Vulnerability assessment of urban drainage network using relevance‐based centrality metrics
Abstract The analysis of urban drainage networks (UDNs) is one of the most important topics in the study of water systems. The interest in strategies aimed at analyzing the impacts of sewer pipes failure on the urban drainage system operation is growing, and the need of developing methodologies aime...
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| Format: | Article |
| Language: | English |
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Wiley-VCH
2023-02-01
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| Series: | River |
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| Online Access: | https://doi.org/10.1002/rvr2.30 |
| _version_ | 1797231276505169920 |
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| author | Antonietta Simone |
| author_facet | Antonietta Simone |
| author_sort | Antonietta Simone |
| collection | DOAJ |
| description | Abstract The analysis of urban drainage networks (UDNs) is one of the most important topics in the study of water systems. The interest in strategies aimed at analyzing the impacts of sewer pipes failure on the urban drainage system operation is growing, and the need of developing methodologies aimed at vulnerability assessment and system management is increasingly important. To this purpose, the present work shows and discusses the use of complex network theory. In particular, the recently developed relevance‐based centrality metrics have been used to classify UDNs and to identify the most critical pipes. First, the relevance‐based degree is applied to the direct graph of the drainage network to classify the systems. Afterward, the relevance‐based edge betweenness is used for ranking the importance, that is, the criticality with respect to fluxes, for the pipes. The relevance‐based metrics assign importance to the network elements (pipes and nodes), considering both the intrinsic relevance of nodes and the network connectivity structure. Results provide useful information to support pipe maintenance programs to be prepared for malfunctioning events by means of a criticality analysis in advance.The relevance‐based metrics are presented by using the direct graph of a simple example network, and they are then applied both to a benchmark and a real urban drainage system to show the effectiveness even for real systems. |
| first_indexed | 2024-04-24T15:41:49Z |
| format | Article |
| id | doaj.art-7a6156e510a44bc781cbff237e8e73ba |
| institution | Directory Open Access Journal |
| issn | 2750-4867 |
| language | English |
| last_indexed | 2024-04-24T15:41:49Z |
| publishDate | 2023-02-01 |
| publisher | Wiley-VCH |
| record_format | Article |
| series | River |
| spelling | doaj.art-7a6156e510a44bc781cbff237e8e73ba2024-04-01T19:00:13ZengWiley-VCHRiver2750-48672023-02-0121395110.1002/rvr2.30Vulnerability assessment of urban drainage network using relevance‐based centrality metricsAntonietta Simone0University of Naples Federico II Faculty of Engineering, Civil, Building, and Environmental Engineering Napoli ItalyAbstract The analysis of urban drainage networks (UDNs) is one of the most important topics in the study of water systems. The interest in strategies aimed at analyzing the impacts of sewer pipes failure on the urban drainage system operation is growing, and the need of developing methodologies aimed at vulnerability assessment and system management is increasingly important. To this purpose, the present work shows and discusses the use of complex network theory. In particular, the recently developed relevance‐based centrality metrics have been used to classify UDNs and to identify the most critical pipes. First, the relevance‐based degree is applied to the direct graph of the drainage network to classify the systems. Afterward, the relevance‐based edge betweenness is used for ranking the importance, that is, the criticality with respect to fluxes, for the pipes. The relevance‐based metrics assign importance to the network elements (pipes and nodes), considering both the intrinsic relevance of nodes and the network connectivity structure. Results provide useful information to support pipe maintenance programs to be prepared for malfunctioning events by means of a criticality analysis in advance.The relevance‐based metrics are presented by using the direct graph of a simple example network, and they are then applied both to a benchmark and a real urban drainage system to show the effectiveness even for real systems.https://doi.org/10.1002/rvr2.30complex network theoryfailure eventrelevance‐based centrality metricsUDNs classificationUDNs vulnerability assessment |
| spellingShingle | Antonietta Simone Vulnerability assessment of urban drainage network using relevance‐based centrality metrics River complex network theory failure event relevance‐based centrality metrics UDNs classification UDNs vulnerability assessment |
| title | Vulnerability assessment of urban drainage network using relevance‐based centrality metrics |
| title_full | Vulnerability assessment of urban drainage network using relevance‐based centrality metrics |
| title_fullStr | Vulnerability assessment of urban drainage network using relevance‐based centrality metrics |
| title_full_unstemmed | Vulnerability assessment of urban drainage network using relevance‐based centrality metrics |
| title_short | Vulnerability assessment of urban drainage network using relevance‐based centrality metrics |
| title_sort | vulnerability assessment of urban drainage network using relevance based centrality metrics |
| topic | complex network theory failure event relevance‐based centrality metrics UDNs classification UDNs vulnerability assessment |
| url | https://doi.org/10.1002/rvr2.30 |
| work_keys_str_mv | AT antoniettasimone vulnerabilityassessmentofurbandrainagenetworkusingrelevancebasedcentralitymetrics |