Uma SR, Syed Y, Karalliyadda SC, Prasanna R. 2020. Modelling interdependencies of critical infrastructure network recovery using a decision support system. Lower Hutt (NZ): GNS Science. 42 p. (GNS Science report; 2020/18). doi:10.21420/Y46F-GJ02.
Abstract:
Critical infrastructure networks provide functional services to support the wellbeing of the community. In the event of a hazard, failures of one or more infrastructure networks and their components disrupt their functionality, affecting the supply of services. Damage to one network could potentially result in cascading functional failures based on their order of dependencies and interdependencies. Understanding the extent of disruption and quantifying their consequences is important to assist various stakeholders in their decision-making processes to meet their respective objectives. Several infrastructure network modelling approaches have been developed by various researchers in the last few decades, and many highlighted the complexities around modelling their interdependencies. In this study, a network-based approach is applied to model the performance of individual networks and to account for interdependencies. The networks are complex to analyse, considering their spatially distributed nature and structural details, so a computer-based decision support system (DSS) is developed in this study to provide a convenient and efficient platform to run several ‘what-if’ scenarios and to generate respective results for consideration in decision-making processes. The features of the DSS and its capabilities are demonstrated through a set of real infrastructure networks from the Wellington region by analysing network performance independently and with interdependencies to generate outage of services in spatial and temporal aspects. The capabilities of the DSS are versatile enough that the utility providers from local government and private sectors will be able to make informed decisions to address the likely impact of infrastructure network failures. (auth)
