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    Recent progress in reverse osmosis modeling: An overview

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    1-s2.0-S0011916423003375-main.pdf (5.346Mb)
    Date
    2023-05-24
    Author
    Mohd Muzammil, Zubair
    Saleem, Haleema
    Zaidi, Syed Javaid
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    Abstract
    The increasing worldwide demand for freshwater production requires new and sustainable processes to overcome the shortage of clean water. Reverse osmosis (RO) is regarded as the most efficient type of desalination technology and proper knowledge of mathematical modeling of the RO system can help in developing advanced RO systems. Currently, with high computational capability, it is possible to predict how a system will behave in specific conditions without testing experimentally. This article provides a comprehensive assessment of current developments in the RO modeling. To the best of our knowledge, there is no review paper published so far which has covered the modeling in overall RO processes. The study includes basic theories for RO processes and different models based on the membrane configurations like spiral wound, hollow fiber, and tubular. The paper also discusses different mathematical models of RO concerning the solvent flux, solute flux, membrane fouling, energy consumption, nanomaterial incorporation in membrane, hybrid technologies with RO, and zero liquid discharge to enhance the performance of RO system. It is observed that these models could assist in optimizing the design as well as the operation of the systems to increase efficiency, decrease the consumption of energy and enhance the quality of water obtained. Further, predictive models could be developed for forecasting the performance of systems and contribute early warning of possible problems like scaling, fouling, and membrane degradation.
    URI
    https://www.sciencedirect.com/science/article/pii/S0011916423003375
    DOI/handle
    http://dx.doi.org/10.1016/j.desal.2023.116705
    http://hdl.handle.net/10576/56588
    Collections
    • Center for Advanced Materials Research [‎1482‎ items ]
    • Mechanical & Industrial Engineering [‎1461‎ items ]

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