Abstract

This paper presents the probabilistic seismic demand analysis with respect to seismic input uncertainty only of a 3-D reinforced concrete building model subjected to three-component earthquake ground motion excitation. Response history analyses are carried out on a nonlinear frame model. Probability distributions are assumed for the ground motion Intensity Measure (IM) taken as the linear 5% damped elastic spectral acceleration at the fundamental period of the structure. Part of the framework of the so-called Performance Based Earthquake Engineering (PBEE) methodology developed by the Pacific Earthquake Engineering Research (PEER) Center is used in this study. This paper has two main objectives. The first objective is to perform a probabilistic demand analysis of an existing building conditional on the ground motion IM. The second objective is to use the results obtained from this existing testbed, with real-world complexities, to demonstrate the deficiency of the PEER PBEE methodology when using a scalar ground motion IM for 3-D structural models. This last objective shows the need for improving the definition of the seismic IM in the PBEE methodology for the general case of 3-D structures subjected to multi-directional input ground motions. To this effect, an ensemble of natural ground motion records is used to represent the inherent randomness in ground motion time-histories (i.e., record-to-record variability). The statistical correlation of different Engineering Demand Parameters (EDPs) with a set of IMs, taken as the 5% damped spectral accelerations at different periods for two horizontal ground motion components, is investigated in order to assess the dispersion in the EDPs due to different ground motion records. Some statistical correlation coefficients are found to be high, indicating that the dispersion of the EDPs is heavily influenced by the spectral content at periods different from the fundamental period. This result points to the need for using vector-valued ground motion Intensity Measures in the PBEE methodology currently proposed by PEER.

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