Progressive collapse design optimization of RC frame structures using high-performance computing

Abstract

Structural progressive collapse design is essential for improving the robustness of structures against accidental local loads. In this study, a design framework was developed for optimizing the nonlinear dynamic progressive collapse design of reinforced concrete (RC) frame structures. An objective function featuring both structural response and material consumption was combined with a cluster computing technology and the global optimization algorithm to optimize a structure for resisting progressive collapse. A four-story RC frame was taken as an example. The design framework was adopted to achieve precise control of its structural progressive collapse response with optimization of the material consumption to the maximum extent. The design outcomes of global and sequential design schemes, including structural resistance and material consumption, were compared to devise the best optimized progressive collapse design strategy. This research can serve as a reference for the development of efficient and accurate structural progressive collapse design methods.