A systematic framework for dynamic nodal vulnerability assessment of water distribution networks based on multilayer networks
Hoese Michel Tornyeviadzi,
Emmanuel Owusu-Ansah,
Hadi Mohammed and
Razak Seidu
Reliability Engineering and System Safety, 2022, vol. 219, issue C
Abstract:
Nodal demands vary throughout the day, as such any vulnerability analysis based on static networks, which considers daily average demands cannot realistically represent the criticality of nodes in the network. This study presents a systematic framework, which couples multilayer networks, structural reducibility and a Demand Adjusted Vulnerability Measure for dynamic nodal vulnerability assessment of water distribution networks (WDNs) under extended period simulation. Within this framework, we present the novel idea of characterizing the dynamics of WDNs with multi-slice networks, which captures the state of the network within a predefined temporal window taking into consideration the directional flow in pipes and the operational status of pumps, valves etc. Using a benchmark WDN, Net 3, as a case study we have demonstrated the importance of demand variations and operational status of various components, no matter how minuscule their operational time, on nodal vulnerability assessment in WDNs. The results indicated that the framework evaluates the criticality of all types of nodes, even intermediary nodes with zero base demand, within any temporal window much more realistically than conventional vulnerability analysis methods based on single (static) networks. Structural reducibility unearthed correlations between the operational status of source nodes and pumps on the general dynamics of the distribution system. The multilayer framework opens a new frontier in vulnerability analysis of WDNs and could serve as a tool for stakeholders in accessing node criticality, impact of various failure scenarios and optimal scheduling of maintenance routines.
Keywords: Water distribution networks; Node vulnerability; Dynamic vulnerability assessment model; Multilayer networks; Structural reducibility (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021006955
DOI: 10.1016/j.ress.2021.108217
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