Mohsen Hajibabaei, Azadeh Yousefi, Sina Hesarkazzazi, Amin Minaei, Oswald Jenewein, Mohsen Shahandashti, Robert Sitzenfrei
{"title":"管道故障下配水网络弹性增强:水力启发的复杂网络方法","authors":"Mohsen Hajibabaei, Azadeh Yousefi, Sina Hesarkazzazi, Amin Minaei, Oswald Jenewein, Mohsen Shahandashti, Robert Sitzenfrei","doi":"10.2166/aqua.2023.180","DOIUrl":null,"url":null,"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.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resilience enhancement of water distribution networks under pipe failures: a hydraulically inspired complex network approach\",\"authors\":\"Mohsen Hajibabaei, Azadeh Yousefi, Sina Hesarkazzazi, Amin Minaei, Oswald Jenewein, Mohsen Shahandashti, Robert Sitzenfrei\",\"doi\":\"10.2166/aqua.2023.180\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/aqua.2023.180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/aqua.2023.180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Resilience enhancement of water distribution networks under pipe failures: a hydraulically inspired complex network approach
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.