environ Sci, 371. , https://doi.org/10.1088/1755-1315/371/2/022034; Biondini, F., BRIDGE|50 research project: Residual structural performance of a 50-year-old bridge (2021) Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020), 28 June–2 July 2020 (Postponed to 11–15 April, p. 2021. , Yokota H, Frangopol DM, Sapporo, Japan. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations. London: CRC Press, Taylor & Francis Group","Tondolo, F.; Politecnico di Torino, Corso Duca degli Abruzzi 24, Italy; email: D058687@polito.it","Pellegrino C.Faleschini F.Zanini M.A.Matos J.C.Casas J.R.Strauss A.",,"Springer Science and Business Media Deutschland GmbH","1st Conference of the European Association on Quality Control of Bridges and Structures, EUROSTRUCT 2021","29 August 2021 through 1 September 2021",,269849,23662557,9783030918767,,,"English","Lect. Notes Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85121915314
"Xenidis Y.","8520901800;","Building Information Modeling for Bridge Design and Construction",2022,"Lecture Notes in Civil Engineering","200 LNCE",,,"777","784",,,"10.1007/978-3-030-91877-4_88","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121915026&doi=10.1007%2f978-3-030-91877-4_88&partnerID=40&md5=a87d8a002291375a29412995629f891d","Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece","Xenidis, Y., Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece","Building Information Modeling (BIM) is increasingly expanding its application from the building sector to other types of structures, such as roads, rail and bridges. Especially for bridges that require explicit structural analysis and standard construction processes BIM can be a cornerstone of cost-effective and safe delivery exploiting the consolidation of a point by point geometric model and the potential of coordinating technical and temporal information during construction. Therefore, the potential of BIM technology for bridge design and analysis needs to be presented in a plain manner to foster a broader implementation for this type of infrastructure. This paper contributes to this goal by presenting an informed update on the application of BIM for bridge design and construction. More specifically, it reviews recent academic publications to investigate the extent of the respective research field, and it highlights respective critical issues. More importantly, it sheds light on the Industry Foundation Classes (IFC) protocol uses for Bridge Information Modeling (BrIM) by providing details for the development, current limitations, and future needs with respect to them. The conclusions from this review aim at allowing the provision of a clear understanding of the current state-of-the-art, a clear identification of the obstacles for a wider application, and a full description of the potential and challenges for the introduction of BIM technology to bridge design and construction. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.","BIM; Bridge; BrIM; IFC; Infrastructure","Architectural design; Bridges; Construction; Cost effectiveness; Structural design; Bridge constructions; Bridge design; Bridge information modeling; Building Information Modelling; Design and construction; Industry foundation class; Information Modeling; Infrastructure; ITS applications; Modeling technology; Information theory",,,,,,,,"DODGE Data & Analytics: The business value of BIM for Infrastructure 2017 Smart Market Report. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/finance/us-fas-bim-infrastructure.pdf. Accessed 14 May 2021; Costin, A., Adibfar, A., Hu, H., Chen, S.S., Building Information Modeling (BIM) for transportation infrastructure – Literature review, applications, challenges, and recommendations (2018) Autom Constr, 94, pp. 257-281; Bradley, A., Li, H., Lark, R., Dunn, S., BIM for infrastructure: An overall review and constructor perspective (2016) Autom Constr, 71 (2), pp. 139-152; Lu, R., Ioannis Brilakis, I., Digital twinning of existing reinforced concrete bridges from labelled point clusters (2019) Autom Constr, 105; Cheng, J.C.P., Lu, Q., Deng, Y., Analytical review and evaluation of civil information modeling (2016) Autom Constr, 67, pp. 31-47; Minehane, M., Ruane, K., O’Keeffe, B., O’Sullivan, G., McKenna, T., Developing an ‘as-is’ bridge information model (BrIM) for a heritage listed viaduct (2005) CITA BIM Gathering Conference 2015, pp. 181-188. , Hore A, McAuley B, West R, pp, The Construction IT Alliance; Prendergast, L.J., Gavin, K., A review of bridge scour monitoring techniques (2014) J Rock Mech Geotech Eng, 6 (2), pp. 138-149; Shim, C.-S., Lee, K.-M., Kang, L.S., Hwang, J., Kim, Y., Three-dimensional information model-based bridge engineering in Korea (2012) Struct Eng Int, 22 (1), pp. 8-13; Zhou, C.H., Wang, W., Highway bridge construction process simulation base on 4D visualization (2009) Geohunan International Conference Proceedings, pp. 138-145. , pp, ASCE, Changsha, Hunan; Lee, K.M., Lee, Y.B., Shim, C.S., Park, K.L., Bridge information models for construction of a concrete box-girder bridge (2012) Struct Infrastruct Eng, 8 (7), pp. 687-703; Marzouk, M., Hisham, M., Ismail, S., Youssef, M., Seif, O., On the use of building information modeling in infrastructure bridges (2010) 27Th International Conference Applications of IT in the AEC Industry (CIB W78), pp. 1-10. , pp, Cairo; Fanning, B., Clevenger, C.M., Ozbek, M.E., Mahmoud, H., Implementing BIM on infrastructure: Comparison of two bridge construction projects (2014) Pract Period Struct Des Constr, 20 (4), pp. 1-8; Catbas, F.N., Susoy, M., Frangopol, D.M., Structural health monitoring and reliability estimation: Long span truss bridge application with environmental monitoring data (2008) Eng Struct, 30 (9), pp. 2347-2359; Jeong, S., Zhang, Y., O’Connor, S., Lynch, J.P., Sohn, H., Law, K.H., A NoSQL data management infrastructure for bridge monitoring (2016) Smart Struct Syst, 17 (4), pp. 669-690; Isailović, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R., Döllner, J., Bridge damage: Detection, IFC-based semantic enrichment and visualization (2020) Autom Constr, 112; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., An information modeling framework for bridge monitoring (2017) Adv Eng Softw, 114, pp. 11-31; Mirzaei, Z., Adey, B.T., Klatter, L., Thompson, P., (2014) The IABMAS Bridge Management Committee Overview of Existing Bridge Management Systems. In: International Association for Bridge Maintenance and Safety (IABMAS), p. 2014. , Rijkswaterstaat, The Netherlands; Grolinger, K., Higashino, W.A., Tiwari, A., Capretz, M.A.M., Data management in cloud environments: NoSQL and NewSQL data stores (2013) J Cloud Comput Adv Syst Appl, 2 (1), pp. 1-24. , https://doi.org/10.1186/2192-113X-2-22; Sacks, R., SeeBridge as next generation bridge inspection: Overview, information delivery manual and model view definition (2018) Autom Constr, 90, pp. 134-145; Chen, S.S., Shirolé, A.M., Integration of information and automation technologies in bridge engineering and management: Extending the state of the art (2006) J Transp Res Board, 1976 (1), pp. 2-12; Costin, A., A new methodology for interoperability of heterogeneous bridge information models, PhD Dissertation (2016) School of Civil & Environmental Engineering, , Georgia Institute of Technology, Atlanta, GA; Girardet, A., Boton, C., A parametric BIM approach to foster bridge project design and analysis (2021) Autom Constr, 126","Xenidis, Y.; Aristotle University of ThessalonikiGreece; email: ioxen@civil.auth.gr","Pellegrino C.Faleschini F.Zanini M.A.Matos J.C.Casas J.R.Strauss A.",,"Springer Science and Business Media Deutschland GmbH","1st Conference of the European Association on Quality Control of Bridges and Structures, EUROSTRUCT 2021","29 August 2021 through 1 September 2021",,269849,23662557,9783030918767,,,"English","Lect. Notes Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85121915026
"Akanbi T., Zhang J.","57194700443;55358453700;","Framework for Developing IFC-Based 3D Documentation from 2D Bridge Drawings",2022,"Journal of Computing in Civil Engineering","36","1","04021031","","",,,"10.1061/(ASCE)CP.1943-5487.0000986","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116518186&doi=10.1061%2f%28ASCE%29CP.1943-5487.0000986&partnerID=40&md5=c50dc1b4b1d742db06d8b359af2eb4ca","Automation and Intelligent Construction Lab (AutoIC), School of Construction Management Technology, Purdue Univ., West Lafayette, IN  47907, United States","Akanbi, T., Automation and Intelligent Construction Lab (AutoIC), School of Construction Management Technology, Purdue Univ., West Lafayette, IN  47907, United States; Zhang, J., Automation and Intelligent Construction Lab (AutoIC), School of Construction Management Technology, Purdue Univ., West Lafayette, IN  47907, United States","Building information modeling (BIM) has been widely accepted in the industry and extensively used in supporting many construction tasks. In the government sector, the USDOT Federal Highway Administration (FHWA) has implemented building information modeling (BIM) for bridge construction. Hence, state DOTs are now faced with heightened pressure in complying with the FHWA's Bridge Information Modeling (BrIM) standardization. Although BIM can provide many benefits to DOTs, current BIM-based platforms for bridges are not fully developed to process traditional two-dimensional (2D) bridge drawings for BIM-based computational tasks involving existing bridges, for example cost estimation. Bridges are a critical infrastructure in any nation's economy, and by law the DOTs are tasked with ensuring that they remain safe for use. To maintain bridges, engineers currently perform periodic inspections, assessing each part of the bridge to identify areas that require maintenance. Maintenance work items are then generated for these areas; these are usually computed traditionally or by systems that still rely heavily on manual inputs. Such processes are time-consuming and cumbersome, and depend on years of bridge technical expertise. To overcome these limitations and improve the accuracy of processes such as generating maintenance work items for bridges, we propose a framework for automatically (1) processing existing 2D bridge drawings for bridges built pre-BIM adoption in the architecture, engineering, and construction (AEC) industry; (2) converting these record drawings into three-dimensional (3D) information models; and (3) converting 3D information models into industry foundation class (IFC) files. The developed 3D models using the proposed framework were compared against developed 3D models using the state-of-the-art method. Experimental results show that the developed framework can be used in developing algorithms that generate 3D models and IFC output files from portable document format (PDF) bridge drawings in a semiautomated fashion. The proposed method uses 3.33% of the time it takes the current state-of-the-art method to generate a 3D model, and the generated models are of comparative quality. © 2021 American Society of Civil Engineers.","Automation; Bridge construction; Bridge information modeling (BrIM); Building information modeling (BIM); Industry foundation classes","3D modeling; Architectural design; Bridges; Construction; Construction industry; Cost estimating; Highway administration; Highway planning; Maintenance; Three dimensional computer graphics; 'current; 3D models; 3d-modeling; Bridge constructions; Bridge information modeling; Building information modeling; Building Information Modelling; Industry foundation class; Information Modeling; Model-based OPC; Information theory",,,,,"National Science Foundation, NSF: 1937115","The authors would like to thank the National Science Foundation (NSF). This material is based on work supported by the NSF under Grant No. 1937115. