Abstract

Seismic repair of reinforced concrete (RC) bridge columns has been studied extensively during the past several decades; however, few studies have been conducted on the influence of the column repair (member level) on the post-repair performance of bridge structures (system level). In a previous experimental study by the authors, a method was developed to rapidly repair severely damaged RC bridge columns to enable the quick reopening of the bridge to emergency traffic. Thus, a lower limit state was used for the repair design, so that the lateral strength and drift capacity of a repaired RC column with fractured longitudinal bars were not fully restored. In order to investigate whether this reduced performance of the repaired column was acceptable for the overall performance of the repaired bridge, this paper presents a numerical approach to assess the post-repair seismic response of the bridge system. Nonlinear fiber element models were developed using Open System for Earthquake Engineering Simulation (OpenSees) software to simulate the response of the undamaged and repaired columns. Then, a three-span RC bridge structure was selected and modeled with the developed column models, based on which incremental dynamic analysis (IDA) was conducted. Seven scenarios of different combinations of undamaged and repaired columns were analyzed employing 40 ground motion (GM) records. Based on the results, it is shown that the performance of the bridge models containing varied numbers of repaired columns was comparable to that of the bridge containing only original columns with respect to the target system level performance, which confirms the effectiveness of the developed repair method.

Department(s)

Civil, Architectural and Environmental Engineering

Comments

Missouri University of Science and Technology, Grant DTRT06-G-0014

Keywords and Phrases

Bridge; Earthquake; Fiber-reinforced polymer (FRP); Fractured bars; Incremental dynamic analysis (IDA); Reinforced concrete column; Repair

International Standard Serial Number (ISSN)

1873-7323; 0141-0296

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Elsevier, All rights reserved.

Publication Date

01 Apr 2016

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