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Dynamic Modeling of Fouling in Reverse Osmosis Membranes

During reverse osmosis (RO) membrane filtration, performance is dramatically affected by fouling, which concurrently decreases the permeate flux while increasing the energy required to operate the system. Comprehensive design and optimization of RO systems are best served by an understanding of the...

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Autores principales: Ling, Bowen, Xie, Peng, Ladner, David, Battiato, Ilenia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151604/
https://www.ncbi.nlm.nih.gov/pubmed/34068543
http://dx.doi.org/10.3390/membranes11050349
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author Ling, Bowen
Xie, Peng
Ladner, David
Battiato, Ilenia
author_facet Ling, Bowen
Xie, Peng
Ladner, David
Battiato, Ilenia
author_sort Ling, Bowen
collection PubMed
description During reverse osmosis (RO) membrane filtration, performance is dramatically affected by fouling, which concurrently decreases the permeate flux while increasing the energy required to operate the system. Comprehensive design and optimization of RO systems are best served by an understanding of the coupling between membrane shape, local flow field, and fouling; however, current studies focus exclusively on simplified steady-state models that ignore the dynamic coupling between fluid flow, solute transport, and foulant accumulation. We developed a customized solver (SUMs: Stanford University Membrane Solver) under the open source finite volume simulator OpenFOAM to solve transient Navier–Stokes, advection–diffusion, and adsorption–desorption equations for foulant accumulation. We implemented two permeate flux reduction models at the membrane boundary: the resistance-in-series (RIS) model and the effective-pressure-drop (EPD) model. The two models were validated against filtration experiments by comparing the equilibrium flux, pressure drop, and fouling pattern on the membrane. Both models not only predict macroscopic quantities (e.g., permeate flux and pressure drop) but also the fouling pattern developed on the membrane, with a good match with experimental results. Furthermore, the models capture the temporal evolution of foulant accumulation and its coupling with flux reduction.
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spelling pubmed-81516042021-05-27 Dynamic Modeling of Fouling in Reverse Osmosis Membranes Ling, Bowen Xie, Peng Ladner, David Battiato, Ilenia Membranes (Basel) Article During reverse osmosis (RO) membrane filtration, performance is dramatically affected by fouling, which concurrently decreases the permeate flux while increasing the energy required to operate the system. Comprehensive design and optimization of RO systems are best served by an understanding of the coupling between membrane shape, local flow field, and fouling; however, current studies focus exclusively on simplified steady-state models that ignore the dynamic coupling between fluid flow, solute transport, and foulant accumulation. We developed a customized solver (SUMs: Stanford University Membrane Solver) under the open source finite volume simulator OpenFOAM to solve transient Navier–Stokes, advection–diffusion, and adsorption–desorption equations for foulant accumulation. We implemented two permeate flux reduction models at the membrane boundary: the resistance-in-series (RIS) model and the effective-pressure-drop (EPD) model. The two models were validated against filtration experiments by comparing the equilibrium flux, pressure drop, and fouling pattern on the membrane. Both models not only predict macroscopic quantities (e.g., permeate flux and pressure drop) but also the fouling pattern developed on the membrane, with a good match with experimental results. Furthermore, the models capture the temporal evolution of foulant accumulation and its coupling with flux reduction. MDPI 2021-05-10 /pmc/articles/PMC8151604/ /pubmed/34068543 http://dx.doi.org/10.3390/membranes11050349 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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ling, Bowen
Xie, Peng
Ladner, David
Battiato, Ilenia
Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title_full Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title_fullStr Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title_full_unstemmed Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title_short Dynamic Modeling of Fouling in Reverse Osmosis Membranes
title_sort dynamic modeling of fouling in reverse osmosis membranes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151604/
https://www.ncbi.nlm.nih.gov/pubmed/34068543
http://dx.doi.org/10.3390/membranes11050349
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