Reliability-Based Design Optimization of Tuned Mass Damper for Tall Buildings Considering Uncertainty of Soil-Structure Interaction

Tuned mass dampers (TMDs) are widely used to mitigate vibration in tall structures subjected to forces such as seismic activity and wind. Despite extensive research on TMD design, implementation, and structural vibration control, determining the optimal parameters for TMDs remains a challenging task. For instance, ignoring the potential effects of soil-structure interaction (SSI) may result in suboptimal design parameters of TMDs, especially for tall buildings. This is why soil-structure parameters were recently considered for a more realistic optimum design of TMDs. Due to variable soil characteristics, ensuring system reliability requires a probabilistic approach. This paper presents a method for optimizing TMD parameters through both deterministic and probabilistic frameworks, utilizing metaheuristic algorithms and reliability-based design optimization (RBDO) techniques. The objective function of this study is the transfer function of the top-story displacement. Mass, stiffness, and damping of the TMD are considered as design variables. Five different metaheuristic algorithms are comparatively employed to seek the most efficient solution of the deterministic optimization problem. Finally, the TMD optimum parameters considering uncertainty in soil parameters are identified by a novel double-loop combination of RBDO and chaos game optimization (CGO). The procedure's effectiveness is tested on a 40-story shear building with SSI considerations. Results indicate that SSI uncertainty significantly impacts the optimal TMD design for tall buildings. The accuracy of the RBDO-CGO approach is validated through performance metrics under various ground motions.