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Robust design optimization of friction dampers for structural response control
It is known that the use of passive energy dissipation devices, as friction dampers, reduces considerably the dynamic response of a structure subjected to earthquake ground motions. However, the parameters of each damper as well as the best placement of these devices remain difficult to determine. Thus, in this paper, robust design optimization of friction dampers to control the structural response against earthquakes is proposed. In order to take into account uncertainties present in the system, some of its parameters are modeled as random variables, and consequently, the structural response becomes stochastic. To perform the robust optimization of such system, two objective functions are simultaneously considered: the mean and variance of the maximum displacement. This approach allows finding a set of Pareto-optimal solutions. A genetic algorithm, the NSGA-II (Nondominated Sorting Genetic Algorithm), is applied to solve the resulting multi-objective optimization problem. For illustration purposes, a six-story shear building is analyzed. The results showed that the proposed method was able to reduce the mean maximum displacement in approximately 70% and the variance of the maximum displacement in almost 99% with only three dampers.
Robust design optimization of friction dampers for structural response control
It is known that the use of passive energy dissipation devices, as friction dampers, reduces considerably the dynamic response of a structure subjected to earthquake ground motions. However, the parameters of each damper as well as the best placement of these devices remain difficult to determine. Thus, in this paper, robust design optimization of friction dampers to control the structural response against earthquakes is proposed. In order to take into account uncertainties present in the system, some of its parameters are modeled as random variables, and consequently, the structural response becomes stochastic. To perform the robust optimization of such system, two objective functions are simultaneously considered: the mean and variance of the maximum displacement. This approach allows finding a set of Pareto-optimal solutions. A genetic algorithm, the NSGA-II (Nondominated Sorting Genetic Algorithm), is applied to solve the resulting multi-objective optimization problem. For illustration purposes, a six-story shear building is analyzed. The results showed that the proposed method was able to reduce the mean maximum displacement in approximately 70% and the variance of the maximum displacement in almost 99% with only three dampers.
Robust design optimization of friction dampers for structural response control
Miguel, Leticia Fleck Fadel (author) / Miguel, Leandro Fleck Fadel (author) / Lopez, Rafael Holdorf (author)
Structural Control and Health Monitoring ; 21 ; 1240-1251
2014
12 Seiten
Article (Journal)
English
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