Abstract
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.
Published Version
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