Direct Solar Heating of Hydration Baths for Dry Dates: Efficiency and Performance Evaluation

Abstract

This study explores the rehydration kinetics of dry dates using a solar water hydration system under real climatic conditions in Ghardaïa. It focuses on evaluating the thermal response of dates in three regions:El Oued, Guerrara, and Beriane, at hydration temperatures ranging from 39°C to 55°C. Mathematical modeling of the rehydration process using Peleg, Weibull, and exponential models yielded high coefficients of determination (R2 > 0.95), confirming their suitability for accurately predicting water absorption kinetics. The effective diffusion coefficients varied considerably with temperature, reflecting the combined effects of water viscosity and molecular mobility. In addition, an artificial neural network (ANN) model was developed and trained using eight days of meteorological data (ambient temperature, solar irradiation, wind speed, and relative humidity) to predict water temperature inside the solar heater. The ANN model demonstrated excellent predictive performance (R2 = 0.968; MAE = 3.140; RMSE = 4.988), with predicted temperatures closely matching measured values. The high accuracy of the ANN model underscores its potential for real-time temperature prediction, enabling better control and management of the solar rehydration process. Overall, this study emphasizes the critical role of precise temperature management in optimizing the rehydration of dates and highlights the integration of ANN models as powerful tools for enhancing process efficiency and sustainability in arid regions.