Enhancing resilience of highway bridges through seismic retrofit

桥(图论) 弹性(材料科学) 地震灾害 抗震改造 龙卷风 工程类 脆弱性(计算) 结构工程 增量动力分析 码头 地震情景 诱发地震 地震风险 土木工程 地震分析 计算机科学 地质学 钢筋混凝土 医学 海洋学 物理 计算机安全 内科学 热力学
作者
Ashok Venkittaraman,Swagata Banerjee
出处
期刊:Earthquake Engineering & Structural Dynamics [Wiley]
卷期号:43 (8): 1173-1191 被引量:76
标识
DOI:10.1002/eqe.2392
摘要

SUMMARY The present study evaluates seismic resilience of highway bridges that are important components of highway transportation systems. To mitigate losses incurred from bridge damage during seismic events, bridge retrofit strategies are selected such that the retrofit not only enhances bridge seismic performance but also improves resilience of the system consisting of these bridges. To obtain results specific to a bridge, a reinforced concrete bridge in the Los Angeles region is analyzed. This bridge was severely damaged during the Northridge earthquake because of shear failure of one bridge pier. Seismic vulnerability model of the bridge is developed through finite element analysis under a suite of time histories that represent regional seismic hazard. Obtained bridge vulnerability model is combined with appropriate loss and recovery models to calculate seismic resilience of the bridge. Impact of retrofit on seismic resilience is observed by applying suitable retrofit strategy to the bridge assuming its undamaged condition prior to the Northridge event. Difference in resilience observed before and after bridge retrofit signified the effectiveness of seismic retrofit. The applied retrofit technique is also found to be cost‐effective through a cost‐benefit analysis. First order second moment reliability analysis is performed, and a tornado diagram is developed to identify major uncertain input parameters to which seismic resilience is most sensitive. Statistical analysis of resilience obtained through random sampling of major uncertain input parameters revealed that the uncertain nature of seismic resilience can be characterized with a normal distribution, the standard deviation of which represents the uncertainty in seismic resilience. Copyright © 2013 John Wiley & Sons, Ltd.

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