Abstract

ABSTRACT The purpose of this study is to explore the optimum seismic IMs for the probabilistic seismic demand model of subway stations subjected to near-fault seismic excitations with velocity pulses, and establish the seismic fragility curves based on the optimum seismic IMs. A two-storey three-span subway station is used herein as a representative case study for the cut-and-cover rectangular underground structure. Because the dynamic response of underground structure is closely related to the properties of the surrounding soil/rock, four typical classes of engineering sites covering Classes I to IV are selected in accordance with the Chinese code for seismic design of urban rail transit structures. Nonlinear time history analyses considering soil–structure interaction (SSI) are conducted on the two-dimensional numerical model of the subway station embedded in four different engineering sites. An ensemble of 121 near-fault seismic excitations with velocity pulses is used in seismic dynamic analyses so as to define the optimum IMs. Each seismic excitation is converted into the free field load at artificial boundaries of discretized numerical model of SSI system. The efficacy of 21 commonly used ground motion IMs for predicting seismic response of shallowly buried subway stations is discussed in this study. Four different criteria characterizing the adequacy of IMs, including efficiency, practicality, proficiency and sufficiency, are used in identification of the optimum IMs, on account of the statistical regression results of the selected IMs and engineering demand parameters of the subway station structure measured by maximum inter-story displacement ratio. It is concluded that for engineering sites of Classes I and II, the sustained maximum acceleration followed by peak ground acceleration are the optimum IMs, and for engineering sites of Classes III and IV, the velocity spectrum intensity is the optimum IM. Finally, based on the optimized seismic IMs, the fragility curves of subway station embedded in different site classes are developed in this study.

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