Liquid desiccant dehumidification is a promising energy-extensive process for air dehumidification, which can easily be driven by any waste or renewable heat sources. In the current study, a hybrid method is proposed by combining the solar evacuated tube collectors as a regeneration source to drive liquid desiccant system in a close-loop. Subsequently, an experimental setup has been fabricated to assess the performance of the overall system using a novel desiccant mixture. The overall energy balance between the ambient air and the liquid desiccant was also studied. Effects of independent parameters such as solution to airflow rate, solution concentration and temperature on the dehumidifier-regenerator performance parameters such as latent heat ratio, condensation rate, desiccant mass fraction index, evaporation rate, latent and enthalpy effectiveness were analyzed. The result of present investigation showed that high solution to airflow (S/A) ratio enhanced the dehumidification and low S/A ratio enhanced the liquid desiccant regeneration rate. The maximum latent heat ratio for the dehumidifier at the design condition was 0.92, and the thermal coefficient of performance of the system was found as 1.1. The airside pressure drop in the dehumidifier/regenerator was also estimated at different flow rates of desiccant. Further, adaptive neuro-fuzzy inference system (ANFIS) prediction models are developed to predict the system performance as a function of system-independent parameters. The model results exhibited a good agreement with the experimental outcomes. The latent heat ratio and evaporation rate are predicted within a mean absolute percentage error (MAPE) of 2.7% and 2.3%, respectively.
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