Edge-based graph centrality measures with spatial analytics to support vulnerability assessment and maintenance planning in sewer networks

被引:1
作者
Okwori, Emmanuel Jenkeri [1 ]
Viklander, Maria [1 ]
Hedstroem, Annelie [1 ]
机构
[1] Lulea Univ Technol, Dept Civil Environm & Nat Resources Engn, S-97187 Lulea, Sweden
关键词
asset management; complex network theory; network resilience; proactive maintenance planning; topological analysis; ALGORITHM;
D O I
10.2166/hydro.2024.300
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this study, the spatial relationship between critical pipes identified using edge-based centrality measures and pipes with higher failure probability-based vulnerability indicators were analysed in sanitary sewer networks. By analysing two sub-networks, one residential and the other a central network, significant spatial associations between pipes with high centrality values and those exhibiting adverse conditions (poor CCTV grades, previous blockages, and low self-cleaning capabilities) were identified. Path-based centrality measures, particularly edge betweenness and K-path edge centrality were less influenced by weights when identifying critical pipes. In contrast, non-path-based measures like nearest neighbour edge centrality could identify localised spatial patterns between critical pipes and pipes in adverse conditions within the sewer networks investigated. The results showed that the spatial patterns between critical pipes and pipes in adverse conditions were not random and could support proactive maintenance planning and the development of more resilient networks. Additionally, the impact of network structure, connectivity, and differences in the composition of pipe attributes could contribute to variations in the strength of observable spatial associations.
引用
收藏
页码:2146 / 2161
页数:16
相关论文
共 41 条
[21]   Factors Influencing the Condition of Sewer Pipes: State-of-the-Art Review [J].
Malek Mohammadi, Mohammadreza ;
Najafi, Mohammad ;
Kermanshachi, Sharareh ;
Kaushal, Vinayak ;
Serajiantehrani, Ramtin .
JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE, 2020, 11 (04)
[22]   A framework for considering externalities in urban water asset management [J].
Marlow, David ;
Pearson, Leonie ;
MacDonald, Darla Hatton ;
Whitten, Stuart ;
Burn, Stewart .
WATER SCIENCE AND TECHNOLOGY, 2011, 64 (11) :2199-2206
[23]   A topological characterisation of looped drainage networks [J].
Meijer, Didrik ;
Korving, Hans ;
Clemens-Meyer, Francois .
STRUCTURE AND INFRASTRUCTURE ENGINEERING, 2024, 20 (10) :1563-1576
[24]   Identifying Critical Elements in Sewer Networks Using Graph-Theory [J].
Meijer, Didrik ;
van Bijnen, Marco ;
Langeveld, Jeroen ;
Korving, Hans ;
Post, Johan ;
Clemens, Francois .
WATER, 2018, 10 (02)
[25]   A defect classification methodology for sewer image sets with convolutional neural networks [J].
Meijer, Dirk ;
Scholten, Lisa ;
Clemens, Francois ;
Knobbe, Arno .
AUTOMATION IN CONSTRUCTION, 2019, 104 :281-298
[26]   Identifying weak points of urban drainage systems by means of VulNetUD [J].
Moederl, M. ;
Kleidorfer, M. ;
Sitzenfrei, R. ;
Rauch, W. .
WATER SCIENCE AND TECHNOLOGY, 2009, 60 (10) :2507-2513
[27]   A Survey of Information Entropy Metrics for Complex Networks [J].
Omar, Yamila M. ;
Plapper, Peter .
ENTROPY, 2020, 22 (12) :1-26
[28]   Centrality and shortest path length measures for the functional analysis of urban drainage networks [J].
Reyes-Silva, Julian D. ;
Zischg, Jonatan ;
Klinkhamer, Christopher ;
Rao, P. Suresh C. ;
Sitzenfrei, Robert ;
Krebs, Peter .
APPLIED NETWORK SCIENCE, 2020, 5 (01)
[29]   Sewer inspection and comparison of acoustic and CCTV methods [J].
Romanova, Anna ;
Horoshenkov, Kirill V. ;
Tait, Simon J. ;
Ertl, Thomas .
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-WATER MANAGEMENT, 2013, 166 (02) :70-80
[30]   Design of water distribution systems using an intelligent simple benchmarking algorithm with respect to cost optimization and computational efficiency [J].
Shende, Sachin ;
Chau, K. W. .
WATER SUPPLY, 2019, 19 (07) :1892-1898