Performance-based seismic design optimization of reinforced concrete structures with multiple ground motions via surrogate model

Abstract

To address the challenge of designing structures that can withstand seismic loads and simplify the design process, a novel optimization formulation considering performance targets is defined in this paper. Multiple ground motions are considered to optimize structures under earthquake excitations. Single and seven ground motions are employed to perform nonlinear time history analysis, and the resulting responses are utilized as the objective function for the optimization problem. Subsequently, a Kriging model is adopted to approximate the objective function. During the model construction process, an enhanced Latin hypercube sampling strategy with mutation and evolutionary operation is employed, conditional likelihood approach is used to update the kriging model, and genetic algorithm (GA) is employed to search for the optimal solution. Finally, the methodology is applied to three 2-dimensional (2D) examples and a 3-dimensional (3D) example to demonstrate its effectiveness. The results show the Kriging model-assisted methodology can significantly reduce the computational burden associated with function evaluations, while simultaneously identifying optimum designs that improve the dynamic responses of structures. This highlights the effectiveness of the proposed methodology in mitigating the effects of earthquakes and reducing dynamic responses, which is crucial for preventing structural damage and collapse. Furthermore, the results emphasize the importance of considering multiple ground motions when optimizing structures under earthquakes.