Optimized design under uncertainties of a passive vibration control system for highway bridges considering the vehicle-bridge-pavement interaction

Dynamic bridge analysis requires considering factors like material properties, vehicle velocity, mass, suspension, and road roughness, all of which are crucial for understanding the bridge’s behavior. Excessive vibrations can cause discomfort, reduce the structure’s service life, and even lead to collapse. Tuned Mass Dampers (TMDs) offer a reliable and economical solution to mitigate these vibrations. This work introduces a comprehensive methodology for optimizing TMDs, addressing the coupled vibration challenges across all involved systems (Bridge-Vehicle-Pavement-TMD) while incorporating uncertainties, making the design more robust against parameter variations. Three vehicle models are analyzed, including simulations of pavement roughness and obstacles at the bridge entrance. Uncertainties are accounted for using Monte Carlo simulation, enhancing the reliability of the results. The TMD parameters were designed using the HBA algorithm, and to further improve efficiency, the objective function was parallelized, resulting in a 60% reduction in computation time per iteration compared to a fully sequential code. This optimization under uncertainty led to a reduction in the mean maximum bridge displacement by over 7.5% on uneven pavement and 14.4% with obstacles. This robust optimization approach, combined with parallel processing, provides a useful tool to assist designers with the project of new structures or propose a solution to extend the service life of the existing ones.