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Yasir Imtiaz Syed, Raj Prasanna, S Uma, Kristin Stock, & Denise Blake. (2018). A Design Science based Simulation Framework for Critical Infrastructure Interdependency. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 516–524). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Critical Infrastructures (CI) such as electricity, water, fuel, telecommunication and road networks are a crucial factor for secure and reliable operation of a society. In a normal situation, most of the businesses operate on an individual infrastructure. However, after major natural disasters such as earthquakes, the conflicts and complex interdependencies among the different infrastructures can cause significant disturbances because a failure can propagate from one infrastructure to another. This paper discusses the development of an integrated simulation framework that models interdependencies between electricity and road infrastructure networks of Wellington region. The framework uses a damage map of electricity network components and integrates them with road access time to the damaged components for determining electricity outage time of a region. The results can be used for recovery planning, identification of vulnerabilities, and adding or discarding redundancies in an infrastructure network.
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Andrew Sherson, S Uma, & Raj Prasanna. (2018). The effect of localised factors on water pipe repair times post-earthquake. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 366–380). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: In the Wellington Region, many lifelines are at risk, because they are in vulnerable narrow corridors close to active faults. In an earthquake, it is expected that these lifelines will be significantly damaged and unusable for extended periods of time. Because of this risk, many studies have been conducted to investigate the resulting downtimes. These studies, despite their usefulness, do not incorporate or make significant assumptions about localised factors. This paper summarises a thesis that aimed to improve the current predictive models, by including these local, and contextual influences. Multiple stakeholders who manage and repair the lifelines were interviewed to identify these factors which were then included into one of the current predictive models, and the influence on repair times was recorded. It was discovered that localised impacts such as staff logistics, land sliding, the land gradient, interdependency, and access doubled previous predicted repair times.
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