Performance evaluation of open-cycle solar regenerator using artificial neural network technique

Theoretical investigation on the performance of lithium chloride (LiCl) absorption cooling system using an artificial neural network (ANN) model is presented. Tabulated data from the literature are used to construct the ANN model. Solar collector desiccant/regenerator is applied to re-concentrate the working solution. Using the proposed model, the effect of system design parameters; namely regenerator length, and air flow rate on the performance of the system is demonstrated. The variation of the thermo-physical parameters along the regenerator length is highlighted.

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