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. The authors would like to thank the Bridge Design Office of the Indiana Department of Transportation for providing bridge plans.",,"(2019) Adoption of Industry Foundation Classes (IFC) Schema As the Standard Data Schema for the Exchange of Electronic Engineering Data, , https://highways.transportation.org/wp-content/uploads/sites/46/2019/10/Administrative-Resolution-AR-1-19-Adoption-of-Industry-Foundation-Classes-IFC-Schema-as-the-Standard-Data-Schema-for-the-Exchange-of-Electronic-Engineering-Data.pdf, AASHTO. "" "" Accessed March 29, 2021; Alshabab, M., Vysotskly, A.E., Khalil, T., Petrochenko, M.V., BIM-based quantity takeoff (2017) Constr. Unique Build. Struct., 55 (2017), pp. 124-134; (2020) What Is the Difference between, , https://asiapacific.anu.edu.au/mapsonline/faq/what-difference-between-png-file-raster-image-and-svg-file-vector-image, Australian National University. "" "" Accessed October 31, 2020; Bae, A., Lee, D., Park, B., Building information modeling utilization for optimizing milling quantity and hot mix asphalt pavement overlay quality (2016) Can. J. Civ. Eng., 43 (10), pp. 886-896. , https://doi.org/10.1139/cjce-2015-0001; Benning, P., Publics, B., France, G., IFC for infrastructure: New concepts and entities for bridges (2017) Int. J. 3-D Inf. Model., 6 (3), pp. 44-56. , https://doi.org/10.4018/IJ3DIM.2017070104; Borrmann, A., Muhic, S., Hyvarinen, J., Chipman, T., Jaud, S., Castaing, C., Dumoulin, C., Mol, L., (2019) The IFC-bridge Project - Extending the IFC Standard to Enable High-quality Exchange of Bridge Information Models, pp. 377-386. , Proc. European Conference on Computing in Construction, Paris: European Conference on Computing in Construction; Bradley, A., Li, H., Lark, R., Dunn, S., BIM for infrastructure: An overall review and constructor perspective (2016) Autom. Constr., 71 (2016), pp. 139-152. , https://doi.org/10.1016/j.autcon.2016.08.019; Brownlee, J., (2019) A Gentle Introduction to Generative Adversarial Networks (GANs), , https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans/, Accessed September 1, 2020; (2020) View and Convert 3D CAD Files, , https://cadexchanger.com/IFC/IFC-to-step/, CAD Exchanger. "" "" Accessed October 5, 2020; Cheng, J., Lu, Q., Deng, Y., Analytical review and evaluation of civil information modeling (2016) Autom. Constr., 67 (2016), pp. 31-47. , https://doi.org/10.1016/j.autcon.2016.02.006; Fanning, B., Clevenger, C., Ozbek, M., Mahmoud, H., Implementing BIM on Infrastructure: Comparison of two bridge construction projects (2015) Pract. Period. Struct. Des. Constr., 9 (2015), pp. 376-384; Franco, J., Mahdi, F., Abaza, H., Using building information modeling (BIM) for estimating and scheduling, adopting barriers (2015) Universal J. Manage., 3 (9), pp. 376-384. , https://doi.org/10.13189/ujm.2015.030905; Furferi, R., Governi, L., Palai, M., Volpe, Y., From 2D orthographic views to 3D pseudo-wireframe: An automatic procedure (2010) Int. J. Comput. Appl., 5 (6), pp. 18-24. , https://doi.org/10.5120/918-1296; Girdhar, R., Fouhey, D., Rodriguez, M., Gupta, A., (2016) Learning A Predictable and Generative Vector Representation for Objects, pp. 484-499. , Proc. European Conference on Computer Vision, Paris: European Conference on Computer Vision; Huthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC bridge defect information into BIM models (2018) J. Comput. Civ. Eng., 2018 (3), p. 32; Isailovic, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R., Bridge damage: Detection, IFC-based semantic enrichment and visualization (2020) Autom. Constr., 112 (2020), p. 103088; (2018) Industry Foundation Classes (IFC) for Data Sharing in the Construction and Facility Management Industries - Part 1: Data Schema, , ISO (International Organization for Standardization). ISO 16739-1: 2018. London: ISO; Ji, Y., Borrmann, A., Beetz, J., Obergrieber, M., Analytical review and evaluation of civil information modeling (2013) J. Comput. Civ. Eng., 27 (6), pp. 593-606. , https://doi.org/10.1061/(ASCE)CP.1943-5487.0000286; Kim, J.-U., Kim, Y.-J., Ok, H., Yang, S.-H., (2015) A Study on the Status of Infrastructure BIM and BIM Library Development, pp. 857-858. , Proc. Int. Conf. on Computational Science and Computational Intelligence (CSCI), Las Vegas: Computational Science and Computational Intelligenc; Kumar, B., Cai, H., Hastak, M., (2017) An Assessment of Benefits of Using BIM on An Infrastructure Project, pp. 88-95. , Proc. Int. Conf. on Sustainable Infrastructure, Reston, VA: ASCE; Lau, S., Zakaria, R., Aminudin, E., Saar, C., Yusof, A., Wahid, C., A review of application building information modeling (BIM) during pre-construction stage: Retrospective and future directions (2018) IOP Conf. Ser.: Earth Environ. Sci., 143 (1), p. 012050; Lu, W., Peng, Y., Shen, Q., Li, H., Generic model for measuring benefits of BIM as a learning tool in construction tasks (2013) J. Civ. Eng. Manage., 139 (2), pp. 195-203. , https://doi.org/10.1061/(ASCE)CO.1943-7862.0000585; (2020) Vector, Raster, JPG, EPS, PNG - What's the Difference?, , https://modassicmarketing.com/understanding-image-file-types, MODassic. """" Accessed October 31, 2020; Park, S., Lee, S.-H., Almasi, A., Song, J.-H., Extended IFC-based strong form meshfree collocation analysis of a bridge structure (2020) Autom. Constr., 119 (2020), p. 103364. , https://doi.org/10.1016/j.autcon.2020.103364","Zhang, J.; Automation and Intelligent Construction Lab (AutoIC), United States; email: zhan3062@purdue.edu",,,"American Society of Civil Engineers (ASCE)",,,,,08873801,,JCCEE,,"English","J. Comput. Civ. Eng.",Article,"Final","",Scopus,2-s2.0-85116518186
"Adibfar A., Costin A.M.","57202945239;55200193500;","Integrated Management of Bridge Infrastructure through Bridge Digital Twins: A Preliminary Case Study",2021,"Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021",,,,"358","365",,,"10.1061/9780784483893.045","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132577008&doi=10.1061%2f9780784483893.045&partnerID=40&md5=37e887b659fe6376b9c53b1ddb77ea56","M.E. Rinker, Sr. School of Construction Management, Univ. of Florida, United States","Adibfar, A., M.E. Rinker, Sr. School of Construction Management, Univ. of Florida, United States; Costin, A.M., M.E. Rinker, Sr. School of Construction Management, Univ. of Florida, United States","Data play a significant role in the life cycle management of road infrastructure and bridges, and their integration is a crucial element of smart infrastructure systems. However, the current practice of managing infrastructure involves the use of an abundance of data produced by a variety of non-interoperable information systems. Thus, the lack of interoperability creates major challenges in deployment of a fully integrated and smart management system for the infrastructure. This research focuses on the development of a digital twin that could be used as an umbrella for integrating the live load traffic data on bridges with other bridge life cycle data to mirror the bridge behavior and offer a smart and integrated bridge management system. Intelligent transportation systems (ITS) are remarkable instances of advanced technology that reduced the human role in the operation and management of transportation infrastructure. Weigh-in-motion (WIM) is a type of ITS system provides a stream of valuable data about weight and other dynamic attributes of the fleeting traffic over road network and bridges. In this research, the real-time WIM data are integrated into a BrIM model by visual scripting to form the digital twin of the bridge. Through this approach, weight sensor data could be streamed in the digital twin of bridge, and the level of data utilization by different stakeholders can be improved. The outcomes of this study will help the preservation and sustainability of bridges and helping their resiliency through pro-active planning and enhancing the utilization of the available data. © 2021 Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021. All rights reserved.",,"Bridges; Data integration; Highway administration; Highway planning; Information management; Intelligent vehicle highway systems; Interoperability; Life cycle; Roads and streets; Bridge infrastructure; Case-studies; Current practices; Infrastructure systems; Integrated management; Intelligent transportation systems; Lifecycle management; Road bridge; Road infrastructures; Smart infrastructures; Intelligent systems",,,,,,,,"(2021) Report Card for America's Infrastructure, , https://infrastructurereportcard.org/, ASCE. (Apr. 12, 2021); (2020) Report card for West Virginia's Infrastructure, , https://www.infrastructurereportcard.org/wp-content/uploads/2020/12/WV-2020-Infrastructure-Report-Card-1.pdf, ASCE. (Dec. 10, 2020); Adibfar, A., Costin, A., Next Generation of Transportation Infrastructure Management: Fusion of Intelligent Transportation Systems (ITS) and Bridge Information Modeling (BrIM) (2019) Advances in informatics and computing in civil and construction engineering, pp. 43-50; Adibfar, A., Costin, A., Evaluation of IFC for the Augmentation of Intelligent Transportation Systems (ITS) into Bridge Information Models (BrIM) (2019) Proceedings of ASCE international conference on computing in civil engineering, , June 17-19, Atlanta, Georgia; Costin, A., Adibfar, A., Hu, H., Chen, S., Building Information Modeling (BIM) for Transportation Infrastructure-Literature Review, Applications, and Challenges (2018) Automation in Construction, 94, pp. 257-281; Dygalo, V., Keller, A., Shcherbin, A., Principles of application of virtual and physical simulation technology in production of digital twin of active vehicle safety systems (2020) Transportation Research Procedia, 50, pp. 121-129; (2019) The FAST Act, , https://www.fhwa.dot.gov/fastact/, FHWA. (Dec. 09, 2020); Glaessgen, E.H., Stargel, D.S., The digital twin paradigm for future NASA and U.S. Airforce vehicles (2012) 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Special Session on the Digital Twin, , https://doi.org/10.2514/6.2012-1818, April 23-26, Honolulu, Hawaii; Hofmann, W., Branding, F., Implementation of an IoT and Cloud-based Digital Twin for real-time decision support in port operations (2019) IFAC PapersOnline, 53 (13). , Elsevier; Kritzinger, W., Karner, M., Traar, G., Henjes, J., Sihn, W., Digital Twin in manufacturing: A categorical literature review and classification (2018) IFAC-PapersOnLine, 51 (11), pp. 1016-1022; Lu, R., Brilakis, I., Digital twining of existing reinforced concrete bridges from labelled point clusters (2019) Automation in Construction, 105, p. 102837. , https://doi.org/10.1016/j.autcon.2019.102837; McLoud, D., Construction groups seek more transportation funding as shutdown looms (2020) Equipment World's Better Roads, , https://tinyurl.com/y3qn4gvh, Dec. 09, 2020; Mi, S., Feng, Y., Zheng, H., Wang, Y., Gao, Y., Tan, J., Prediction maintenance integrated decision-making approach supported by digital twin-driven cooperative awareness and interconnection framework (2021) Journal of Manufacturing Systems, 58, pp. 329-345. , https://doi.org/10.1016/j.jmsy.2020.08.001; Shirowzhan, S., Tan, W., Sepasgozar, S., Digital twin and CyberGIS for improving connectivity and measuring the impact of infrastructure construction planning in smart cities (2020) International Journal of Geo-Information, 9 (4), p. 240. , https://doi.org/10.3390/ijgi9040240; Sofia, H., Anas, E., Faiz, O., Mobile Mapping, Machine Learning and Digital Twin for Road Infrastructure Monitoring and Maintenance: Case Study of Mohammed VI Bridge in Morocco (2020) Proceedings of 2020 IEEE International conference of Moroccan Geomatics (Morgeo), , 11-13 May 2020, Casablanca, Morocco, Morocco; Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Gou, Z., Nee, A., Digital twin-driven product design framework (2019) International Journal of production research, (12), p. 57. , https://doi.org/10.1080/00207543.2018.1443229; Teng, S., Toud, M., Leong, W., How, B., Lam, H., Masa, V., Recent advances on industrial data-driven energy savings: Digital twins and infrastructures (2021) Renewable and Sustainable Energy Reviews, 135, p. 110208",,"Issa R.R.A.","Computing Division of the American Society of Civil Engineers (ASCE)","American Society of Civil Engineers (ASCE)","2021 International Conference on Computing in Civil Engineering, I3CE 2021","12 September 2021 through 14 September 2021",,179585,,9780784483893,,,"English","Comput. Civ. Eng. - Sel. Pap. ASCE Int. Conf. Comput. Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85132577008
