A numerical framework for enhancing the seismic resilience of urban infrastructure in clayey basins using finite element modeling and AI optimization

Due to dynamic soil-structure interaction amplifying ground shaking and inflicting considerable damage on buildings, bridges, and roads, urban infrastructure in clayey basins is beset with its own seismic risk. This paper discusses the concept of a MATLAB-based computational framework to assess and optimize the seismic resilience of urban infrastructure in such environments. The proposed framework combines finite element modeling (FEM) for soil-structure interaction with artificial intelligence (AI)-oriented optimization techniques to simulate the seismic response of different infrastructure systems under different earthquake magnitudes (M w 6.0, M w 7.4, and M w 8.0). The study considers the construction’s structural displacement, stress, and failure modes under seismic loading and optimizes retrofitting and soil stabilization strategies using genetic algorithms and particle swarm optimization. The results point toward the effectiveness of retrofitting strategies, including base isolation and shear walls, to limit displacement and damage. AI-based sensitivity analysis has singled out key parameters influencing seismic resilience; real earthquake data validates model predictions. This study provides a systemic approach toward enhancing the seismic resilience of urban infrastructure in clayey basins, with information applicable for earthquake risk mitigation and infrastructure design.