TMD parameters optimization in different-length suspension bridges using OTLBO algorithm under near and far-field ground motions

Suspension bridges have the extended in plan configuration which makes them prone to dynamic events like earthquake. The longer span lead to more flexibility and slender of them. So, control systems seem to be essential in order to protect them against ground motion excitation. Tuned mass damper or in brief TMD is a passive control system that its efficiency is practically proven. Moreover, its parameters i.e. mass ratio, tuning frequency and damping ratio can be optimized in a manner providing the best performance. Meta-heuristic optimization algorithm is a powerful tool to gain this aim. In this study, TMD parameters are optimized in different-length suspension bridges in three distinct cases including 3, 4 and 5 TMDs by observer-teacher-learner based algorithm under a complete set of ground motions formed from both near-field and far-field instances. The Vincent Thomas, Tacoma Narrows and Golden Gate suspension bridges are selected for case studies as short, mean and long span ones, respectively. The results indicate that All cases of used TMDs result in response reduction and case 4TMD can be more suitable for bridges in near and far-field conditions.