A Novel Whale Optimization Algorithm for the Design of Tuned Mass Dampers under Earthquake Excitations - Luis A. Lara-Valencia; Daniel Caicedo; Yamile Valencia-Gonzalez (Applied Sciences, 2021)
This paper introduces a novel methodology for the optimum design of linear tuned mass dampers (TMDs) to improve the seismic safety of structures through a novel Whale Optimization Algorithm (WOA). The algorithm is aimed to reduce the maximum horizontal peak displacement of the structure, and the root mean square (RMS) response of displacements as well. Furthermore, four additional objective functions, derived from multiple weighted linear combinations of the two previously mentioned parameters, are also studied in order to obtain the most efficient TMD design configuration. The differential evolution method (DEM), whose effectiveness has been previously demonstrated for TMD applications, and an exhaustive search (ES) process, with precision to two decimal positions, are used to compare and validate the results computed through WOA. Then, the proposed methodology is applied to a 32-story case-study derived from an actual building, and multiple ground acceleration time histories are considered to assess its seismic performance in the linear-elastic range. The numerical results show that the proposed methodology based on WOA is effective in finding the optimal TMD design configuration under earthquake loads. Finally, practical design recommendations are provided for TMDs, and the robustness of the optimization is demonstrated.