Analysis and optimization of a nonlinear dual‐mode floor isolation system subjected to earthquake excitations
Analysis and optimization of a nonlinear dual‐mode floor isolation system subjected to earthquake excitations
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DOI:
10.1002/eqe.3449
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发表时间:
2021-04
影响因子:
4.5
通讯作者:
P. Bin;M. H. Tehrani;M. Nisa;P. S. Harvey;A. Taflanidis
中科院分区:
文献类型:
--
作者:
P. Bin;M. H. Tehrani;M. Nisa;P. S. Harvey;A. Taflanidis
Floor isolation systems (FISs) are used to mitigate earthquake‐induced damage to sensitive building contents. Dynamic coupling between the FIS and primary structure (PS) may be nonnegligible or even advantageous when strong nonlinearities are present under large isolator displacements. This study investigates the influence of dynamic coupling between the PS and FIS in the presence of nonsmooth (impact‐like) nonlinearity in the FIS under intense earthquakes. Using component mode analysis, a nonlinear reduced order model of the combined FIS–PS system is developed by coupling a condensed model of the linear PS to the nonlinear FIS. A bilinear Hertz‐type contact model is assumed for the FIS, with the gap and the impact stiffness and damping providing parametric variation. The performance of the FIS–PS system is quantified through a multiobjective, risk‐based design criterion considering both the total acceleration sustained by the isolated mass under a service‐level earthquake and the interstory drift under a maximum considered earthquake. The results of a parametric study shed light on understanding the valid range that the decoupled approach can be reliably applied for nonlinear FISs experiencing impacts. It is also shown that the nonlinear FIS can be tuned in such a way to mitigate seismic responses of the supporting PS under strong shaking, in addition to protecting the isolated mass at low to moderate shaking. The FIS, therefore, functions as a dual‐mode vibration isolator/absorber system, with displacement‐dependent response adaptation. Guidelines to the optimal tuning of such a dual‐mode system are presented based on the risk‐based stochastic design optimization.