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

Abstract : 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.
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https://hal.inrae.fr/hal-03205411
Contributor : Dominique Fournier Connect in order to contact the contributor
Submitted on : Thursday, April 22, 2021 - 12:03:52 PM
Last modification on : Thursday, September 16, 2021 - 12:40:05 PM

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Abdeljalil Chougradi, François Zaviska, Ahmed Abed, Jérome Harmand, Jamal-Eddine Jellal, et al.. Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile. Membranes, MDPI, 2021, 11 (3), pp.173. ⟨10.3390/membranes11030173⟩. ⟨hal-03205411⟩

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