Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network

Abstract

As a lateral load-bearing system, the steel plate shear wall (SPSW) is utilized in different structural systems that are susceptible to seismic risk and because of functional reasons SPSWs may need openings. In this research, the effects of rectangular openings on the lateral load-bearing behavior of the steel shear walls by the finite element method (FEM) is investigated. The results of the FEM are used for the prediction of SPSW behavior using the artificial neural network (ANN). The radial basis function (RBF) network is used to model the effects of the rectangular opening in the SPSW with different plate thicknesses. The results showed that the opening leads to reduced load-bearing capacity, stiffness and absorbed energy, which can be precisely predicted by employing RBF network model. Besides, the suitable relative area of the opening is determined.

Keywords

• artificial neural network
• steel shear wall
• finite element method
• opening
• radial basis function