Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks
American Journal of Civil Engineering
Volume 4, Issue 4, July 2016, Pages: 174-184
Received: Jun. 14, 2016;
Published: Jun. 15, 2016
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Manzhen Duan, Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China
Dayong Wu, Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock, Texas, U.S.A
Bo Dong, Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China
Lin Zhang, Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China
Transportation network faces the possibility of sudden events that disrupts its normal operation, particularly in earthquake prone areas. As the backbone of critical infrastructure lifelines, it is therefore essential that transportation network retains its resilience after disastrous earthquakes to ensure efficient evacuation of at-risk population to safe zones and timely dispatch of emergency response resources to the impacted area. However, predicting transportation network resilience and planning for emergency situations is an extremely challenging problem, particularly under earthquake uncertainty and risks. This paper aims to propose a model to quantify seismic resilience of transportation network. The focus of this model is on generalizing quantitative resilience measures of transportation network response to earthquake risks rather than specifying characteristics of the corridor selections that lead to patterns of the response of each specific road segment. In the model, traffic capacity is selected as resilience measure and three capacity reduction indices are introduced to address the uncertainty and risks from impacted roads, buildings and bridges, respectively. Finally, the proposed models were validated by the 2008 Sichuan Earthquake data.
Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks, American Journal of Civil Engineering.
Vol. 4, No. 4,
2016, pp. 174-184.
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