"de Freitas Bello V.S., Popescu C., Blanksvärd T., Täljsten B., Popescu C.","57338405600;56272949500;20336636900;8703323300;56272949500;","Framework for facility management of bridge structures using digital twins",2021,"IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs",,,,"629","637",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119053364&partnerID=40&md5=2c97d419b5e6fffe2cd8d175aa0698b7","Luleå University of Technology (LTU), Luleå, Sweden; SINTEF Narvik AS, Narvik, 8517, Norway","de Freitas Bello, V.S., Luleå University of Technology (LTU), Luleå, Sweden; Popescu, C., Luleå University of Technology (LTU), Luleå, Sweden, SINTEF Narvik AS, Narvik, 8517, Norway; Blanksvärd, T., Luleå University of Technology (LTU), Luleå, Sweden; Täljsten, B., Luleå University of Technology (LTU), Luleå, Sweden; Popescu, C., Luleå University of Technology (LTU), Luleå, Sweden, SINTEF Narvik AS, Narvik, 8517, Norway","The maturity of Digital Twin (DT) models has evolved in the aerospace and manufacturing industries; however, the construction industry still lags behind. DT technology can be applied to achieve smart management through the entire life cycle of structures. Particularly for bridge structures, which play an essential role in any transportation system and can have high maintenance demands throughout their long life spans. In this study, a literature review on DTs was performed, from the origins of the concept until current best practice focused on bridges. Especially concerning structural analysis and facility management, few studies that employ DT for bridges were encountered. The main challenges identified are related to treatment of the large amount of data involved in the process, mostly gathered from different platforms. Finally, a framework for smart facility management of bridges using DTs was proposed to tackle potential solutions. © 2021 IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs. All rights reserved.","BIM; Bridges; BrIM; Digital twins; Facility management; Review","Architectural design; Bridges; Construction industry; Life cycle; Structural design; BIM; Bridge structures; BrIM; Entire life cycles; Facilities management; Lifespans; Long life; Maintenance demand; Manufacturing industries; Transportation system; Office buildings",,,,,"Energimyndigheten","This work was carried out within the strategic innovation program InfraSweden2030, a joint venture by Vinnova, Formas and The Swedish Energy Agency. The work is also funded by SBUF (construction industry's organisation for research and development in Sweden) and Skanska Sweden.",,"Woodward, R., Cullington, D. W., Daly, A. F., Vassie, P. R., Haardt, P., Kashner, R., Astudillo, R., Cremona, C., (2001) Bridge management in Europe (BRIME) - Deliverable D14-Final Report; Hurt, M., Schrock, S., Chapter 1 - Introduction (2016) Highway Bridge Maintenance Planning and Scheduling, pp. 1-30; Lu, Q., Xie, X., Heaton, J., Parlikad, A. K., Schooling, J., From BIM towards digital twin: Strategy and future development for smart asset management (2020) Studies in Computational Intelligence, 853, pp. 392-404; Kritzinger, W., Karner, M., Traar, G., Henjes, J., Sihn, W., Digital twin in manufacturing: a categorical literature review and classification (2018) IFAC Papers On Line, 51 (11), pp. 1016-1022; Grieves, M., Vickers, J., (2017) Digital Twin: mitigating unpredictable, undesirable emergent behavior in complex systems, pp. 85-113; Cimino, C., Negri, E., Fumagalli, L., Review of digital twin applications in manufacturing (2019) Computers in Industry, 113. , (103130); Negri, E., Fumagalli, L., Macchi, M., A review of the roles of Digital Twin in CPS-based production systems (2017) Procedia Manufacturing, 11, pp. 939-948; Shafto, M., Conroy, M., Doyle, R., Glaessgen, E., Kemp, C., LeMoigne, J., Wang, L., DRAFT Modeling, Simulation, Information Technology & Processing Roadmap (2010) Technology Area, 11; Shim, C.-S., Dang, N.-S., Lon, S., Jeon, C.-H., Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model (2019) Structure and Infrastructure Engineering, 15 (10), pp. 1319-1332; Lu, R., Brilakis, I., Digital twinning of existing reinforced concrete bridges from labelled point clusters (2019) Automation in Construction, 105. , (102837); Huthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC bridge defect information into BIM models (2018) Journal of Computing in Civil Engineering, 32 (3), pp. 1-14. , (04018013); Ye, C., Butler, L., Calka, B., Iangurazov, M., Lu, Q., Gregory, A., Girolami, M., Middleton, C., A digital twin of bridges for structural health monitoring (2019) Proceedings of the 12th International Workshop on Structural Health Monitoring; Andersen, J., Rex, S., Concrete bridge deck condition assessment using IR Thermography and Ground Penetrating Radar technologies (2019) 20th Congress of IABSE, , New York City 2019: The Evolving Metropolis; Lu, Q., Parlikad, A. K., Woodall, P., Don Ranasinghe, G., Xie, X., Liang, Z., Konstantinou, E., Schooling, J., Developing a digital twin at building and city levels: Case study of West Cambridge campus (2020) Journal of Management in Engineering, 36. , (05020004); Khajavi, S. H., Motlagh, N. H., Jaribion, A., Werner, L. C., Holmstrom, J., Digital twin: Vision, benefits, boundaries, and creation for buildings (2019) IEEE Access, 7, pp. 147406-147419; Tao, F., Zhang, M., Liu, Y., Nee, A. Y. C., Digital twin driven prognostics and health management for complex equipment (2018) CIRP Annals, 67, pp. 169-172; Jouan, P., Hallot, P., Digital twin: Research framework to support preventive conservation policies (2020) ISPRS International Journal of Geo-Information, 9 (228); Xu, Y., Sun, Y., Liu, X., Zheng, Y., A digital-twin-assisted fault diagnosis using deep transfer learning (2019) IEEE Access, 7, pp. 19990-19999; Xu, Y., Turkan, Y., BrIM and UAS for bridge inspections and management (2019) Engineering, Construction and Architectural Management, 27 (3), pp. 785-807; Abu Dabous, S., Yaghi, S., Alkass, S., Moselhi, O., Concrete bridge deck condition assessment using IR Thermography and Ground Penetrating Radar technologies (2017) Automation in Construction, 81, pp. 340-354; Delgado, J. M. D., Brilakis, I., Middleton, C., Modelling, management, and visualisation of structural performance monitoring data on BIM (2016) Proceedings of the International Conference on Smart Infrastructure and Construction, ICSIC, pp. 543-549; Delgado, J. M. D., Butler, L. J., Gibbons, N., Brilakis, I., Elshafie, M. Z. E. B., Middleton, C., Management of structural monitoring data of bridges using BIM (2017) Bridge Engineering, 170, pp. 204-218; Chan, B., Guan, H., Hou, L., Jo, J., Blumenstein, M., Wang, J., Defining a conceptual framework for the integration of modelling and advanced imaging for improving the reliability and efficiency of bridge assessments (2016) Journal of Civil Structural Health Monitoring, 6, pp. 703-714; Sacks, R., Kedar, A., Borrmann, A., Ma, L., Brilakis, I., Hüthwohl, P., Daum, S., Muhic, S., SeeBridge as next generation bridge inspection: Overview, information delivery manual and model view definition (2018) Automation in Construction, 90, pp. 134-145; Isailovic, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R., Döllner, J., Bridge damage: Detection, IFC-based semantic enrichment and visualization (2020) Automation in Construction, 112. , (103088); Boddupalli, C., Sadhu, A., Azar, E. R., Pattyson, S., Improved visualization of infrastructure monitoring data using building information modeling (2019) Structure and Infrastructure Engineering, 15 (9), pp. 1247-1263; Riveiro, B., Jauregui, D. V., Arias, P., Armesto, J., Jiang, R., An innovative method for remote measurement of minimum vertical underclearance in routine bridge inspection (2012) Automation in Construction, 25, pp. 34-40; Borin, P., Cavazzini, F., Condition assessment of RC bridges integrating machine learning, photogrametry and BIM (2019) International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, pp. 201-208. , XLII-2/W15; Morgenthal, G., Hallermann, N., Kersten, J., Taraben, J., Debus, P., Helmrich, M., Rodehorst, V., Framework for automated UAS-based structural condition assessment of bridges (2019) Automation in Construction, 97, pp. 77-95; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) Journal of Bridge Engineering, 21 (4), p. 04015076","de Freitas Bello, V.S.; Luleå University of Technology (LTU)Sweden; email: vanessa.saback.de.freitas@ltu.se","Snijder H.H.De Pauw B.De Pauw B.van Alphen S.F.C.Mengeot P.","Allplan;et al.;Greisch;Infrabel;Royal HaskoningDHV;TUC RAIL","International Association for Bridge and Structural Engineering (IABSE)","IABSE Congress, Ghent 2021: Structural Engineering for Future Societal Needs","22 September 2021 through 24 September 2021",,172892,,,,,"English","IABSE Congr., Ghent: Struct. Eng. Future Soc. Needs",Conference Paper,"Final","",Scopus,2-s2.0-85119053364
"Perry B.J., Guo Y., Atadero R., van de Lindt J.W.","57217167354;55873076900;23988525500;6701580121;","Unmanned aerial vehicle (UAV)-enabled bridge inspection framework",2021,"Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020",,,,"158","165",,,"10.1201/9780429279119-17","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117574244&doi=10.1201%2f9780429279119-17&partnerID=40&md5=e836085093e9d345738a393a2467d993","Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States","Perry, B.J., Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States; Guo, Y., Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States; Atadero, R., Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States; van de Lindt, J.W., Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States","Bridge inspections of medium or large scale are often cumbersome, expensive, and time-consuming. With a large number of bridges in the United States that require at least a bi-yearly inspection, there is a need to improve bridge inspection techniques to save time and reduce costs. Unmanned Aerial Vehicles (UAVs) have made tremendous advancements in recent years to allow for better data collection with enhanced sensors, more controllability with precise global-positioning-systems and inertial measurement units, and increased safety with omnidirectional sensors to avoid collisions while becoming more affordable. In current bridge inspection practice, UAVs have been used as “eyes-in-the-sky,” simply assisting inspectors to view bridges or other structures from different vantage points with the inspectors still taking measurements and making decisions with the traditional techniques. However, to take full advantage of the UAV's capabilities and allow for the UAV to perform and quantitate inspections automatically to create a more streamlined work-flow, there is a need for more robust data processing of the information attained by the UAV. A streamlined decision-making support framework is proposed that uniquely integrates UAV-based field inspection, automated damage identification, and establishment of an element-wise As-Built Bridge Information Model (AB-BrIM) for the damage documentation. In this framework, a UAV platform with optical sensors first collects the data. Next, an automated damage detection algorithm that highlights cracks and spalling is developed to quickly extract quantitative information (i.e. type, size, amount, and location). Finally, a 3-D point cloud is created with photogrammetry and then segmented into identified structural elements (e.g. beam, girders, deck, etc.) to serve as a base for the AB-BrIM. The identified damage information is automatically linked to each element. The resulting AB-BrIM with 3-D visualization of element-wise, quantitative damage information offers a transparent condition evaluation and thus can greatly ease the planning of repair/maintenance. © 2021 Taylor & Francis Group, London",,"Bridges; Damage detection; Data handling; Decision making; Life cycle; Maintenance; Omnidirectional antennas; Three dimensional computer graphics; Bridge inspection; Damage information; Data collection; Information Modeling; Inspection technique; Large-scales; Medium-scale; Reduce costs; Saves time; Time cost; Unmanned aerial vehicles (UAV)",,,,,"69A3551747108; U.S. Department of Transportation, DOT; Colorado State University, CSU; Mountain-Plains Consortium, MPC","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University’s