Optimisation de la distribution des voiles dans les structures mixtes en B. A. soumises au séisme

Abstract

Shear walls are crucial for enhancing the stability and safety of buildings in seismic regions by resisting lateral forces and reducing earthquake damage. Traditionally, optimizing shear walls in reinforced concrete (RC) structures has involved a trial-and-error process where designers select wall distribution, adjust thickness incrementally, and verify security criteria. This method, heavily reliant on experience, is time-consuming and often fails to achieve cost-effective or highperformance designs. A parametric study, using the nonlinear static pushover analysis, was first conducted to examine the effect of shear wall placement, revealing that centralizing shear walls amplifies induced forces, leading to overly conservative designs. Conversely, distributing shear walls at the building’s periphery significantly minimizes shear forces and bending moments, resulting in optimal seismic performance with minimal material use. Building on these findings, a comprehensive framework using Python and SAP2000 API was developed to automate the optimization of shear wall distribution and thickness using optimization algorithms and Artificial Intelligence. This framework addresses the inefficiencies of traditional trial-and-error methods, which rely on designers incrementally adjusting wall thickness based on experience. By automating the iterative design process, the framework reduces design time and effort, offering a flexible solution applicable to both regular and irregular building structures while adhering to the latest Algerian seismic code. Validated through case studies, the framework achieved cost savings of approximately 17%, ensuring optimal shear wall configurations that enhance building safety without increasing construction costs. This research introduces a robust, adaptable tool that revolutionizes the design of earthquake-resistant RC buildings, offering significant structural and economic benefits.