• Structural Engineering and Mechanics
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• v.73 no.3
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• pp.339-351
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• 2020

Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.241-242
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• 2016

Recently, the interests in safety and prevention from disaster are increasing. In particular, lifeline networks such as water line and sewerage, electricity, gas, and road would be damaged from a disaster. If the lifeline networks do not work in normal, national public service will not properly function. Researches in social network analysis have been conducted for analyzing the interdependency between individuals since 1970s. These network analysis are utilized to investigate a spread of information and disease. However, it is hard to discover the analyzed cases including characteristics of nodes of networks in the area of transportation and disaster. Therefore, this study conducts network analysis of flooded road with flooding scenarios, investigates safe evacuation routes in flooded road network, and suggests efficient approaches for preventing damages from a flooding.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.781-791
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• 2015

Dam risk analysis requires a systematic process to ensure that hydrologic variables (e.g. precipitation, discharge and water surface level) contribute to each other. However, the existing dam risk approach showed a limitation in assessing the interdependencies across the variables. This study aimed to develop Bayesian network based dam risk analysis model to better characterize the interdependencies. It was found that the proposed model provided advantages which would enable to better identify and understand the interdependencies and uncertainties over dam risk analysis. The proposed model also provided a scenario-based risk evaluation framework which is a function of the failure probability and the consequence. This tool would give dam manager a framework for prioritizing risks more effectively.