Drone Center for providing the UAVs and support.","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University's Drone Center for providing the UAVs and support.","(2018) The Manual for Bridge Evaluation, , AASHTO Third Edition, 2017 (3rd ed). Washington, D.C.: American Association of State Highway and Transportation Officials; (2018) Revit, , Autodesk; Bang, S., Kim, H., Kim, H., UAV-based automatic generation of high-resolution panorama at a construction site with a focus on preprocessing for image stitching (2017) Automation in Construction, 84, pp. 70-80. , (August); (2017) LEAP Bridge, , Bently; Bradski, G., (2000) The OpenCV Library; Chiu, W. K., Ong, W. H., Kuen, T., Courtney, F., Large Structures Monitoring Using Unmanned Aerial Vehicles (2017) Procedia Engineering, 188, pp. 415-423; Dorafshan, S., Maguire, M., Hoffer, N. V., Coopmans, C., Challenges in bridge inspection using small unmanned aerial systems: Results and lessons learned (2017) 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1722-1730. , (6) IEEE; Dorafshan, S., Thomas, R. J., Maguire, M., Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete (2018) Construction and Building Materials, 186, pp. 1031-1045; Duque, L., Seo, J., Wacker, J., Bridge Deterioration Quantification Protocol Using UAV (2018) Journal of Bridge Engineering, 23 (10), p. 04018080; Gageik, N., Strohmeier, M., Montenegro, S., An autonomous UAV with an optical flow sensor for positioning and navigation (2013) International Journal of Advanced Robotic Systems, 10, pp. 1-9; Gillins, M. N., (2016) Cost-Effective Bridge Safety Inspections Using Unmanned Aerial Vehicles (Uavs), , Technical report, United States Department of Transportation, Washington, D.C; Gillins, M. N., Gillins, D. T., Parrish, C., Cost-Effective Bridge Safety Inspections Using Unmanned Aircraft Systems (UAS) (2016) Geotechnical and Structural Engineering Congress 2016, , Phoenix, AZ; Girshick, R., Donahue, J., Darrell, T., Malik, J., Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation (2014) 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 580-587; Greenwood, W. W., Lynch, J. P., Zekkos, D., Applications of UAVs in Civil Infrastructure (2019) Journal of Infrastructure Systems, 25 (2), p. 04019002; Hernandez, I., (2016) Overcoming the Challenges of Using Unmanned Aircraft for Bridge Inspections, , Ph. D. thesis, University of Missouri-Kansas City; Hoang, N.-D., Nguyen, Q. L., Tran, V. D., Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network (2018) Automation in Construction, 94, pp. 203-213. , (June); Jahanshahi, M. R., Masri, S. F., Adaptive vision-based crack detection using 3D scene reconstruction for condition assessment of structures (2012) Automation in Construction, 22, pp. 567-576; Li, J., Wong, H. C., Lo, S. L., Xin, Y., Multiple Object Detection by a Deformable Part-Based Model and an R-CNN (2018) IEEE Signal Processing Letters, 25 (2), pp. 288-292; Lowe, D., Object recognition from local scale-invariant features (1999) Proceedings of the Seventh IEEE International Conference on Computer Vision, pp. 1-8. , Kerkyra, Greece, IEEE; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge Information Modeling for Inspection and Evaluation (2016) Journal of Bridge Engineering, 21 (4), p. 04015076; Moore, M., Phares, B., Graybeal, B., Rolander, D., Washer, G., (2001) Reliability of Visual Inspection for Highway Bridges, , Technical Report FHWA-RD-01-020, FHWA, Atlanta, GA; Moulon, P., Monasse, P., Marlet, R., Adaptive Structure from Motion with a contrario model estimation (2012) Lecture Notes in Computer Science, 7727, pp. 1-14. , (PART 4); Mulakala, J., (2018) Measurement Accuracy of the DJI Phantom 4 RTK & Photogrammetry, , Technical report, DroneDeploy, San Francisco, CA; Omar, T., Nehdi, M. L., Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography (2017) Automation in Construction, 83, pp. 360-371. , (April); Ryan, T. W., Mann, E., Chill, Z. M., Ott, B. T., (2012) Bridge Inspector's Reference Manual, , Technical report, FHWA, Washington, D.C; Sankarasrinivasan, S., Balasubramanian, E., Karthik, K., Chandrasekar, U., Gupta, R., Health Monitoring of Civil Structures with Integrated UAV and Image Processing System (2015) Procedia Computer Science, 54, pp. 508-515; Schoenberger, J. L., Frahm, J.-M., Structure-from-Motion Revisited (2016) Conference on Computer Vision and Pattern Recognition (CVPR); Seo, J., Duque, L., Wacker, J. P., Field Application of UAS-Based Bridge Inspection (2018) Transportation Research Record, 2672 (12), pp. 72-81; Shahnaz, S., (2010) Gravel Road Condition Monitoring Using Unmanned Aerial Vehicle (UAV) Technology, , Ph. D. thesis, South Dakota State University; Talab, A. M. A., Huang, Z., Xi, F., Haiming, L., Detection crack in image using Otsu method and multiple filtering in image processing techniques (2016) Optik, 127 (3), pp. 1030-1033; (2018) Tekla Structures, , Trimble; Wells, J., Lovelace, B., (2018) Improving the Quality of Bridge Inspections Using Unmanned Aircraft Systems (UAS), , Technical Report July, Minnesota Department of Transportation, St. Paul, MN; Wu, C., Towards linear-time incremental structure from motion (2013) Proceedings - 2013 International Conference on 3D Vision, 3DV 2013, pp. 127-134; Zhang, N., Donahue, J., Girshick, R., Darrell, T., Part-Based R-CNNs for Fine-Grained Category Detection (2014) ECCV, 2014 1, pp. 834-849; Zhou, Q.-y., Park, J., Koltun, V., (2018) Open3D: A Modern Library for 3D Data Processing; Zingg, S., Scaramuzza, D., Weiss, S., Siegwart, R., MAV navigation through indoor corridors using optical flow (2010) Proceedings - IEEE International Conference on Robotics and Automation, pp. 3361-3368",,"Yokota H.Frangopol D.M.",,"CRC Press/Balkema","10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020","11 April 2021 through 15 April 2021",,172353,,9780429279119; 9780367232788,,,"English","Bridge Maint., Saf., Manag., Life-Cycle Sustain. Innov. - Proc. Int. Conf. Bridge Maint., Saf. Manag., IABMAS",Conference Paper,"Final","",Scopus,2-s2.0-85117574244
"Tanaka F., Nakajima Y., Egusa E., Onosato M.","14826015900;57304744500;57304004500;6701469140;","Data modeling based on a 3D BIM standard and viewer system for the bridge inspections",2021,"Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020",,,,"2984","2991",,,"10.1201/9780429279119-406","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117562203&doi=10.1201%2f9780429279119-406&partnerID=40&md5=3c656e2717083145897e0efadbc3a00a","Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan","Tanaka, F., Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan; Nakajima, Y., Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan; Egusa, E., Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan; Onosato, M., Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan","A data model containing information of design and inspection data is important in inspection, maintenance, and asset management using information and communication technology. In this paper, we propose a three-dimensional (3D) bridge information model based on Industry Foundation Classes (IFC), which are a building information modeling standard, for the support of inspection, evaluation, and maintenance. Various data, such as text, photographs, point clouds, and measured polygon meshes, relating to the inspection, evaluation, and repair of a bridge are recorded in the 3D bridge model. A viewer system, which has the ability to visually present not only 3D geometric models but also a virtual-reality environment, is developed to show the model. This system also extracts information from past inspection reports written as documents. A data segmentation procedure is proposed for point clouds and measured polygon meshes. © 2021 Taylor & Francis Group, London",,"3D modeling; Architectural design; Bridges; Information theory; Life cycle; Maintenance; Virtual reality; BIM standards; Bridge inspection; Design data; Inspection datum; Inspection maintenance; Inspection management; Maintenance management; Model-based OPC; Point-clouds; Polygon meshes; Inspection",,,,,,,,"(2019) Industry Foundation Classes (IFC) 4.2, , https://standards.buildingsmart.org/IFC/DEV/IFC4_2/FINAL/HTML/, buildingSMART International [Accessed November 11,2019]; Chen, S., UAV Bridge Inspection through Evaluated 3D Reconstructions (2018) Journal of Bridge Engineering, 24 (4); Fathall, E., Remaining fatigue life assessment of in-service road bridge decks based upon artificial neural networks (2018) Engineering Structures, 171, pp. 602-616; Hada, Y., Development of a Bridge Inspection Support System Using Two-Wheeled Multicopter and 3D Modeling Technology (2017) J. Disaster Res, 12 (4), pp. 593-606; Hüthwohl, P., Integrating RC Bridge Defect Information into BIM Models (2018) Journal of Computing in Civil Engineering, 32 (3), pp. 1-14; (2004) Industrial automation systems and integration - Product data representation and exchange - Part 11: Description methods: The EXPRESS language reference manual, , ISO 10303-11; (2018) Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries - Part 1: Data schema, , ISO 16739-1; Lu, R., Detection of Structural Components in Point Clouds of Existing RC Bridges (2019) Computer-Aided Civil and Infrastructure Engineering, 34 (2019), pp. 191-212; (2014) Guideline for Periodic Road Bridge Inspection, , MLIT (Ministry of Land, Infrastructure, Transport and Tourism). (In Japanese) Tokyo: Japan; (2015) Road Maintenance in Japan: Problems and Solutions, , http://www.mlit.go.jp/road/road_e/pdf/RoadMaintenance.pdf, MLIT (Ministry of Land, Infrastructure, Transport and Tourism). [Accessed November 11,2019]; Popescu, C., 3D reconstruction of existing concrete bridges using optical methods (2019) Structure and Infrastructure Engineering, 15 (7), pp. 912-924; Özyeşil, O., A survey of structure from motion (2017) Acta Numerica, 26, pp. 305-364; Sacks, R., SeeBridge as next generation bridge inspection: Overview, Information Delivery Manual and Model View Definition (2018) Automation in Construction, 90, pp. 134-145; Salamak, M., Januszka, M., BrIM bridge inspections in the context of Industry 4.0 trends (2018) Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges, pp. 2260-2268. , Powers, N. et al. (eds) Taylor & Francis Group, London; Tanaka, F., Bridge information model based on IFC standards and web content providing system for supporting an inspection process (2016) Proceedings of 16th Int. Conf. on Computing in Civil and Building Engineering; Tanaka, F., Bridge Information Modeling based on IFC for supporting maintenance management of existing bridges (2018) Proceedings of 17th Int. Conf. on Computing in Civil and Building Engineering; Tanaka, F., Tsuchida, M., Onosato, M., Associating 2D Sketch Information with 3D CAD Models for VR/AR Viewing During Bridge Maintenance Process (2019) Int. J. Automation Technol, 13 (4), pp. 482-489; Yang, S., UAV Assisted Bridge Defect Inspection System (2018) Intelligence Science II. ICIS 2018. IFIP Advances in Information and Communication Technology, 539. , Shi Z., Pennartz C., Huang T. (eds) Springer, Cham",,"Yokota H.Frangopol D.M.",,"CRC Press/Balkema","10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020","11 April 2021 through 15 April 2021",,172353,,9780429279119; 9780367232788,,,"English","Bridge Maint., Saf., Manag., Life-Cycle Sustain. Innov. - Proc. Int. Conf. Bridge Maint., Saf. Manag., IABMAS",Conference Paper,"Final","",Scopus,2-s2.0-85117562203
