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Rapid Assessment of Hurricane Damage and Disruption to Interdependent Civil Infrastructure Systems
Civil infrastructure systems such as power, water, and communications are critical for the well-being and functioning of citizens, industries, and organizations both under normal and disaster conditions. Infrastructure systems cannot be seen as independent entities because they rely a great deal on each other for services needed for operation. Damage to one system can have cascading effects throughout that system, and throughout all of the systems that rely on it. To obtain a meaningful prediction of disruption, these interdependencies among the systems must be considered. This paper presents two models to predict and analyze the effect that a hurricane can have on the performance of interdependent infrastructure systems. The first model uses a Monte Carlo simulation and statistical methods to predict the damage caused by a hurricane on the systems being considered. The second model applies optimization techniques to determine the cascading effects that the damage has throughout the infrastructure systems considered. A case study was conducted using an artificial interdependent infrastructure data set called “Clarc” County. Examples from this case study show that there is a benefit in considering interdependencies among infrastructure systems when predicting disruptions. In addition, the effect of these interdependencies can be assessed in time to support decision making for restoration of services either during an event or as a training exercise.
Rapid Assessment of Hurricane Damage and Disruption to Interdependent Civil Infrastructure Systems
Civil infrastructure systems such as power, water, and communications are critical for the well-being and functioning of citizens, industries, and organizations both under normal and disaster conditions. Infrastructure systems cannot be seen as independent entities because they rely a great deal on each other for services needed for operation. Damage to one system can have cascading effects throughout that system, and throughout all of the systems that rely on it. To obtain a meaningful prediction of disruption, these interdependencies among the systems must be considered. This paper presents two models to predict and analyze the effect that a hurricane can have on the performance of interdependent infrastructure systems. The first model uses a Monte Carlo simulation and statistical methods to predict the damage caused by a hurricane on the systems being considered. The second model applies optimization techniques to determine the cascading effects that the damage has throughout the infrastructure systems considered. A case study was conducted using an artificial interdependent infrastructure data set called “Clarc” County. Examples from this case study show that there is a benefit in considering interdependencies among infrastructure systems when predicting disruptions. In addition, the effect of these interdependencies can be assessed in time to support decision making for restoration of services either during an event or as a training exercise.
Rapid Assessment of Hurricane Damage and Disruption to Interdependent Civil Infrastructure Systems
Loggins, Ryan A. (author) / Wallace, William A. (author)
2015-05-14
Article (Journal)
Electronic Resource
Unknown
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