Reverse Osmosis (RO) is one of the widely adopted methods for water desalination to mitigate shortage of freshwater for domestic, irrigation and industrial consumption. Recently RO is also used as a draw solution regeneration step for most hybrid Forward Osmosis-Reverse Osmosis (FO-RO) systems used for water desalination. Accurate model is required which is more flexible and reliable, to design and operate RO treatment plants for producing freshwater from various water resources. However, most models do not represent multi element field scale RO systems accurately. Plant engineers widely use the available commercial programs for the design of multi element RO systems where the computational code is not provided, which makes the program inflexible. This work presents a computational tool developed on the python platform for the prediction and analysis of the RO process employed in a hybrid FO-RO system. A steady state model based on the solution-diffusion and film theory is established by employing concentration polarization, pressure drop and average solution properties in the computational calculations of the RO process. The model is used to design and estimate the performance parameters of an entire RO system having multiple membrane elements installed in a pressure vessel. A comparison between the outputs obtained by the model and membrane manufacturers software shows good agreement.

反渗透 (RO) 是一种广泛采用的海水淡化方法，以缓解生活用水、灌溉用水和工业用水的淡水短缺问题。最近 RO 也被用作大多数用于水淡化的混合正渗透-反渗透 (FO-RO) 系统的汲取溶液再生步骤。需要更灵活、更可靠的精确模型来设计和运营从各种水资源中生产淡水的反渗透处理厂。然而，大多数模型不能准确地表示多元素现场规模 RO 系统。工厂工程师广泛使用可用的商业程序来设计不提供计算代码的多元素反渗透系统，这使得程序不灵活。这项工作提出了一种在 python 平台上开发的计算工具，用于预测和分析混合 FO-RO 系统中采用的 RO 过程。采用浓差极化、压降和平均溶液特性对反渗透工艺进行计算，建立了基于溶液扩散和薄膜理论的稳态模型。该模型用于设计和估计在压力容器中安装了多个膜元件的整个 RO 系统的性能参数。模型和膜制造商软件获得的输出之间的比较显示出良好的一致性。RO 过程计算中的压降和平均溶液特性。该模型用于设计和估计在压力容器中安装了多个膜元件的整个 RO 系统的性能参数。模型和膜制造商软件获得的输出之间的比较显示出良好的一致性。RO 过程计算中的压降和平均溶液特性。该模型用于设计和估计在压力容器中安装了多个膜元件的整个 RO 系统的性能参数。模型和膜制造商软件获得的输出之间的比较显示出良好的一致性。