Multi-objective optimization of a three-fluid hollow fiber membrane dehumidifier for energy-efficient drying applications

This study presents a multi-objective optimization (MOO) of a three-fluid hollow fiber membrane dehumidifier (THFD) to improve humidity regulation for drying processes. Two conflicting objectives, energy transfer across membrane column (Emc) and vapor removal rate (υVRR), were optimized utilizing the NSGA-II algorithm and fuzzy clustering with weighted cumulative probability distribution (FC-WCPD). The decision variables were air mass flow rate (mai), LiCl solution inlet temperature (τLSi), and concentration (XLSi). The optimal solution from NSGA-II yielded Emc = 2.82 kW/m2 and uVRR = 2.6 g/min at mai = 7.5 kg/h, τLSi = 30 °C and XLSi = 0.33 kgLiCl/kgsol. Both optimization methods showed a deviation of less than ±3.5 %, confirming robustness. Experimental validation showed excellent agreement, with only 1.05 % increase in Emc and 0.38 % decrease in υVRR. A case study integrating THFD with a solar-assisted agricultural dryer, showed up to 45 % improvement in thermal gain under solar intensity of 0.9 kW/m2, water inlet temperature of 50 °C, and air flow rate of 15 kg/h. Increasing water jacket effectiveness from 0.6 to 0.75 led to a 36 % gain in thermal output. These results highlight the potential of THFD systems for scalable drying applications and underscore the importance of further studies on long-term stability and real-world deployment.

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