Computational Design of High-Performance U-Shaped Seismic Dampers Using Statistical Optimization.

Passive metallic dampers are critical for the seismic resilience of structures, yet their design has historically relied on incremental modifications rather than systematic optimization. This study introduces and validates a data-driven workflow that combines the Taguchi method with nonlinear finite element analysis to design novel U-shaped seismic dampers (USSDs) with superior performance. Building on an experimentally validated computational model from prior work, an L25 orthogonal array was employed to systematically investigate key geometric parameters, with an Analysis of Variance (ANOVA) identifying height, thickness, and length as the most influential factors on damper behavior. This statistical insight guided the creation of two optimized models, with the UD-M4 model demonstrating a nearly seven-fold increase in total energy dissipation (340.6 kJ vs. 51.2 kJ), a nine-fold increase in stiffness, and a 50% improvement in deformability compared to the commercial UD-40 baseline. The primary contribution of this work is the validation of an efficient statistical-computational methodology for the performance-based design of next-generation seismic protection devices, moving beyond traditional trial-and-error approaches.