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Optimal design of hysteretic dampers connecting adjacent structures using multi-objective genetic algorithm and stochastic linearization method
Authors:Seung-Yong Ok   Junho Song  Kwan-Soon Park  
Affiliation:

aDepartment of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, IL 61801, United States

bDepartment of Architectural Engineering, Dongguk University, South Korea

Abstract:An optimal design method is proposed for nonlinear hysteretic dampers that enhance the seismic performance of two adjacent structures. The proposed method employs nonlinear random vibration analyses by use of a stochastic linearization method in order to efficiently estimate the stochastic responses of coupled buildings without performing numerous nonlinear time-history analyses. The main objectives of the optimal design are not only to reduce the seismic responses but also to minimize the total cost of the damper system. To deal with such conflicting objectives, a multi-objective genetic algorithm is adopted. This approach systematically obtains a set of Pareto optimal solutions that are non-inferior or non-superior to each other. The process for choosing a reasonable design from the optimal surface of Pareto solutions is also discussed. As an example of a nonlinear hysteretic damping device, this study considers passive-type magneto-rheological dampers with fixed input voltages. The optimal voltages and numbers of installed dampers are simultaneously determined. The robustness of the optimal design against uncertain characteristics of ground motions is examined through extensive nonlinear random vibration analyses.
Keywords:Adjacent structures   Genetic algorithm   Magneto-rheological damper   Multi-objective optimization   Hysteretic damper   Nonlinear random vibration analysis   Optimal control   Stochastic linearization method
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