"Lin J.-R.","56703744700;","Openbridgegraph: Integrating open government data for bridge management",2020,"Proceedings of the 37th International Symposium on Automation and Robotics in Construction, ISARC 2020: From Demonstration to Practical Use - To New Stage of Construction Robot",,,,"1255","1262",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109362203&partnerID=40&md5=5daa88e518ffb35b8b3a353011a2446c","Department of Civil Engineering, Tsinghua University, China; Tsinghua University-Glodon Joint Research Center for Building Information Modeling, Tsinghua University, China","Lin, J.-R., Department of Civil Engineering, Tsinghua University, China, Tsinghua University-Glodon Joint Research Center for Building Information Modeling, Tsinghua University, China","Due to limited funds, road authorities around the world are facing challenges related to bridge management and the escalating maintenance requirements of large infrastructure assets. Nowadays, many government organizations have published a variety of data to enable transparency, foster applications, and to satisfy legal obligations. Open governments data like bridge data, weather data would help to better assess the condition of bridges for maintenance purpose and allocation of funds. However, these data sets are fragmented in different systems or formats, and their value in bridge management are not fully explored. This paper proposes a graph-based bridge information modeling framework to integrate open government data for bridge management. The framework represents bridge inventory data as a labeled property graph model and extends the model with weather data. Implementation of the framework employs python scripts for data processing, and neo4j database for data management. The framework is demonstrated using data from national bridge inventory (NBI) and national oceanic and atmosphere administration (NOAA). The results show that the proposed framework can potentially facilitate the integration and retrieval of public government data, and effectively support and provide services to bridge management. Scripts and used data are also shared on GitHub to foster future explorations. © 2020 Proceedings of the 37th International Symposium on Automation and Robotics in Construction, ISARC 2020: From Demonstration to Practical Use - To New Stage of Construction Robot. All rights reserved.","Bridge information modeling; Bridge management; Data retrieval; Graph database; Knowledge; Open government data","Agricultural robots; Data integration; Government data processing; Graphic methods; Industrial robots; Meteorology; Open Data; Robotics; Bridge inventory data; Bridge management; Government organizations; Information modeling frameworks; Infrastructure assets; Legal obligations; Maintenance requirement; Road authorities; Information management",,,,,"National Natural Science Foundation of China, NSFC: 51908323; Tsinghua University, THU: 2019Z02UOT; Natural Science Foundation of Beijing Municipality: 8194067","This research is supported by the Tsinghua University Initiative Scientific Research Program (No. 2019Z02UOT), the Natural Science Foundation of China (No. 51908323), and the Beijing Natural Science Foundation (No. 8194067). The author also thanks Prof. Kincho Law (Stanford University) for his valuable comments.",,"Rashidi, M., Samali, B., Sharafi, P., A new model for bridge management: Part A: Condition assessment and priority ranking of bridges (2016) Australian Journal of Civil Engineering, 14 (1), pp. 35-45; Pregnolato, M., Bridge safety is not for granted-a novel approach to bridge management (2019) Engineering Structures, 196, p. 109193; Aktan, A., Farhey, D., Brown, D., Dalal, V., Helmicki, A., Hunt, V., Shelley, S., Condition assessment for bridge management (1996) Journal of Infrastructure Systems, 2 (3), pp. 108-117; Wang, H., Hsieh, S., Lin, C., Wang, C., Forensic diagnosis on flood-induced bridge failure. I: Determination of the possible causes of failure (2014) Journal of Performance of Constructed Facilities, 28 (1), pp. 76-84; Thompson, P., Small, E., Johnson, M., Marshall, A., The Pontis bridge management system (1998) Structural Engineering International, 8 (4), pp. 303-308; Attard, J., Orlandi, F., Scerri, S., Auer, S., A systematic review of open government data initiatives (2015) Government Information Quarterly, 32 (4), pp. 399-418; National Bridge Inventory, , Https://www.fhwa.dot.gov/bridge/nbi.cfm, FHWA. On-line: Accessed: 14/03/2020; Climate Data Online, , Https://www.ncdc.noaa.gov/cdo-web/, NOAA. On-line: Accessed: 14/03/2020; Yoon, B., Kim, S., Kim, S., Use of graph database for the integration of heterogeneous biological data (2017) Genomics & informatics, 15 (1), pp. 19-27; (1995) Recording and Coding Guide for the Structure Inventory and Appraisal of the Nation's Bridges, , FHWA. Washington, D.C","Lin, J.-R.; Department of Civil Engineering, China; email: lin611@tsinghua.edu.cn",,"Advanced Construction Technology Center;Architectural Institute of Japan;Council for Construction Robot Research;et al.;Japan Robot Association;The International Association for Automation and Robotics in Construction (IAARC)","International Association on Automation and Robotics in Construction (IAARC)","37th International Symposium on Automation and Robotics in Construction: From Demonstration to Practical Use - To New Stage of Construction Robot, ISARC 2020","27 October 2020 through 28 October 2020",,169727,,9789529436347,,,"English","Proc. Int. Symp. Autom. Robot. Constr., ISARC: From Demonstr. Pract. Use - New Stage Constr. Robot",Conference Paper,"Final","",Scopus,2-s2.0-85109362203
"Turkan Y., Xu Y.","54390463700;57274179700;","Deep semantic segmentation for 3D as-is bridge model generation",2020,"Sustainable Buildings and Structures: Building a Sustainable Tomorrow - Proceedings of the 2nd International Conference in Sustainable Buildings and Structures, ICSBS 2019",,,,"16","",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108919986&partnerID=40&md5=a7fdde4bcafc1865ed6aeb79f9a4efc7","School of Civil Engineering & Construction Engineering, Oregon State University, Corvallis, OR, United States","Turkan, Y., School of Civil Engineering & Construction Engineering, Oregon State University, Corvallis, OR, United States; Xu, Y., School of Civil Engineering & Construction Engineering, Oregon State University, Corvallis, OR, United States","The mobility of people and goods is highly dependent on the health of a nation’s transportation system. Timely inspection and effective maintenance of bridges is crucial to avoid any issues that may have a negative impact on public mobility. However, current bridge inspection practice inhibits the collection and analysis of information regarding the status of bridges in an efficient and timely manner. A Bridge Information Model (BrIM) is an object-oriented database that enables storing all bridge data, including its 2D drawings and 3D models, material specifications, inspection notes, images and maintenance information. Recent research efforts have focused on implementing BrIM for bridge structural condition assessment, and concluded that it is a suitable concept and technology that can be used to improve the current bridge inspection and management processes. However, there are several challenges that needs to be overcome for wide adoption of BrIM for bridge inspections and management tasks. These challenges include the following: 1) manual development of 3D BrIM for existing bridges from their 2D drawings and specifications is labor-intensive and time-consuming; 2) 3D BrIM that are built based on the original 2D drawings may be inaccurate representations of the current status and geometrical information of the bridges; and 3) transportation agencies do not have the resources or personnel time to develop 3D BrIM for all the bridges they maintain and operate. There is, therefore, an urgent need to establish an automated and cost-effective method for developing 3D BrIM for existing bridges. In order to overcome these challenges associated with the development of 3D BrIMs, this study presents a novel data collection and analysis framework that enables rapid collection of 3D geometrical information from existing bridges in the form of 3D dense point clouds, and converts them into 3D BrIM in an automated and efficient manner. 3D point clouds are obtained by applying Structure from Motion (SfM) algorithms to the images collected using an Unmanned Aerial System (UAS). In the next step, these 3D point clouds are automatically segmented and classified into different structural components using deep learning algorithms. In the final step, the labeled point clouds are automatically converted to 3D BrIM. In summary, this study develops a framework that will make it more convenient and faster to develop and implement 3D BrIM, which can improve the current bridge inspection and management practice significantly in terms of efficiency and safety, thus help improve public mobility. © 2020 Taylor & Francis Group, London.",,"Antennas; Cost effectiveness; Deep learning; Inspection; Intelligent buildings; Learning algorithms; Object recognition; Object-oriented databases; Semantics; Specifications; Sustainable development; Transportation personnel; Cost-effective methods; Geometrical informations; Maintenance information; Material specification; Structure from motion algorithm; Transportation agencies; Transportation system; Unmanned aerial systems; Bridges",,,,,,,,,,"Papadikis K.Chin C.S.Galobardes I.Gong G.Guo F.",,"CRC Press/Balkema","2nd International Conference in Sustainable Buildings and Structures, ICSBS 2019","25 October 2019 through 27 October 2019",,260199,,9780367430191,,,"English","Sustain. Build. Struct.: Build. Sustain. Tomorrow - Proc. Int. Conf. Sustain. Build. Struct.",Conference Paper,"Final","",Scopus,2-s2.0-85108919986
"Singh H.","57209254668;","Sustainable practices for bridge structures",2020,"IABSE Congress, Christchurch 2020: Resilient Technologies for Sustainable Infrastructure - Proceedings",,,,"1048","1055",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104764206&partnerID=40&md5=22e0f4843b9ac7f26e32e4b5991df1ae","Arcadis Australia Pty. LtdVIC, Australia","Singh, H., Arcadis Australia Pty. LtdVIC, Australia","On a typical project, the sustainability requirements of bridges should be considered from the planning stage or earlier. In recent years, a lot of research has been undertaken to improve the durability of reinforced concrete and with the use of high-grade steel and weathering steel, the sustainability aspects of bridges have significantly improved. To ensure sustainability in bridges, the already available framework of sustainability covering environmental, economic and social aspects can be implemented. There are several other frameworks and guidelines available from different countries about the sustainability requirements that can be useful for bridges. The paper presents a brief overview of sustainability in bridges, current practices and areas of emerging and future opportunities to improve sustainability. © 2020 IABSE Congress, Christchurch 2020: Resilient Technologies for Sustainable Infrastructure - Proceedings. All rights reserved.","BIM; Bridge; BrIM; Economic; Environment; Future; Life cycle; Power; Social; Sustainability","Reinforced concrete; Social aspects; Weathering steel; Bridge structures; Current practices; High grade steels; Planning stages; Sustainable practices; Sustainable development",,,,,,,,"(2006) Environmental Management- Life Cycle Assessment- Principles and Framework, , ISO 14040, International Organization for Standardization, Geneva, Switzerland; (2006) Environmental Management- Life cycle Assessment- Requirements and Guidelines, , ISO 14044, International Organization for Standardization, Geneva, Switzerland; Mirza, Saeed, Design of durable and sustainable bridges , pp. 333-344. , Dr. CBM-CI International Workshop, Karachi, Pakistan; Constructing for sustainability - a basic guide for clients and their professional advisors, , Construction Industry Council, UK; Gervasio, Helena, da Silva, Luís Simões, A design approach for sustainable bridges - Part 1: Methodology; (2017) Using a Life cycle Planning Process to Support Asset Management, , Federal Highway Administration. November; CD 355 Application of whole-life costs for design and maintenance of highway structure, , Highways England UK; http://www.ceequal.com/download/4487/An_introduction_to_CEEQUAL_May_2018; https://www.isca.org.au/is_ratings, ISCA rating scheme; Singh, Harminder, Repair and Retrofitting of Bridges - Present and Future (2018) IABMAS Conference; Marzouk, M. M., Hisham, M., Bridge Information Modeling in Sustainable Bridge Management ICSDC, 201, pp. 457-466; https://www.tekla.com/products/teklastructures, Tekla structures; https://envusa.design/ourapproach.html, Envision; Marzouk, M. M., Hisham, M., On the use of building information modeling in infrastructure bridges; http://www.issol.eu/, White solar panels; https://www.smartcitylab.com/blog/urban-environment/recoveringenergy-from-traffic-positive-energy-roads/, Recovering energy from traffic: positive energy roads; https://edition.cnn.com/style/article/shanghai-3d-printed-bridgescli-intl/index.html, Shanghai opens world's longest 3D-printed concrete bridge; https://www.theguardian.com/environment/2014/jan/22/worlds-largestsolar-powered-bridge-opens-in-london, World's largest solar-powered bridge opens in London","Singh, H.; Arcadis Australia Pty. LtdAustralia; email: harsingh4@hotmail.com","Abu A.","Arup;Aurecon;Granor Rubber and Engineering;Sika;TJAD;WSP","International Association for Bridge and Structural Engineering (IABSE)","IABSE Congress Christchurch 2020: Resilient Technologies for Sustainable Infrastructure","3 February 2021 through 5 February 2021",,168364,,9783857481703,,,"English","IABSE Congress, Christchurch: Resilient Technol. Sustain. Infrastr. - Proc.",Conference Paper,"Final","",Scopus,2-s2.0-85104764206
