A mathematical method and artificial neural network modeling to simulate osmosis membrane’s performance

Lack of fresh water has been a major obstacle to development and flourishing in human history. Desalination provides a new vision toward fresh water production in the upcoming future. The study has proposed a simple mathematical equation and ANN models to simulate eight types of sea water RO membranes. The Artificial Neural Network (ANN) models have been developed to simulate TDS corresponding to the temperature (T,  °C), flow rate (gpm) and recovery percentage. The feed data was generated by ROSA software. The model developed using a simple rational mathematical method. ANN models were trained using feed-forward back propagation algorithm with two hidden layers and various numbers of neurons in each layer. The model verification analysis proved both mathematical and ANN models to be highly accurate, reliable and practical for analyzing, designing, operating and optimizing of RO systems. The correlation coefficients (R) of 0.96 and 0.97, respectively, confirmed that the equation and ANN models resulted in this study are in good agreement with the measured data.

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