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dc.contributor.authorHernández López, Ángela
dc.contributor.authorCamacho-Espino, Jorge
dc.contributor.authorPeñate Suárez, Baltasar
dc.contributor.authorMarichal Plasencia, Graciliano Nicolás
dc.contributor.otherIngeniería Civil, Náutica y Marítima
dc.date.accessioned2024-02-02T21:06:45Z
dc.date.available2024-02-02T21:06:45Z
dc.date.issued2023
dc.identifier.urihttp://riull.ull.es/xmlui/handle/915/35998
dc.description.abstractThis work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) on board a marine vessel. This investigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.ispartofseriesapplied sciences, 2023, 13
dc.rightsLicencia Creative Commons (Reconocimiento-No comercial-Sin obras derivadas 4.0 Internacional)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es_ES
dc.titleEnergy Efficiency Optimization in Onboard SWRO Desalination Plants Based on a Genetic Neuro-Fuzzy System
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3390/app13063392
dc.subject.keywordDesalination
dc.subject.keywordGenetic Neuro-Fuzzy
dc.subject.keywordEnergy Efficiency
dc.subject.keywordIntelligent Control
dc.subject.keywordSoft Computing Techniques


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