{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T13:55:11Z","timestamp":1764251711266,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["DSAIPA\/DS\/0089\/2018"],"award-info":[{"award-number":["DSAIPA\/DS\/0089\/2018"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Water"],"abstract":"<jats:p>The current paper proposes a novel methodology for near\u2013real time burst location and sizing in water distribution systems (WDS) by means of Multi\u2013Layer Perceptron (MLP), a class of artificial neural network (ANN). The proposed methodology can be systematized in four steps: (1) construction of the pipe\u2013burst database, (2) problem formulation and ANN architecture definition, (3) ANN training, testing and sensitivity analyses, (4) application based on collected data. A large database needs to be constructed using 24 h pressure\u2013head data collected or numerically generated at different sensor locations during the pipe burst occurrence. The ANN is trained and tested in a real\u2013life network, in Portugal, using artificial data generated by hydraulic extended period simulations. The trained ANN has demonstrated to successfully locate 60\u201370% of the burst with an accuracy of 100 m and 98% of the burst with an accuracy of 500 m and to determine burst sizes with uncertainties lower than 2 L\/s in 90% of tested cases and lower than 0.2 L\/s in 70% of the cases. This approach can be used as a daily management tool of water distribution networks (WDN), as long as the ANN is trained with artificial data generated by an accurate and calibrated WDS hydraulic models and\/or with reliable pressure\u2013head data collected at different locations of the WDS during the pipe burst occurrence.<\/jats:p>","DOI":"10.3390\/w13131841","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T12:03:27Z","timestamp":1625141007000},"page":"1841","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Near\u2013Real Time Burst Location and Sizing in Water Distribution Systems Using Artificial Neural Networks"],"prefix":"10.3390","volume":"13","author":[{"given":"Miguel","family":"Capelo","sequence":"first","affiliation":[{"name":"CERIS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal"}]},{"given":"Bruno","family":"Brentan","sequence":"additional","affiliation":[{"name":"Hydraulic Engineering and Water Resources Department, School of Engineering, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5232-2018","authenticated-orcid":false,"given":"Laura","family":"Monteiro","sequence":"additional","affiliation":[{"name":"CERIS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6901-4767","authenticated-orcid":false,"given":"D\u00eddia","family":"Covas","sequence":"additional","affiliation":[{"name":"CERIS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,1]]},"reference":[{"key":"ref_1","first-page":"133","article-title":"Moving urban water infrastructure asset management from science into practice","volume":"13","author":"Coelho","year":"2014","journal-title":"Urban Water J."},{"key":"ref_2","first-page":"57","article-title":"Analysis and calculation of the short and long run economic","volume":"12","author":"Kanakoudis","year":"2016","journal-title":"Water Util. 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