"Bien J., Salamak M.","7003571099;25028351300;","Management of bridge structures-challenges and possibilities",2020,"IABSE Symposium, Wroclaw 2020: Synergy of Culture and Civil Engineering - History and Challenges, Report",,,,"8","31",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103440178&partnerID=40&md5=1124d55cdb29270c991b8107334e1485","Faculty of Civil Engineering, Wrocaw University of Science and Technology, Wroclaw, Poland; Faculty of Civil Engineering, Silesian University of Technology, Gliwice, Poland","Bien, J., Faculty of Civil Engineering, Wrocaw University of Science and Technology, Wroclaw, Poland; Salamak, M., Faculty of Civil Engineering, Silesian University of Technology, Gliwice, Poland","Bridges are particularly vulnerable elements of transport infrastructures. In many cases, bridge structures may be subject to higher volumes of traffic and higher loads as well as more severe environmental conditions than it was designed. Sound procedures to ensure monitoring, quality control, and preventive maintenance systems are therefore vital. The paper presents main challenges and arriving possibilities in management of bridge structures, including: Relationships between environment and bridge infrastructure, improvement of diagnostic technologies, advanced modelling of bridges in computer-based management systems, development of knowledge-based expert systems with application of artificial intelligence, applications of technology of Bridge Information Modelling (BrIM) with augmented and virtual reality techniques. Presented activities are focused on monitoring the safety of bridges for lowering the risk of an unexpected collapse significantly as well as on efficient maintenance of bridges as components of transport infrastructure-by means of integrated management systems. © 2020 IABSE Symposium, Wroclaw 2020: Synergy of Culture and Civil Engineering - History and Challenges, Report. All rights reserved.","Bridge; Bridge information modelling; Bridge management system; Diagnostics; Environment; Management","Expert systems; History; Information management; Knowledge acquisition; Augmented and virtual realities; Bridge infrastructure; Diagnostic technologies; Environmental conditions; Information modelling; Integrated management systems; Knowledge-based expert systems; Transport infrastructure; Bridges",,,,,"European Commission, EC","testing and monitoring. Development of technologies of the transport infrastructure management in essential scope is stimulated by international research cooperation supported by the European Union, like “Sustainable Bridges – Assessment for Future Traffic Demands and Longer Live” [21] or “Quality specifications for roadway bridges, standardization at a European level” [22]. It creates a chance for the integration of transport infrastructure management in the whole EU.",,"PANG, B., YANG, P., WANG, Y., KENDALL, A., XIE, H., ZHANG, Y., Life cycle environmental impact assessment of a bridge with different strengthening schemes (2015) The International Journal of Life Cycle Assessment, 20 (9), pp. 1300-1311; BIONDINI, F., FRANGOPOL, D.M., (2012) Bridge Maintenance, Safety, Management, Resilience and Sustainability, p. 4061. , (eds), CRC Press; YEHIA, S., ABUDAYYEH, O., NABULSI, S., ABDELQADER, I., Detection of common defects in concrete bridge decks using non-destructive evaluation techniques (2007) J. Bridge Engrg, 12 (2), pp. 215-225; BIEN, J., (2010) Defects and diagnostics of bridge structures (in Polish), p. 417. , Transport and Communication Publishers, Warsaw; HOA, J., BIEN, J., SADOWSKI, L., SCHABOWICZ, K., Non-destructive and semi-destructive diagnostics of concrete structures in assessment of their durability (2015) Bulletin of the Polish Academy of Sciences, Technical Sciences, 63 (1), pp. 87-96; BIEN, J., KAMINSKI, T., KUZAWA, M., Taxonomy of non-destructive field tests of bridge materials and structures (2019) Archives of Civil and Mechanical Engineering, 19 (4), pp. 1353-1367; WANG, X., DOU, W., CHEN, S., RIBARSKY, W., CHANG, R., An Interactive Visual Analytics System for Bridge Management (2010) Comput. Graph. Forum, 29 (3), pp. 1033-1042; THOMPSON, P.D., SMALL, E.P., JOHNSON, M., MARSHALL, A.R., The PONTIS Bridge Management System (1998) Struct. Eng. Int, 8 (4), pp. 303-308; SODERQVIST, M. K., VEIJOLA, M., The Finnish Bridge Management System (1998) Structural Engineering International, 8 (4), pp. 315-319; THOMPSON, P.D., CHETHAM, A., MERLO, T., ELLIS, R., KERR, B., The New Ontario Bridge Management System (2000) Transportation Research Circular, (498). , F-6/1-15; BIEN, J., Modelling of structure geometry in Bridge Management Systems (2011) Archives of Civil and Mechanical Engineering, 11 (3), pp. 519-532; KAMINSKI, T., BIEN, J., BIEN, B., An expert tool for assessment of damaged masonry arch bridges (2013) 7th International Conference on Arch Bridges, pp. 691-698. , Trogir-Split, Croatia; BIEN, J., KUZAWA, M., NDT-based bridge condition assessment supported by expert tools (2016) International Conference of Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015) American Institute of Physics, pp. 1-4. , Rhodes, 2015, AIP Publishing; VAGNOLI, M., REMENYTE-PRESCOTT, R., ANDREWS, J., Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges (2017) Structural Health Monitoring, 17 (4), pp. 971-1007; SHIM, CH.-S, KANG, H., DANG, N.S., LEE, D., Development of BIM-based bridge maintenance system for cable-stayed bridges (2017) Smart Structures & Systems, 20 (6), pp. 697-708; AZUMA, R.T., A Survey of Augmented Reality (1997) Tele-operators Virtual Environ, 6 (4), pp. 355-385; BIEN, J., KUZAWA, M., BIEN, B., To See is to Know: Visualization in Bridge Inspection and Management (2010) 5th International Conference on Bridge Maintenance, Safety and Management, pp. 567-574. , Philadelphia; SALAMAK, M., JANUSZKA, M., BrIM bridge inspections in the context of Industry 4.0 trends (2018) Proceedings of IABMAS 2018, Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges, pp. 2260-2267; WANG, X., LOVE, P.E.D., JEONG KIM, M., PARK, C., SING, C., HOU, L., A conceptual framework for integrating building information modelling with augmented reality (2013) Autom. Constr, 34, pp. 37-44; CHUNFENG, W., ZHENWEI, Z., SIYUAN, L., YOULIANG, D., ZHAO, X., ZEGANG, Y., YEFEI, X., FANGZHOU, Y., Development of a Bridge Management System Based on the Building Information Modelling Technology (2019) Sustainability, 11, p. 4583; OLOFSSON, J., Assessment of European Railway Bridges for Future Traffic Demands and Longer Lives-EC Project ""Sustainable Bridges (2005) Journal of Structure and Infrastructure Engineering, 1 (2), pp. 93-100; MATOS, J., An overview of the European situation on quality control of existing bridges-COST Action TU1406 (2018) Proceedings of the 40th IABSE Symposium, , Nantes, France; BIEN, J., KRZYZANOWSKI, J., RAWA, P., ZWOLSKI, J., Dynamic Load Tests in Bridge Management (2004) Archives of Civil and Mechanical Engineering, 4 (2), pp. 63-78; CUNHA, A., CAETANO, E., MAGALHAES, F., Output-Only Dynamic Testing of Bridges and Special Structure (2007) Structural Concrete, 8 (2), pp. 67-85; WENZEL, H., (2009) Health Monitoring of Bridges, , J. Wiley & Sons Ltd; ZWOLSKI, J., BIEN, J., Modal analysis of bridge structures by means of Forced Vibration Tests (2011) Journal of Civil Engineering and Management, 17 (4), pp. 590-599; HELMERICH, R., NIEDERLEITHINGER, E., TRELA, CH., BIEN, J., BERNARDINI, G., Multi-tool inspection and numerical analysis of an old masonry arch bridge (2012) Structure and Infrastructure Engineering, 8 (1), pp. 27-39; MIDDLETON, C., FIDLER, P.R.A., VARDANEGA, P.J., (2016) Bridge Monitoring: A Practical Guide, , (eds), ICE Publishing; MAKSYMOWICZ, M., CRUZ, P., BIEN, J., Load capacity of damaged RC slab spans of railway bridges (2011) Archives of Civil and Mechanical Engineering, 11 (4), pp. 963-978; ZWOLSKI, J., BIEN, J., KAMINSKI, T., KUZAWA, M., RAWA, P., Experimental vibration analysis of concrete box bridge girders (2013) 5th International Conference on Experimental Vibration Analysis for Civil Engineering Structures EVACES 2013, pp. 193-200. , Ouro Preto, Brazil; BIEN, J., KAMINSKI, T., KUZAWA, M., Validation of numerical models of concrete box bridges based on load test results (2015) Archives of Civil and Mechanical Engineering, 15 (4), pp. 1046-1060; KUZAWA, M., KAMINSKI, T., BIEN, J., Fatigue assessment procedure for old riveted road bridges (2018) Archives of Civil and Mechanical Engineering, 18 (4), pp. 1259-1274; KAMINSKI, T., KUZAWA, M., BIEN, J., Experimental and numerical assessment of an old backfilled concrete arch bridge (2020) 9th International Conference on Arch Bridges, Structural Integrity, 11, pp. 194-202. , Springer; BIEN, J., KUZAWA, M., GADYSZ-BIEN, KAMINSKI T., Quality control of road bridges in Poland (2016) 8th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2016, pp. 971-978. , Foz do Iguaçu, Brasil; ZADEH, L. A., Fuzzy sets and information granularity (1979) Advances in Fuzzy Set Theory and Applications, pp. 3-18. , M. Gupta, R. Ragade and R. Yager, eds., North-Holland, Amsterdam; SASMAL, S., RAMANJANEYULU, K., Condition evaluation of existing reinforced concrete bridges using fuzzy based analytic hierarchy approach (2008) Int. J. Expert Systems with Applications, 35 (3), pp. 1430-1441; LI, Z., BURGUEÑO, R., Using soft computing to analyze inspection results for bridge evaluation and management (2010) J. Bridge Engrg, 15 (4), pp. 430-439; KUZAWA, M., BIEN, J., GADYSZ-BIEN, M., Hybrid knowledge expert tool for load capacity assessment of railway plate girders with defects (2013) 11th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2013), pp. 1294-1297. , American Institute of Physics, Rhodes; ABDULLAH, A., THAI, O.B., Personal digital assistants as a mobile inspection system at construction site (2006) Proceedings of the 6th Asia-Pacific Structural Engineering and Construction Conference (APSEC 2006), pp. D28-D38. , 5-6 September Kuala Lumpur, Malaysia, 2006; BIEN, J., RAWA, P., Hybrid Knowledge Representation in BMS (2004) Ach. Civ. Mech. Eng, 4 (1), pp. 41-55; CARLSON, W., (2013) A Critical History of Computer Graphics and Animation, , Ohio State University, Ohio; GOLPARVAR-FARD, M., D4AR. 4-Dimensional Augmented Reality (2012) LiDAR Mag, 2, pp. 11-15; GOASZEWSKA, M., SALAMAK, M., Challenges in takeoffs and cost estimating in the BIM technology, based on the example of a road bridge model (2017) Tech. Trans. Civ. Eng, 4 (201), pp. 71-79; HU, Y., HAMMAD, A., Location-based Mobile Bridge Inspection Support System (2005) Proceedings of the 1st CSCE Specialty Conference on Infrastructure Technologies, , Ontario, FR130.1-FR130.10; JANUSZKA, M., MOCZULSKI, W., Acquisition and Knowledge Representation in the Product Development Process with the Use of Augmented Reality (2013) Concurrent Engineering Approaches for Sustainable Product Development in a Multi-Disciplinary Environment, pp. 315-326. , Proceedings of the J. Stjepandic et al. (eds), Springer-Verlag, London; JASINSKI, M., PASZCZYK, T., SALAMAK, M., Visual programming and BIM technology in parametric concrete bridge design (2017) 12th Central European Congress on Concrete Engineering CCC2017, pp. 130-138. , Tokaj, Hungary; MILGRAM, P., TAKEMURA, H., UTSUMI, A., KISHINO, F., Augmented Reality: A class of displays on the reality-virtuality continuum (1994) Proceedings of SPIE-The International Society for Optical Engineering, 2351; SALAMAK, M., JANUSZKA, M., BIM models and augmented reality for concrete bridge inspections (2015) 11th Central European Congress on Concrete Engineering CCC2015, pp. 25-28. , Hainburg","Bien, J.; Faculty of Civil Engineering, Poland; email: jan.bien@pwr.edu.pl","Bien J.Biliszczuk J.Hawryszkow P.Hildebrand M.Knawa-Hawryszkow M.Sadowski K.","Allplan;BERD;Budimex;et al.;Maurer;Research and Design Office MOSTY-WROCLAW","International Association for Bridge and Structural Engineering (IABSE)","1st IABSE Online Symposium Wroclaw 2020: Synergy of Culture and Civil Engineering - History and Challenges","7 October 2020 through 9 October 2020",,167847,,9783857481697,,,"English","IABSE Symp., Wroclaw: Synerg. Cult. Civ. Eng. - Hist. Challenges, Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85103440178
