Enhancing Seismic Resilience of Steel Frames Through GA-Optimized Knee Element Sizing

As earthquakes pose an ever-growing threat to urban infrastructure,enhancing the seismic performance of steel frames remains a critical challenge. This study explores the potential of knee-braced steel frames, where knee elements act as dissipative zones, optimized for energy absorption using a genetic algorithm (GA). By focusing on the cross-sectional area of these elements as the design variable, the research aims to maximize hysteretic energy dissipation under seismic loading an essential metric for mitigating structural damage. The methodology integrates finite element simulations to model the nonlinear response of the frames, coupled with a GA to refine the knee element sizing iteratively. Seismic performance is evaluated using dynamic loading conditions representative of earthquake-prone regions, ensuring practical relevance. Results reveal that optimized cross-sectional configurations significantly enhance energy dissipation capacity, improving ductility without compromising overall frame stability. The approach also demonstrates computational efficiency, making it feasible for real-world design applications. Beyond its technical contributions, this work underscores the power of evolutionary algorithms in solving complex structural optimization problems, offering a scalable framework for tailoring dissipative systems to specific seismic demands. These findings pave the way for more resilient steel structures, providing engineers with a tool to balance safety and economy in earthquake-resistant design.