%A Rostami,Parisa
%A Mahsuli,Mojtaba
%D 2018
%J Frontiers in Built Environment
%C
%F
%G English
%K Steel plate shear wall,Door opening,Stiffener,probabilistic model,reliability analysis,decision analysis
%Q
%R 10.3389/fbuil.2018.00059
%W
%L
%N 59
%M
%P
%7
%8 2018-October-31
%9 Original Research
%#
%! Risk-Optimal Arrangement of Stiffeners
%*
%<
%T Risk-Optimal Arrangement of Stiffeners in Steel Plate Shear Walls With Door Opening
%U https://www.frontiersin.org/article/10.3389/fbuil.2018.00059
%V 4
%0 JOURNAL ARTICLE
%@ 2297-3362
%X Placement of steel plate shear walls (SPSW) in the building cores around the elevators and stairs necessitates door-type openings in these systems. Because of large dimensions of door openings, the energy dissipation capacity drops significantly and thus, the probability of out-of-plane buckling under lateral load increases. Accordingly, introducing stiffeners around the opening increases the amount of dissipated energy and improves the performance of the SPSW system. This paper evaluates the seismic risk of SPSW systems with different arrangements of stiffeners around the door opening. Risk, in this context, denotes the probability of failure times the cost of failure of a given SPSW. The probability of failure is computed through a finite element reliability analysis in which material properties, element geometries, and the lateral force are random variables. The failure event is described by a limit-state function as the exceedance of the drift ratio of the SPSW from a prescribed threshold. The drift ratio is computed by subjecting the finite element model to nonlinear static analysis in ABAQUS. The reliability analysis is conducted for a variety of single-story SPSW models having door opening with different arrangements of stiffeners and also for a typical SPSW model without opening as a base model. Next, decision analysis is employed to identify the optimal arrangement, i.e., the one that is associated with the minimum risk. Finally, the effect of risk aversion on the optimal decision is studied by introducing risk-averse utility functions with different degrees of risk aversion.