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<p>In recent years, water resources in many countries have been under increasing pressure due to climate change and population growth. Desalination has emerged as a promising alternative to address water scarcity; however, effective design and management of desalination plants require accurate modeling and simulation. In this study, we develop a model to simulate a reverse osmosis (RO) desalination system. Based on the solution-diffusion approach with a new pressure-drop method, the model predicts specific energy consumption, salt concentrations, and flow rates, enabling comparison of plant configurations and evaluation of key input parameters. The results demonstrate that the model is highly efficient and reliable for simulating the desalination process, achieving permeate prediction errors below 1%. A comparative analysis between a multistage RO system and a conventional single-stage RO system highlights the superior performance of the multistage configuration, predicting specific energy consumption of 0.35&#xa0;kWh/m<sup>3</sup> for the multistage system versus 0.40&#xa0;kWh/m<sup>3</sup> for the single-stage system. Additionally, we investigate the impact of feed water temperature on permeate production, identifying the optimal temperature for maximizing efficiency showing that higher feed temperatures in hot seasons maximize efficiency. The findings also reveal the influence of water transport parameter (<i>k</i><sub>w</sub>) and net driving pressure (NDP) on permeate flux. Furthermore, this study determines the maximum allowable feed concentration to ensure optimal system performance in terms of permeate production.</p>

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Simulation and analysis of a multistage reverse osmosis desalination system under varying feed temperatures

  • 期刊论文

  • 发表日期：

    2025年7月16日

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  • A. Bouach,
  • S. Benmamar

摘要

In recent years, water resources in many countries have been under increasing pressure due to climate change and population growth. Desalination has emerged as a promising alternative to address water scarcity; however, effective design and management of desalination plants require accurate modeling and simulation. In this study, we develop a model to simulate a reverse osmosis (RO) desalination system. Based on the solution-diffusion approach with a new pressure-drop method, the model predicts specific energy consumption, salt concentrations, and flow rates, enabling comparison of plant configurations and evaluation of key input parameters. The results demonstrate that the model is highly efficient and reliable for simulating the desalination process, achieving permeate prediction errors below 1%. A comparative analysis between a multistage RO system and a conventional single-stage RO system highlights the superior performance of the multistage configuration, predicting specific energy consumption of 0.35 kWh/m3 for the multistage system versus 0.40 kWh/m3 for the single-stage system. Additionally, we investigate the impact of feed water temperature on permeate production, identifying the optimal temperature for maximizing efficiency showing that higher feed temperatures in hot seasons maximize efficiency. The findings also reveal the influence of water transport parameter (kw) and net driving pressure (NDP) on permeate flux. Furthermore, this study determines the maximum allowable feed concentration to ensure optimal system performance in terms of permeate production.