AI-Supported Seismic Performance Evaluation of Structures: Challenges, Gaps, and Future Directions at Early Design Stages - Ekici, Berk; Ak, Fatma; Demir, Uğur; Ekici, Berk; Demir, Ugur (Elsevier Sci Ltd, 2026)
This study reviews 91 journal articles that intersect with earthquake-resistant building design and artificial intelligence (AI)- based modeling, utilizing machine learning, deep learning, and metaheuristic optimization algorithms. Previous reviews on AI applications have examined engineering problems without considering the impact of architectural design parameters and structural irregularities on seismic performance. This review discusses the role of AI in integrating architectural design variables and seismic performance objectives, highlighting challenges, gaps, and future directions in the early design phase. The reviewed articles demonstrate that AI is successful in addressing seismic performance objectives; however, a holistic framework for assessing architectural and structural variables has not been presented. The review highlights key findings, gaps, and future directions for those involved in earthquake-resistant building design utilizing AI.
Keywords: Computational Design; Earthquake; Machine Learning; Optimization; Seismic Performance