World Academy of Science, Engineering and Technology
Published August 1, 2015 | Version 10002360
Journal article Open

Determining Earthquake Performances of Existing Reinforced Concrete Buildings by Using ANN

Description

In this study, an Artificial Neural Network (ANN) analytical method has been developed for analyzing earthquake performances of the Reinforced Concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

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References

  • M. H. Arslan and H. H. Korkmaz, "What is to be learned from damage and failure of reinforced concrete structures during recent earthquakes in Turkey? " Engineering Failure Analysis, 14, 1,1-22, 2006.
  • M.H. Arslan " Determination of effective parameteres on failure load and displacement of existing RC buildings using ANN, Natural Hazards and Earth Systems Journal, 9,967-977,2009.
  • TEC-2007, Turkish Earthquake Code. Regulations on structures constructed in disaster regions. Ministry of Public Works and Settlement Ankara. 2007 (In Turkish).
  • Federal Emergency Management Agency FEMA-356, 2000 Prestandard and commentary for seismic rehabilitation of buildings. Washington (DC).
  • ATC-40 1996 Seismic evaluation and retrofit of concrete buildings" Redwood City (CA): Applied Technology Council.
  • I E Bal, "Advanced applications of the P25 - scoring method for the rapid assessment of RC Buildings". Proceedings of the 1st ECEES, Geneva, 3-8 September, 2006.
  • A Yakut, "A Statistical Procedure for the Assessment of Seismic Performance of Existing Reinforced Concrete Buildings in Turkey, 13th World Conference on Earthquake Engineering, 13 WCEE, Vancouver, BC, Canada, Paper No : 687, 2004.
  • H. Boduroglu "Towards a Modified Rapid Screening Method for Existing Medium Rise RC Buildings in Turkey 13th World Conference on Earthquake Engineering, 13 WCEE August 1-6, Vancouver, B.C., Canada, 2004.
  • T., Koyuncu T "A New Method for Rapid Assessment of Performances of Existing RC Buildings Under Earthquake Loading", MSc Thesis, Selcuk University, 2009, Konya, Turkey (In Turkish). [10] M.H. Arslan "An ANN Approaches on Estimating EQ Performance of Existing RC Buildings", NNW Journal, 5, 12, 443-458, 2012. [11] M H. Arslan, "Prediction of torsional strength of RC beams by using different artificial neural network algorithms and building codes" Advances in Engineering Software, 41 (7-8), 946-955, 2009. [12] M.H. Arslan "An evaluation of effective design parameters on earthquake performance of RC buildings using neural networks, Engineering Structures, 32, 1888-1898, 2010. [13] M. H., Arslan "Prediction of force reduction factor (R) of prefabricated Industrial Buildings Using Neural Networks" Structural Engineering and Mechanics, 27 (2), 117-134, 2007. [14] TEC-1998, Turkish Earthquake Code Regulations on structures constructed in disaster regions. Ministry of Public Works And Settlement Ankara. 1998 (In Turkish).