Resilience enhancement of water distribution networks under pipe failures: a hydraulically inspired complex network approach

Author:

Hajibabaei Mohsen1ORCID,Yousefi Azadeh2,Hesarkazzazi Sina1,Minaei Amin13,Jenewein Oswald4,Shahandashti Mohsen5,Sitzenfrei Robert1ORCID

Affiliation:

1. a Unit of Environmental Engineering, Department of Infrastructure Engineering, University of Innsbruck, Innsbruck, Austria

2. b Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy

3. c Austrian Academy of Sciences (ÖAW), Vienna, Austria

4. d School of Architecture, University of Texas at Arlington, Arlington, TX, USA

5. e Department of Civil Engineering, University of Texas at Arlington, Arlington, TX, USA

Abstract

Abstract The resilience of water distribution networks (WDNs) should be proactively evaluated to reduce the potential impacts of disruptive events. This study proposes a novel hydraulically-inspired complex network approach (HCNA) to assess and enhance WDN resilience in the case of single-pipe failure. Unlike conventional hydraulic-based models, HCNA requires no hydraulic simulations for resilience analysis. Instead, it quantifies the failure consequences of edges (pipes) on the WDN graph by incorporating topological attributes with flow redistribution triggered by failures. This HCNA procedure leads to the identification of critical edges (pipes), as well as impacted ones, representing edges more susceptible to the failure of others. The impacted edges are then systematically resized by integrating HCNA with a graph-based design approach, obtaining a wide range of resilience enhancement solutions. A comparative study between HCNA and a hydraulic-based model for three WDNs confirms HCNA's effectiveness in identifying the most critical pipes in various network sizes. Furthermore, HCNA provides comparable resilience enhancement solutions with a hydraulic-based evolutionary optimization but with significantly lower computational effort (1,400 times faster). Thus, it can efficiently be used for resilience enhancement of large-scale WDNs, where the application of conventional optimizations is limited due to the intensive computational workload.

Funder

The Austrian security research programme KIRAS of the Federal Ministry of Finance

The Austrian Marshall Plan Foundation

The National Science Foundation

Publisher

IWA Publishing

Subject

Management, Monitoring, Policy and Law,Pollution,Water Science and Technology,Ecology,Civil and Structural Engineering,Environmental Engineering

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