Optimization of NTMDI parameters using metaheuristic algorithms and spectral analysis for seismic response mitigation

Abstract This study explores the optimization of parameters for a Nonlinear Tuned Mass Damper Inerter (NTMDI) system by employing six advanced optimization algorithms: Slim Mould Algorithm (SMA), Beluga Whale Optimization (BWO), Artificial Bee Colony (ABC), Starfish Optimization Algorithm (SFOA), Seagull Optimization Algorithm (SOA), and Dragonfly Algorithm (DA). The main goal is to minimize the maximum roof displacement of a 15-story shear frame structure subjected to seismic loading, which serves as the key target function for the Optimization. To represent realistic earthquake conditions, 17 ground motion records from FEMA P-695, encompassing a broad range of earthquake characteristics, were utilized. These records were adjusted in accordance with ASCE 41 − 17 criteria to ensure alignment with structural design specifications. In a departure from prior studies, spectral analysis was implemented to optimize the NTMDI, presenting a novel approach. The optimization process adjusts the NTMDI parameters based on the established target function, with subsequent analyses assessing additional structural responses such as roof acceleration and base shear. Nonlinear dynamic analysis was conducted using OpenSees to compare the performance of the NTMDI system both before and after optimization. The findings reveal that optimizing the NTMDI parameters significantly reduces roof displacement, roof acceleration, and base shear, thus improving the overall seismic performance of the structure. Each algorithm showcases unique attributes in achieving optimal responses, offering valuable insights into their comparative effectiveness. This research underscores the potential of optimized NTMDI systems to enhance building resilience against seismic loads.