Introducing a pioneering model designed to optimize the configuration of full-scale submerged nanofiltration membrane modules

A comprehensive investigation into full-scale submerged flat-sheet nanofiltration membrane module performance using a loss model is currently lacking. This study aimed to establish a novel model for accurately predicting this performance in relation to drinking water treatment. The model was designe...

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Bibliographic Details
Main Authors: Anh-Tuan Hoang, The-Anh Nguyen, Nguyet Thi-Minh Dao, Mitsuharu Terashima, Takahiro Fujioka
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Desalination and Water Treatment
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Online Access:http://www.sciencedirect.com/science/article/pii/S1944398625003145
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Summary:A comprehensive investigation into full-scale submerged flat-sheet nanofiltration membrane module performance using a loss model is currently lacking. This study aimed to establish a novel model for accurately predicting this performance in relation to drinking water treatment. The model was designed to enhance the flow within the submerged flat-sheet nanofiltration membrane module, which was organized as a cross-flow filtration system to prevent membrane fouling and ensure high performance. A mathematical expression was derived from experiments to estimate the full-scale flat-sheet nanofiltration permeate flux based on concentration polarization phenomenon on the membrane surface. The simulation results demonstrated that the efficiency between the tank with and without baffles was significant owing to the uniform distribution of the local shear stress, mass transfer coefficient, and permeate flux. Furthermore, the baffle configuration influenced the cost of nanofiltration for clean water production; a tank with five baffles demonstrated the lowest production cost at an optimal inlet flow rate of 3.6 m3 h−1, offering promising cost savings. Overall, by employing this model and simulating various tank configurations, the permeate flux of the submerged flat-sheet nanofiltration membrane module can be predicted, thereby enabling considerable optimization of tank design.
ISSN:1944-3986