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dc.contributor.authorPérez Magrané, Ramon
dc.contributor.authorMartínez Torrents, Albert
dc.contributor.authorMartínez del Álamo, Manuel
dc.contributor.authorGrau Torrent, Sergi
dc.contributor.authorVinardell Magre, Laura
dc.contributor.authorTomàs Puig, Ricard
dc.contributor.authorMartínez Lladó, Xavier
dc.contributor.authorJubany Güell, Irene
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió
dc.date.accessioned2022-10-11T07:26:57Z
dc.date.available2022-10-11T07:26:57Z
dc.date.issued2022-07-26
dc.identifier.citationPerez, R. [et al.]. Chlorine concentration modelling and supervision in water distribution systems. "Sensors (Switzerland)", 26 Juliol 2022, vol. 22, núm. 15, article 5578, p. 1-14.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/374258
dc.description.abstractThe quality of the drinking water distributed through the networks has become the main concern of most operators. This work focuses on one of the most important variables of the drinking water distribution networks (WDN) that use disinfection, chlorine. This powerful disinfectant must be dosed carefully in order to reduce disinfection byproducts (DBPs). The literature demonstrates researchers’ interest in modelling chlorine decay and using several different approaches. Nevertheless, the full-scale application of these models is far from being a reality in the supervision of water distribution networks. This paper combines the use of validated chlorine prediction models with an intensive study of a large amount of data and its influence on the model’s parameters. These parameters are estimated and validated using data coming from the Supervisory Control and Data Acquisition (SCADA) software, a full-scale water distribution system, and using off-line analytics. The result is a powerful methodology for calibrating a chlorine decay model on-line which coherently evolves over time along with the significant variables that influence it.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Política i gestió ambiental::Gestió de l'aigua
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental::Tractament de l'aigua
dc.subject.lcshChlorine
dc.subject.lcshDrinking water
dc.subject.lcshWater - Distribution
dc.subject.otherChlorine
dc.subject.otherWater distribution networks
dc.subject.otherModelling
dc.subject.otherSupervision
dc.subject.otherDecay model
dc.titleChlorine concentration modelling and supervision in water distribution systems
dc.typeArticle
dc.subject.lemacClor
dc.subject.lemacAigua potable
dc.subject.lemacAigua -- Distribució
dc.identifier.doi10.3390/s22155578
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/22/15/5578
dc.rights.accessOpen Access
local.identifier.drac34204303
dc.description.versionPostprint (author's final draft)
local.citation.authorPerez, R.; Martinez, A.; Martínez del Álamo, M.; Grau, S.; Vinardell, L.; Tomàs, R.; Martínez, X.; Jubany Güell, Irene
local.citation.publicationNameSensors (Switzerland)
local.citation.volume22
local.citation.number15, article 5578
local.citation.startingPage1
local.citation.endingPage14


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