Optimum Robust Design of ۲D Steel Moment-Resisting Frames Using Enhanced Vibrating Particles System Algorithm

This study presents a robust design optimization (RDO) approach for ۲D steel moment-resisting frames, addressing uncertainties in material properties and external loads. The study considers special moment frames with high ductility capacity (R=۸) designed according to American Institute of Steel Construction Load and Resistance Factor Design (AISC-LRFD) specifications. The objective is to minimize both structural weight and the robustness index, defined as the standard deviation of roof displacement. The Enhanced Vibrating Particles System (EVPS) algorithm is employed to solve the optimization problem, while Monte Carlo simulation (MCS) is used to model uncertainties. Three benchmark frames (۱۰, ۱۵, and ۲۴ stories) demonstrate the effectiveness of the proposed methodology. Results show a ۵۰-۶۰% reduction in roof displacement variability compared to deterministic optimization, with only a ۲۰-۳۰% increase in structural weight. For the ۱۰-story frame with β=۰.۴, the approach achieved a ۶۷% reduction in standard deviation (from ۰.۴۸۴ to ۰.۱۵۹) with a ۷۴% weight increase (from ۶۳,۸۴۸ lb to ۱۱۱,۷۰۱ lb). The robustness index coefficient (β) is identified as a key parameter for controlling the weight-robustness trade-off, allowing designers to tailor solutions based on project requirements. The study provides a practical framework for improving steel frame reliability under real-world conditions.

Keywords:

Enhanced Vibrating Particles System , Robust design optimization , Uncertainty , Steel moment resisting frame , Monte Carlo simulation