journal article·2020-01-31Open access

A Probabilistic Capacity Model and Seismic Vulnerability Analysis of Wall Pier Bridges

Libo Chen, Yi Tu, Leqia He

Applied Sciences· Volume 10· Issue 3

Abstract

This study aims to establish a probabilistic capacity model of a wall pier under various damage states, and the seismic vulnerability of a typical wall pier bridge is studied. The finite element analysis of the wall pier is carried out by using the layered shell element, and its accuracy is verified through the comparison with the experimental results. A series of wall pier samples are generated based on the survey data, and the corresponding finite element models are established. The hysteresis analysis is implemented to obtain the displacement drift ratio of each seismic performance point. A candidate capacity model with various factors is proposed, and the unknown parameters are estimated and filtered by the Bayesian method. One hundred and twenty bridge samples of a benchmark bridge are generated by considering the uncertainty of parameters, and the finite element models are established. The bridge samples and ground motions were matched by one-to-one correspondence for the nonlinear time history analysis, and seismic vulnerability models of bridge components and system are obtained. The results showed that the in-plane capacity of wall piers is mainly affected by axial compression ratio, shear span ratio, and vertical reinforcement ratio. The wall pier shows excellent behavior in the earthquakes. The capacity models of wall piers can be used for evaluating the damage states of wall piers, and obtaining the seismic vulnerability model of wall piers bridges to be used for future seismic risk assessment and retrofit prioritization.
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Research context

OpenAlex topics: Seismic Performance and Analysis · Structural Health Monitoring Techniques · Structural Behavior of Reinforced Concrete

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Civil Engineering, Fuzhou University, Fujian 350116, China

Funding

National Natural Science Foundation of China · China Postdoctoral Science Foundation

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