Cargando…

Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile

As world demand for clean water increases, reverse osmosis (RO) desalination has emerged as an attractive solution. Continuous RO is the most used desalination technology today. However, a new generation of configurations, working in unsteady-state feed concentration and pressure, have gained more a...

Descripción completa

Detalles Bibliográficos
Autores principales: Chougradi, Abdeljalil, Zaviska, François, Abed, Ahmed, Harmand, Jérôme, Jellal, Jamal-Eddine, Heran, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997241/
https://www.ncbi.nlm.nih.gov/pubmed/33671027
http://dx.doi.org/10.3390/membranes11030173
_version_ 1783670283584929792
author Chougradi, Abdeljalil
Zaviska, François
Abed, Ahmed
Harmand, Jérôme
Jellal, Jamal-Eddine
Heran, Marc
author_facet Chougradi, Abdeljalil
Zaviska, François
Abed, Ahmed
Harmand, Jérôme
Jellal, Jamal-Eddine
Heran, Marc
author_sort Chougradi, Abdeljalil
collection PubMed
description As world demand for clean water increases, reverse osmosis (RO) desalination has emerged as an attractive solution. Continuous RO is the most used desalination technology today. However, a new generation of configurations, working in unsteady-state feed concentration and pressure, have gained more attention recently, including the batch RO process. Our work presents a mathematical modeling for batch RO that offers the possibility of monitoring all variables of the process, including specific energy consumption, as a function of time and the recovery ratio. Validation is achieved by comparison with data from the experimental set-up and an existing model in the literature. Energetic comparison with continuous RO processes confirms that batch RO can be more energy efficient than can continuous RO, especially at a higher recovery ratio. It used, at recovery, 31% less energy for seawater and 19% less energy for brackish water. Modeling also proves that the batch RO process does not have to function under constant flux to deliver good energetic performance. In fact, under a linear pressure profile, batch RO can still deliver better energetic performance than can a continuous configuration. The parameters analysis shows that salinity, pump and energy recovery devices efficiencies are directly linked to the energy demand. While increasing feed volume has a limited effect after a certain volume due to dilution, it also shows, interestingly, a recovery ratio interval in which feed volume does not affect specific energy consumption.
format Online
Article
Text
id pubmed-7997241
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-79972412021-03-27 Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile Chougradi, Abdeljalil Zaviska, François Abed, Ahmed Harmand, Jérôme Jellal, Jamal-Eddine Heran, Marc Membranes (Basel) Article As world demand for clean water increases, reverse osmosis (RO) desalination has emerged as an attractive solution. Continuous RO is the most used desalination technology today. However, a new generation of configurations, working in unsteady-state feed concentration and pressure, have gained more attention recently, including the batch RO process. Our work presents a mathematical modeling for batch RO that offers the possibility of monitoring all variables of the process, including specific energy consumption, as a function of time and the recovery ratio. Validation is achieved by comparison with data from the experimental set-up and an existing model in the literature. Energetic comparison with continuous RO processes confirms that batch RO can be more energy efficient than can continuous RO, especially at a higher recovery ratio. It used, at recovery, 31% less energy for seawater and 19% less energy for brackish water. Modeling also proves that the batch RO process does not have to function under constant flux to deliver good energetic performance. In fact, under a linear pressure profile, batch RO can still deliver better energetic performance than can a continuous configuration. The parameters analysis shows that salinity, pump and energy recovery devices efficiencies are directly linked to the energy demand. While increasing feed volume has a limited effect after a certain volume due to dilution, it also shows, interestingly, a recovery ratio interval in which feed volume does not affect specific energy consumption. MDPI 2021-02-28 /pmc/articles/PMC7997241/ /pubmed/33671027 http://dx.doi.org/10.3390/membranes11030173 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Chougradi, Abdeljalil
Zaviska, François
Abed, Ahmed
Harmand, Jérôme
Jellal, Jamal-Eddine
Heran, Marc
Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title_full Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title_fullStr Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title_full_unstemmed Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title_short Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile
title_sort batch reverse osmosis desalination modeling under a time-dependent pressure profile
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997241/
https://www.ncbi.nlm.nih.gov/pubmed/33671027
http://dx.doi.org/10.3390/membranes11030173
work_keys_str_mv AT chougradiabdeljalil batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile
AT zaviskafrancois batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile
AT abedahmed batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile
AT harmandjerome batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile
AT jellaljamaleddine batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile
AT heranmarc batchreverseosmosisdesalinationmodelingunderatimedependentpressureprofile