Optimizing Reverse Osmosis Membrane Parameters through the Use of the Solution-Diffusion Model: A Review

Najdawi, Farah Z. and Neptune, Kaleb T. (2022) Optimizing Reverse Osmosis Membrane Parameters through the Use of the Solution-Diffusion Model: A Review. Engineering, 14 (01). pp. 9-32. ISSN 1947-3931

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Abstract

When designing and building an optimal reverse osmosis (RO) desalination plant, it is important that engineers select effective membrane parameters for optimal application performance. The membrane selection can determine the success or failure of the entire desalination operation. The objective of this work is to review available membrane types and design parameters that can be selected for optimal application to yield the highest potential for plant operations. Factors such as osmotic pressure, water flux values, and membrane resistance will all be evaluated as functions of membrane parameters. The optimization of these parameters will be determined through the deployment of the solution-diffusion model devolved from the Maxwell Stephan Equation. When applying the solution-diffusion model to evaluate RO membranes, the Maxwell Stephan Equation provides mathematical analysis through which the steps for mass transfer through a RO membrane may be observed and calculated. A practical study of the use of the solution-diffusion model will be discussed. This study uses the diffusion-solution model to evaluate the effectiveness of a variety of Toray RO membranes. This practical application confirms two principal hypotheses when using the diffusion-solution model for membrane evaluation. First, there is an inverse relationship between membrane and water flux rate. Second, there is a proportional linear relationship between overall water flux rate and the applied pressure across a membrane.

Item Type: Article
Subjects: Pustakas > Engineering
Depositing User: Unnamed user with email support@pustakas.com
Date Deposited: 12 Jun 2023 06:59
Last Modified: 16 Jan 2024 05:18
URI: http://archive.pcbmb.org/id/eprint/738

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