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Published November 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Revolutionizing Structural Engineering: A Review of Digital Twins, BIM, and AI Applications

Creators

  • 1. Department of Civil Engineering, University of Gondar, Gondar, Ethiopia.

Description

Abstract: The structural engineering industry is at a pivotal juncture, driven by the integration of cutting-edge digital tools that are transforming traditional design, analysis, and construction practices. This review provides a comprehensive examination of three major technological advancements—Digital Twins, Building Information Modeling (BIM), and Artificial Intelligence (AI)—that are reshaping the landscape of structural engineering. By synthesizing recent research and case studies, we assess the current applications, benefits, and challenges associated with these technologies, along with their synergistic effects when used in tandem. Digital Twins enable real-time data monitoring and predictive analysis, allowing for enhanced lifecycle management and operational efficiency of infrastructure systems. BIM improves design coordination and collaboration, reducing errors and optimizing resource allocation throughout the project lifecycle. AI, meanwhile, introduces powerful data processing capabilities, enabling predictive maintenance, design optimization, and automated decision-making processes that enhance both safety and performance. Our findings indicate that while these technologies offer immense potential, there are significant implementation barriers, including data privacy concerns, high initial costs, and the need for skilled labor capable of managing complex digital tools. Future directions emphasize the need for standardized data integration protocols, advancements in digital twin modeling for structural health monitoring, and a push toward AI-driven automation in structural analysis and safety inspections. This review provides insights for engineers, researchers, and industry stakeholders aiming to leverage these technologies to achieve more sustainable, efficient, and resilient structural systems, ultimately guiding the field of structural engineering into a more digital, data-centric future.

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Additional details

Identifiers

DOI
10.54105/ijse.B1321.04021124
EISSN
2582-922X

Dates

Accepted
2024-11-15
Manuscript received on 05 October 2024 | Revised Manuscript received on 27 October 2024 | Manuscript Accepted on 15 November 2024 | Manuscript published on 30 November 2024.

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