2020
DOI: 10.1016/j.ress.2020.106828
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Reliability of water distribution networks subjected to seismic hazard: Application of an improved entropy function

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Cited by 9 publications
(2 citation statements)
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“…Because of the above mentioned factors, there are few articles for the supply reliability analysis of multi-product pipelines to the best of our knowledge. Most previous related studies have focused on natural gas pipelines [28,29], water distribution systems (WDNs) [30,31], industrial plants [32,33], etc. Combining graph theory, hydro-thermal simulation, and stochastic process simulation methods, Su et al [7] proposed a systematic comprehensive methodology for the supply reliability analysis of natural gas pipeline networks, and established an evaluation model from different perspectives.…”
Section: Related Workmentioning
confidence: 99%
“…Because of the above mentioned factors, there are few articles for the supply reliability analysis of multi-product pipelines to the best of our knowledge. Most previous related studies have focused on natural gas pipelines [28,29], water distribution systems (WDNs) [30,31], industrial plants [32,33], etc. Combining graph theory, hydro-thermal simulation, and stochastic process simulation methods, Su et al [7] proposed a systematic comprehensive methodology for the supply reliability analysis of natural gas pipeline networks, and established an evaluation model from different perspectives.…”
Section: Related Workmentioning
confidence: 99%
“…Noteworthy contributions in this research direction include Lim and Song's (2012) selective recursive decomposition algorithm for assessing post-hazard responses in WDSs, Farahmandfar et al's (2017) connectivity-based seismic resilience metric and optimization framework, and Pudasaini and Shahandashti's (2020) evaluation of ten topological connectivity metrics for optimizing seismic robustness. Furthermore, researchers have developed additional methods more recently, such as improved entropy functions (Emamjomeh et al, 2020), community structure analysis (Giudicianni et al, 2021), hierarchical Bayesian approaches (Yu et al, 2021), and Bayesian Belief Networks (Pagano et al, 2022).…”
Section: Introductionmentioning
confidence: 99%