Analysis of Structural Behavior under Seismic Loads and Optimization of Retrofitting Using Artificial Intelligence

In recent years, due to the significant increase in earthquake hazards and the resulting damages, the analysis and retrofitting of structures under seismic loads have gained considerable importance. Structures during earthquakes are subjected to complex nonlinear forces that require advanced methods for accurate analysis and effective retrofitting. This paper first comprehensively reviews the dynamic behavior of structures under seismic loads and discusses the challenges in their analysis. Then, leveraging modern artificial intelligence (AI) technologies such as artificial neural networks, genetic algorithms, and multi-objective optimization methods, new approaches for improving analysis accuracy and retrofitting design are presented. These algorithms can simultaneously optimize various structural parameters, enhancing performance prediction accuracy while significantly reducing computational time and costs. The application of AI not only increases the efficiency of retrofitting methods but also enables innovative and optimized solutions. Practical examples of structural optimization using these algorithms are introduced and analyzed to clearly demonstrate the impact of AI in seismic retrofitting. The study concludes that AI can play a key role in developing novel retrofitting strategies for structures.

کلیدواژه ها:

Seismic analysis ، Retrofitting ، Optimization ، Artificial intelligence ، Neural networks ، Genetic algorithms