Optimal design of dampers in seismic applications utilizing the MOPSO algorithm

New technological developments in engineering present an opportunity for improved efficiency in structural design through optimization. High-performance computing resources reduce the time needed for computational calculations. Concurrently, optimization algorithms have greatly evolved to provide the opportunity to solve complicated nonlinear engineering problems that typically include several interrelated, and often conflicting, objectives under a set of constraints. This research proposes a method for the optimal design of viscous dampers in seismic applications utilizing the multi-objective particle swarm optimization (MOPSO) algorithm. The MOPSO, with its inherent metaheuristic approach and geographically-based adaptive grids, effectively discovers global and diverse non-convex solutions. To further improve the efficiency and quality of the search in the milieu of an engineering application, we have extended MOPSO by introducing constraints on objective functions and implementing parallel computing. Additionally, this research provides recommendations on how to efficiently generate reliable solution sets by proper selection of objective (cost) functions and adequate set-up of MOPSO input parameters. These recommendations are derived from a series of sensitivity studies. The proposed method is verified by utilizing an engineered solution of a viscously damped moment frame. It was found that under the same set of constraints and performance objectives, MOPSO produces a solution set that contains outcomes that are superior to the engineered solutions. For example, the MOPSO solution set contains outcomes that reduce demands on dampers (force and stroke) while maintaining engineering demand parameters, generating construction savings as a result of the reduced manufacturing costs of dampers.

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