Reliability based rehabilitation of water distribution networks by means of Bayesian networks
Water plays an essential role in the everyday lives of the people. To supply subscribers with good quality of water and to ensure continuity of service, the operators use water distribution networks (WDN). The main elements of water distribution network (WDN) are: pipes and valves. The work develope...
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2017-09-01
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| Series: | Journal of Water and Land Development |
| Subjects: | |
| Online Access: | http://www.degruyter.com/view/j/jwld.2017.34.issue-1/jwld-2017-0050/jwld-2017-0050.xml?format=INT |
| _version_ | 1797703296403636224 |
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| author | Lakehal Abdelaziz Laouacheria Fares |
| author_facet | Lakehal Abdelaziz Laouacheria Fares |
| author_sort | Lakehal Abdelaziz |
| collection | DOAJ |
| description | Water plays an essential role in the everyday lives of the people. To supply subscribers with good quality of water and to ensure continuity of service, the operators use water distribution networks (WDN). The main elements of water distribution network (WDN) are: pipes and valves. The work developed in this paper focuses on a water distribution network rehabilitation in the short and long term. Priorities for rehabilitation actions were defined and the information system consolidated, as well as decision-making. The reliability data were conjugated in decision making tools on water distribution network rehabilitation in a forecasting context. As the pipes are static elements and the valves are dynamic elements, a Bayesian network (static-dynamic) has been developed, which can help to predict the failure scenario regarding water distribution. A relationship between reliability and prioritization of rehabilitation actions has been investigated. Modelling based on a Static Bayesian Network (SBN) is implemented to analyse qualitatively and quantitatively the availability of water in the different segments of the network. Dynamic Bayesian networks (DBN) are then used to assess the valves reliability as function of time, which allows management of water distribution based on water availability assessment in different segments. Before finishing the paper by giving some conclusions, a case study of a network supplying a city was presented. The results show the importance and effectiveness of the proposed Bayesian approach in the anticipatory management and for prioritizing rehabilitation of water distribution networks. |
| first_indexed | 2024-03-12T05:03:25Z |
| format | Article |
| id | doaj.art-1e9e557d5785474f9e025a331bf9ee46 |
| institution | Directory Open Access Journal |
| issn | 2083-4535 |
| language | English |
| last_indexed | 2024-03-12T05:03:25Z |
| publishDate | 2017-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Journal of Water and Land Development |
| spelling | doaj.art-1e9e557d5785474f9e025a331bf9ee462023-09-03T09:04:55ZengPolish Academy of SciencesJournal of Water and Land Development2083-45352017-09-0134116317210.1515/jwld-2017-0050jwld-2017-0050Reliability based rehabilitation of water distribution networks by means of Bayesian networksLakehal Abdelaziz0Laouacheria Fares1Mohamed Chérif Messaadia University, Department of Mechanical Engineering, P.O. Box 1553, 41000 Souk-Ahras, AlgeriaBadji Mokhtar Annaba University, Department of Hydraulic, P.O. Box 12, 23000, Annaba, AlgeriaWater plays an essential role in the everyday lives of the people. To supply subscribers with good quality of water and to ensure continuity of service, the operators use water distribution networks (WDN). The main elements of water distribution network (WDN) are: pipes and valves. The work developed in this paper focuses on a water distribution network rehabilitation in the short and long term. Priorities for rehabilitation actions were defined and the information system consolidated, as well as decision-making. The reliability data were conjugated in decision making tools on water distribution network rehabilitation in a forecasting context. As the pipes are static elements and the valves are dynamic elements, a Bayesian network (static-dynamic) has been developed, which can help to predict the failure scenario regarding water distribution. A relationship between reliability and prioritization of rehabilitation actions has been investigated. Modelling based on a Static Bayesian Network (SBN) is implemented to analyse qualitatively and quantitatively the availability of water in the different segments of the network. Dynamic Bayesian networks (DBN) are then used to assess the valves reliability as function of time, which allows management of water distribution based on water availability assessment in different segments. Before finishing the paper by giving some conclusions, a case study of a network supplying a city was presented. The results show the importance and effectiveness of the proposed Bayesian approach in the anticipatory management and for prioritizing rehabilitation of water distribution networks.http://www.degruyter.com/view/j/jwld.2017.34.issue-1/jwld-2017-0050/jwld-2017-0050.xml?format=INTdynamic Bayesian networkspredicting reliabilityrehabilitationstatic Bayesian networkswater distribution network |
| spellingShingle | Lakehal Abdelaziz Laouacheria Fares Reliability based rehabilitation of water distribution networks by means of Bayesian networks Journal of Water and Land Development dynamic Bayesian networks predicting reliability rehabilitation static Bayesian networks water distribution network |
| title | Reliability based rehabilitation of water distribution networks by means of Bayesian networks |
| title_full | Reliability based rehabilitation of water distribution networks by means of Bayesian networks |
| title_fullStr | Reliability based rehabilitation of water distribution networks by means of Bayesian networks |
| title_full_unstemmed | Reliability based rehabilitation of water distribution networks by means of Bayesian networks |
| title_short | Reliability based rehabilitation of water distribution networks by means of Bayesian networks |
| title_sort | reliability based rehabilitation of water distribution networks by means of bayesian networks |
| topic | dynamic Bayesian networks predicting reliability rehabilitation static Bayesian networks water distribution network |
| url | http://www.degruyter.com/view/j/jwld.2017.34.issue-1/jwld-2017-0050/jwld-2017-0050.xml?format=INT |
| work_keys_str_mv | AT lakehalabdelaziz reliabilitybasedrehabilitationofwaterdistributionnetworksbymeansofbayesiannetworks AT laouacheriafares reliabilitybasedrehabilitationofwaterdistributionnetworksbymeansofbayesiannetworks |