University of Twente Student Theses


Cascade effects in critical infrastructure : predicting failure from flood events in interdependent infrastructure networks

Krol, M.D. (2018) Cascade effects in critical infrastructure : predicting failure from flood events in interdependent infrastructure networks.

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Abstract:Interdependency within and between critical infrastructure networks increases their vulnerability to failure after a natural hazard such as a ood event. When operation of infrastructure assets gets disrupted this can trigger failure in other infrastructure assets. This process is called a cascade effect and can happen recursively which can cause initially small infrastructure disruptions to have widespread consequences. This study aims to predict cascade failure occurrence due to oods in a selected set of infrastructure networks at a detailed spatial scale. Using a given inundation map to assess direct failure of assets, interdependencies between them are used to simulate indirect failure, i.e. assets failing due to a cascade effect. Failure is described using a topology-based simulation model with aboveground infrastructure assets represented as nodes and interdependencies between them as edges. The modeling methodology is applied for the electrical, telecoms, gas and transportation networks in the Dutch region Zeeuws-Vlaanderen. However, the aim is to devise a method which is generically applicable both in other locations and other types of networks. In order to assess model validity and determine potential areas of improvement, model results and premises are discussed in an expert elicitation process. Operators of selected infrastructure networks are asked to comment on differences between simulated and realistic failure behavior that ensue from modeling choices. In the case study, failure occurs mostly around inundated areas, with direct failure generally accounting for the larger share. This is attributed to key assets in selected networks not being vulnerable to ooding due to their geographical location, but also to the absence of higher order networks in the case study. Indirect failure mostly occurs from intra-sectoral cascade effects, so interdependence between different infrastructure networks is not a driving force behind widespread failure. Vulnerability to cascade effects can be reduced by introducing more network redundancy. While this modeling methodology attempts to be generically applicable, differences between infrastructure networks are encountered that require custom-fit modeling approaches. More information specific to locations and networks can be introduced, but this does institute a need for additional assumptions and data which is often unavailable. The currently applied modeling methodology generally performs well in determining asset functionality during ood events, especially in networks with a clearly defined function and network commodity. However, it falls short for more complex analyses as these require more network- and location-specific modeling. The largest sources of inaccuracy are the premise that no network ow is modeled and the connection with infrastructure networks of higher order, such as the high voltage and national gas networks.
Item Type:Essay (Master)
Nelen & Schuurmans, Utrecht
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
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