"Nessa K., Eggen T.E., Jakobsen S.E.","57194155344;57211568007;23088692600;","Parametrization and BrIM in large infrastructure projects - project study from RV3/25 Norway",2019,"20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report",,,,"1867","1873",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074450569&partnerID=40&md5=a314f8730e77926316c00c1084728c09","A. Aas-Jakobsen AS, Oslo, Norway","Nessa, K., A. Aas-Jakobsen AS, Oslo, Norway; Eggen, T.E., A. Aas-Jakobsen AS, Oslo, Norway; Jakobsen, S.E., A. Aas-Jakobsen AS, Oslo, Norway","RV 3/25 is a large infrastructure project consisting of a new 25 km highway in Hedmark County in Norway. The project is organized as a PPP-project and includes 20 concrete bridges and 8 timber glulam arch bridges. In the project the use of BIM-models and parameterization has been significant and has evolved greatly throughout the project. The work ranged from macro BIM with large coordination models with all disciplines included, to micro BIM-models for bridges including all details needed for construction. For 5 concrete bridges, the BIM-model was the only product delivered to the contractor without producing design or construction drawings. For the 8 glulam arch bridges in timber, parameterization was employed for establishing both the BIM-models and the analysis models. This was vital to achieving the goal of following the strict design schedule with a small design team. It also proved very valuable in the shaping phase of the bridges. Between 80% and 90% of the objects in the finalized BIM-models were included in the parameterization. The product delivered to the contractor was design drawings, most of which were generated directly from the BIM-model, thus benefiting from its advantages. The use of BIM has proved to be cost and time-efficient during design. This paper presents the challenges and benefits of using parameterization and BIM in a large infrastructure project with focus on bridge design. © 20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report. All rights reserved.","BIM; Bridges; BrIM; Infrastructure projects; Parameterization","Arch bridges; Arches; Bridges; Concrete bridges; Concretes; Contractors; Parameterization; Product design; Timber; Analysis models; BrIM; Construction drawings; Coordination model; Design drawings; Infrastructure project; Parametrizations; Time-efficient; Architectural design",,,,,,"Hedmarksveien AS NPRA - Norwegian Public Roads Administration Skanska Norge AS",,"(2018) Trimble, , Quadri 3.0; (2018) Trimble, , Tekla structures; (2019) Rhinoceros 6, , 9, Robert McNeel and Associates; (2019) Grasshopper 1.0.00007, , Robert McNeel and Associates; http://www.ansys.com; Focus Software AS, , http://www.focus.no","Nessa, K.; A. Aas-Jakobsen ASNorway; email: krn@aaj.no",,"Allplan (Gala);et al.;Hardesty and Hanover;Silman;Wiss, Janney, Elstner Associates, Inc.;WSP","International Association for Bridge and Structural Engineering (IABSE)","20th IABSE Congress, New York City 2019: The Evolving Metropolis","4 September 2019 through 6 September 2019",,152767,,9783857481659,,,"English","Congr. IABSE, New York City: Evol. Metropolis - Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85074450569
"Lu R.D., Brilakis I.","57194640091;8837673400;","Digital twinning of existing bridges from labelled point clusters",2019,"Proceedings of the 36th International Symposium on Automation and Robotics in Construction, ISARC 2019",,,,"616","623",,,"10.22260/isarc2019/0082","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071493000&doi=10.22260%2fisarc2019%2f0082&partnerID=40&md5=568e9edaf7887dc96a7fd460df0bba38","Department of Engineering, University of Cambridge, United Kingdom","Lu, R.D., Department of Engineering, University of Cambridge, United Kingdom; Brilakis, I., Department of Engineering, University of Cambridge, United Kingdom","The automation of digital twinning for existing bridges from point clouds has yet been solved. Whilst current methods can automatically detect bridge objects in points clouds in the form of labelled point clusters, the fitting of accurate 3D shapes to detected point clusters remains human dependent to a great extent. 95% of the total manual modelling time is spent on customizing shapes and fitting them to right locations. The challenges exhibited in the fitting step are due to the irregular geometries of existing bridges. Existing methods can fit geometric primitives such as cuboids and cylinders to point clusters, assuming bridges are made up of generic shapes. However, the produced geometric digital twins are too ideal to depict the real geometry of bridges. In addition, none of existing methods have evaluated the resulting models in terms of spatial accuracy with quantitative measurements. We tackle these challenges by delivering a slicing-based object fitting method that can generate the geometric digital twin of an existing reinforced concrete bridge from labelled point clusters. The accuracy of the generated models is gauged using distance-based metrics. Experiments on ten bridge point clouds indicate that the method achieves an average modelling distance smaller than that of the manual one (7.05 cm vs. 7.69 cm) (value included all challenging cases), and an average twinning time of 37.8 seconds. Compared to the laborious manual practice, this is much faster to twin bridge concrete elements. © 2019 International Association for Automation and Robotics in Construction I.A.A.R.C. All rights reserved.","BIM; BrIM; Digital twin; IFC; Point cloud data","Architectural design; Object detection; Reinforced concrete; Robotics; BrIM; Concrete elements; Digital twin; Existing reinforced concrete; Geometric primitives; Irregular geometries; Point cloud data; Quantitative measurement; Geometry",,,,,"Engineering and Physical Sciences Research Council, EPSRC","This research is funded by EPSRC, EU Infravation SeeBridge project and Trimble Research Fund. We thank their support.",,"(2017) 2017 Report Card for America’s Infrastructure, Bridges, , ASCE ASCE; (2015) Network Rail Bridge List, , Network Rail; Buckley, B., Logan, K., The business value of BIM for infrastructure 2017 (2017) Dodge Data & Analytics, pp. 1-68; Lu, R., Brilakis, I., (2017) Recursive Segmentation for as - Is Bridge Information Modelling, , LC3; Valero, E., Semantic 3d reconstruction of furnished interiors using laser scanning and RFID technology (2016) Jr of Comp in Civil Eng, , https://doi.org/10.1061/(ASCE)CP.19435487.0000525; Valero, E., Adán, A., Cerrada, C., Automatic method for building indoor boundary models from dense point clouds collected by laser scanners (2012) Sensors, , https://doi.org/10.3390/s121216099; Oesau, S., Lafarge, F., Alliez, P., Indoor scene reconstruction using feature sensitive primitive extraction and graph-cut (2014) ISPRS, , https://doi.org/10.1016/j.isprsjprs.2014.02.004\; Deng, Mapping between BIM and 3d GIS in different levels of detail using schema mediation and instance comparison (2016) Aut in Constr, , https://doi.org/10.1016/j.autcon.2016.03.006; Xiao, J., Furukawa, Y., Reconstructing the world’s museums (2014) International Jr of Computer Vision, , https://doi.org/10.1007/s11263-014-0711-y; Zhang, Automatic generation of as-built geometric civil infrastructure models from point cloud data (2014) Comput in Civil and Building Eng, pp. 406-413; Ochmann, Automatic reconstruction of parametric building models from indoor point clouds (2016) Computers & Graphics, , https://doi.org/10.1016/j.cag.2015.07.008; Laefer, D.F., Truong-Hong, L., Toward automatic generation of 3d steel structures for building information modelling (2017) Auto in Constr, , https://doi.org/10.1016/j.autcon.2016.11.011; Ji, Exchange of parametric bridge models using a neutral data format (2013) Journal of Computing in Civil Engineering, , https://doi.org/10.1061/(ASCE)CP.19435487.0000286; Amann, Extension of the upcoming IFC alignment standard with cross sections for road design (2015) ICCBEI; Borrmann, (2018) Industry Foundation Classes: A Standardized Data Model for the Vendor-Neutral Exchange of Digital Building Models, , https://doi.org/10.1007/978-3-319-92862-35; Sacks, SeeBridge as next generation bridge inspection: Overview, information delivery manual and model view definition (2018) Aut in Constr, , https://doi.org/10.1016/j.autcon.2018.02.033; Lu, R., Brilakis, I., Middleton, C., Detection of structural components in point clouds of existing RC bridges (2018) CACAIE, , https://doi.org/10.1111/mice.12407; Kobryń, A., Transition curves for highway geometric design (2017) Springer Tracts on Transportations and Traffic, 14. , Cham: Springer International Publishing",,"Al-Hussein M.",,"International Association for Automation and Robotics in Construction I.A.A.R.C)","36th International Symposium on Automation and Robotics in Construction, ISARC 2019","21 May 2019 through 24 May 2019",,150272,,,,,"English","Proc. Int. Symp. Autom. Robot. Constr., ISARC",Conference Paper,"Final","All Open Access, Green",Scopus,2-s2.0-85071493000
"Vilventhan A., Rajadurai R.","55358249800;57204707245;","Application of 4D bridge information model as a lean tool for bridge infrastructure projects: A case study",2018,"IGLC 2018 - Proceedings of the 26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers","2",,,"1229","1239",,,"10.24928/2018/0508","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056776119&doi=10.24928%2f2018%2f0508&partnerID=40&md5=f92e7738ba88db2908cbd9c892c1c760","Department of Civil Engineering, NIT Warangal, India; SRM University, India","Vilventhan, A., Department of Civil Engineering, NIT Warangal, India; Rajadurai, R., SRM University, India","Construction projects require the coordination of multiple organizations. The production flow of these projects is often hampered through sources of wastes such as improper utilization of the skills of the labours and lack of coordination with the multiple organizations involved in these projects. Bridge information modelling provides a powerful platform for visualizing work flow and collaboration between organizations throughout the life cycle of the project. In this paper, 4D bridge information models for a concrete bridge (flyover) construction project was built through integrating 3D BrIM model with the schedule. The developed 4D bridge information model enabled value addition through improved visualization, co-ordination and communication among project participants. This study provides a practical contribution by showing that project stakeholders can use 4D BrIM models as a lean tool to prevent undesirable situations and reduce the overruns, rework and improve the effective utilisation of labours in Bridge construction projects. © IGLC 2018 All Rights Reserved.","4D BrIM model; Bridge information modelling; Coordination; Lean tool; Visualisation","Information theory; Lean production; Life cycle; Visualization; Waste utilization; Bridge constructions; Bridge infrastructure; Construction projects; Coordination; Information modelling; Lean tools; Multiple organizations; Project stakeholders; Bridges",,,,,"Science and Engineering Research Board, SERB: ECR/2017/000002","The authors gratefully acknowledge the financial support by the Science and Engineering Research Board, Department of Science and Technology (DST- SERB), India for this research work (project File No: ECR/2017/000002).",,"Castillo, G., Alarcon, L.F., González, V.A., Implementing lean production in copper mining development projects: Case study (2015) J. Constr. Eng. Manage.; Chen, L., Luo, H., A BIM-based construction quality management model and its applications (2014) Autom. Constr., 46, pp. 64-73; Cheng, J.C.P., Lu, Q., Deng, Y., Analytical review and evaluation of civil information modeling (2016) Autom. Constr., 67, pp. 31-47; Chong, H.Y., Lopez, R., Wang, J., Wang, X., Zhao, Z., Comparative analysis on the adoption and use of BIM in road infrastructure projects (2016) J. Manage. Eng.; Dave, B., Boddy, S., Koskela, L., Challenges and opportunities in implementing lean and BIM on an infrastructure project (2010) Proc. of the 21st Ann. Conf. of the Int'L Group for Lean Construction., , Fortaleza, Brazil; Dubler, C.R., Messner, J.I., Anumba, C.J., Using lean theory to identify waste associated with information exchanges on a building project (2010) Proc. Constr. Res. Congr., pp. 708-716. , ASCE, Banff, Alberta, Canada; Fanning, B., Clevenger, C.M., Ozbek, M.E., Mahmoud, H., Implementing BIM on infrastructure: Comparison of two bridge construction projects (2014) Pract. Period. Struct. Des. Constr.; Gerber, D.J., Becerik-Gerber, B., Kunz, A., Building information modeling and lean construction: Technology, methodology and advances from practice (2010) Proc. of the 18th Ann. Conf. of the Int'L Group for Lean Construction., pp. 1-11. , Technion, Haifa, Israel; Gill, P.S., Application of value stream mapping to eliminate waste in an emergency room (2012) Global Journal of Medical Research, 12 (6), pp. 51-56; Hosseini, S., Nikakhtar, A., Wong, K., Zavichi, A., Implementing lean construction theory to construction processes' waste management (2011) Proc. of Intl. Conf. on Sustainable Design and Construction, pp. 414-420. , ASCE, Kansas City, Missouri; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., An information modeling framework for bridge monitoring (2017) Adv. Eng. Software., 114, pp. 11-31; Jeong, W., Chang, S., Son, J., Yi, J., BIM-integrated construction operation simulation for just-in-time production management (2016) Sustainability, 8 (11), pp. 1-25; Kang, L.S., Kim, H.S., Moon, H.S., Kim, S.K., Managing construction schedule by telepresence: Integration of site video feed with an active nD CAD simulation (2016) Autom. Constr., 68, pp. 32-43; Khanzode, A., (2010) An Integrated Virtual Design and Construction and Lean (IVL) Method for Coordination of MEP, , Center for Integrated Facilities Engineering, Stanford Univ., Stanford, CA; Kim, C., Kim, H., Park, T., Kim, M.K., Applicability of 4D CAD in civil engineering construction: Case study of a cable-stayed bridge project (2011) J. Comput. Civ. Eng., pp. 98-107; Koskela, L., Lean production in construction (1993) Lean Construction, pp. 1-10. , L. Alarcon, ed. 1997. Rotterdam: AA Balkema; Kumar, B., Cai, H., Hastak, M., An assessment of benefits of using BIM on an infrastructure project (2017) Proc. Int. Conf. on Sustainable Infrastruct., pp. 88-95. , ASCE, NewYork; Kumar, J.V., Mukherjee, M., A critical analysis of Building Information Modelling systems used in construction projects (2009) Adv. Eng. Software, 2 (1), pp. 165-169; Li, X., Shen, G.Q., Wu, P., Fan, H., Wu, H., Teng, Y., RBL-PHP: Simulation of lean construction and information technologies for prefabrication housing production (2018) J. Manage. Eng.; Mahalingam, A., Yadav, A.K., Varaprasad, J., Investigating the role of lean practices in enabling BIM adoption: Evidence from two Indian cases (2015) J. Constr. Eng. Manage.; Marzouk, M., Hisham, M., Implementing earned value management using bridge information modeling (2014) KSCE Journal of Civil Engineering, 18 (5), pp. 1302-1313; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) J. Bridge Eng.; Oyegoke, A., The constructive research approach in project management research (2011) International Journal of Managing Projects in Business, 4 (4), pp. 573-595; Porwal, A., Hewage, K.N., Building Information Modeling (BIM) partnering framework for public construction projects (2013) Autom. Constr., 31, pp. 204-214; Sacks, R., Koskela, L., Dave, B.A., Owen, R., Interaction of lean and building information modeling in construction (2010) J. Constr. Eng. Manage., pp. 968-980; Shou, W., Wang, X., Wang, J., Hou, L., Truijens, M., Integration of BIM and lean concepts to improve maintenance efficiency: A case study (2014) Proc. Computing in Civil and Building Engineering, pp. 1449-1456. , ASCE, Orlando, Florida, United States; Tauriainen, M., Marttinen, P., Dave, B., Koskela, L., The effects of BIM and lean construction on design management practices (2016) Procedia Engineering, 164, pp. 567-574; Xiao, R., Lian, Y., Sun, B., Zhao, X., Tang, P., Method of bridge structural analysis based on bridge information modeling (2017) Proc., Computing in Civil Engineering, pp. 326-334. , ASCE, Seattle, Washington; Yin, R.K., Introduction (1994) Case Study Research Design and Methods, pp. 1-15. , K. Yin, ed. 1994. Thousand Oaks, London, NewDelhi: SAGE Publications; Yu, H., Tweed, T., Al-Hussein, M., Nasseri, R., Development of lean model for house construction using (2009) J. Constr. Eng. Manage., pp. 782-790; Zhang, L., Chen, X., Role of lean tools in supporting knowledge creation and performance in lean construction (2016) Procedia Engineering, 145, pp. 1267-1274; Zou, Y., Kiviniemi, A., Jones, S.W., Developing a tailored RBS linking to BIM for risk management of bridge projects (2016) Engineering, Construction and Architectural Management, 23 (6), pp. 727-750",,"Gonzalez V.A.","AFCONS Infrastructure;Digital Construction L and T Construction;Godrej Construction;Shapoorji Pallonji Engineering and Construction","The International Group for Lean Construction","26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers, IGLC 2018","16 July 2018 through 22 July 2018",,140777,,9789380689296,,,"English","IGLC - Proc. Annu. Conf. Int. Group for Lean Constr.: Evol. Lean Constr. Towards Mature Prod. Manag. Across Cult. Front.",Conference Paper,"Final","All Open Access, Bronze",Scopus,2-s2.0-85056776119
"Elgayar A., Jrade A.","57208512726;12804778900;","Integrating Bridge information modeling (BRIM), Bridge Sustainability Rating System (BRSRS), Bridge Environmental Performance Strategy mapping (EPSM) and cost estimating at the conceptual design stage",2017,"6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017","2",,,"937","946",,,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064985501&partnerID=40&md5=bba1f4ce3c423d8728106803cf161b34","Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada","Elgayar, A., Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada; Jrade, A., Department of Civil Engineering, University of Ottawa, Ottawa, ON, Canada","Bridges are crucial infrastructure for urban development as cities rely heavily on various modes of transportation for access and mobility. In an effort to fill the gap in the knowledge and methodology used in the construction of sustainable bridges, a model is developed using the concept of BrIM having the capabilities to develop bridges at the conceptual design stage, which offers ample versatility to influence stakeholders' decisions towards sustainable bridge design. The model incorporates a knowledge-based decision support system and 4 modules namely: BrIM module; the first ever Bridge Sustainability Rating System (BrSRS) module; Bridge Environmental Performance Strategy Map (EPSM) module; and a conceptual cost estimating module. The model takes fundamental data input and processes it through the knowledge-based system established based on MTO's Highway Geometric Design and the Navigational Waterways Clearance guidelines. The sustainability capabilities of the model are broken into two submodules; a BrSRS was developed by using the amalgamation of various existent highways and roads sustainability rating systems and by considering the introduction of bridge design. The system mimics the style of LEED as users can select from a weighted list of sustainable construction activities and materials to accumulate credits towards a sustainability classification. The second includes an EPSM that the forecasts footprints levels of bridge projects based on 5 footprint indicators namely; carbon; water; energy; emissions; and work environment with data obtained from Statistics Canada pertaining to each footprint illustrated on a radar graph. The third module takes the knowledge-based output and presents it in 3D mode via AutoCAD allowing users to alter the drawing's dimensions and accordingly the model reiterates the calculations based on the changes made in the 3D CAD model. The final module generates an approximate cost estimate of the conceptually designed bridge, which is ideal for the feasibility study of the project. © CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017.All rights reserved.","Bridges; Conceptual; Information; Modeling; Sustainability","3D modeling; Artificial intelligence; Bridges; Computer aided design; Conceptual design; Construction industry; Cost benefit analysis; Cost estimating; Decision support systems; Economic analysis; Environmental management; Highway planning; Knowledge based systems; Metals; Models; Urban growth; Urban transportation; Conceptual; Conceptual Cost estimating; Conceptual design stages; Environmental performance; Highway geometric design; Information; Knowledge based decision support systems; Sustainable construction; Sustainable development",,,,,,,,"Amedzuki, A., Meyer, M., Ross, C., (2011) Transportation Planning for Sustainability Guidebook, , 1st ed. Washington, DC: U. S. Federal Highway Administration; Anderson, J., Muench, S., Sustainability trends measured by the greenroads rating system (2013) Transportation Research Record: Journal of the Transportation Research Board, 2357, pp. 24-32; (2008) Sustainability and the Built Environment, , CEM, 1st ed. 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Construction Research Congress, p. 183; Georgoulias, A., (2017) The Envision Rating System for Sustainable Infrastructure: Development, Applications, and the Potential for Lebanon. Ebook, , 1st ed. Beirut: UNDP; Graphics. Drawline method (2017) Msdn. Microsoft. Com, , https://msdn.microsoft.com/enus/library/system.drawing.graphics.drawline(vs.71).aspx; Greenlites (2012) New York State Department of Transportation, , https://www.dot.ny.gov/programs/greenlites; Herva, M., Franco, A., Carraso, E.F., Roca, E., Review of corporate environmental indicators (2011) Journal of Cleaner Production, 19, pp. 1687-1699; (2010) 1-last - Illinois Livable and Sustainable Transportation Rating System and Guide, , http://www.dot.state.il.us/green/documents/I-LASTGuidebook.pdf, Ebook. 1st ed. Illinois: Illinois Department of Transportation; Kroll, E., Condoor, S.S., Jansson, D.G., (2001) Innovative Conceptual Design, , 1st ed. Cambridge: Cambridge University Press; Lansdown, J., The designers' information environment: Some tools for design knowledge manipulation (1989) Civil Engineering Systems, 6 (1-2), pp. 5-10; National BIM standard - United States (2013) Nationalbimstandard. Org, , https://www.nationalbimstandard.org/faqs; Oswald, M.R., McNeil, S., Rating sustainability: Transportation investments in urban corridors as a case study (2010) Journal of Urban Planning and Development, 136 (3), pp. 177-185; Shah, R.K., Dawood, N., Castro, S., Automatic generation of progress profiles for earthwork operations using 4D visualization model (2008) Journal of Information Technology in Construction, 13, pp. 491-506; (1987) Our Common Future: The Report of the World Commission on Environment and Development, , World Commission on Environment and Development WCED, New York: Oxford University Press",,,,"Canadian Society for Civil Engineering","6th CSCE-CRC International Construction Specialty Conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual Conference and General Meeting 2017","31 May 2017 through 3 June 2017",,146894,,9781510878419,,,"English","CSCE-CRC Int. Constr. Spec. Conf. - Held Part Can. Soc. Civ. Eng. Annu. Conf. Gen. Meet.",Conference Paper,"Final","",Scopus,2-s2.0-85064985501