Cyclic loading behavior of novel internally stiffened double steel plate shear wall

Abstract

In this paper, a novel Internally Stiffened Double Steel Plate Shear Wall (ISD-SPSW) is proposed based on the concept of improving the buckling mode of steel plates and enhancing the lateral resistance of steel plate shear wall (SPSW). The ISD-SPSW consists of double outer steel plates on both sides, inner stiffened rib plates, and boundary members. The seismic behavior of ISD-SPSW was investigated through tests and numerical simulations. Five ISD-SPSW specimens with different heights of the wall, thickness of the outer steel plate and boundary member, and different numbers of internally stiffened steel plates were investigated in cyclic loading tests. The performance indexes such as hysteresis curves, strain curves, and skeleton curves of ISD-SPSW were obtained. The finite element model of ISD-SPSW was established and verified by the test results. The test results reveal two distinct failure modes for the ISD-SPSW. The first mode involves the failure of diagonal tension bands, which is a result of local buckling in the outer steel plates. The second mode is characterized by the overall instability of the shear wall, resulting from the out-of-plane deformation of the boundary members. Lowering the height of the wall can markedly improve the load-bearing capacity and out-of-plane stability of ISD-SPSW. Increasing the thickness of the outer steel plate can improve the ultimate load-bearing capacity, but has adverse effect on the boundary members. Reducing the thickness of the boundary member can significantly reduce the load-bearing capacity and seismic performance. Reducing the number of inner stiffened rib plates decreases the shear load-bearing capacity and energy dissipation capacity. The ductility coefficient of most specimens is greater than 3.0, indicating that the ISD-SPSW has good ductility. In addition, the results of the established finite element model are in good agreement with the test results, which verifies the accuracy of the model.