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Heat flow topology-driven thermo-mass decoupling strategy: Cross-scale regularization modeling and optimization analysis

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  • Cao, Menglong
  • Wang, Zhe
  • Tang, Haobo
  • Li, Songran
  • Ji, Yulong
  • Han, Fenghui

Abstract

The liquid desiccant dehumidification (LDD) is both eco-friendly and highly effective in humidity control, widely investigated across diverse angles. This study expands the application of the newly devised heat current method to examine the liquid desiccant dehumidification process. It introduces a new regularized temperature, which includes using a heat flow topology driven thermo-mass decoupling strategy, and constructing the heat current model by defining both the thermal resistance and moisture resistance. It significantly extends the application of the heat current method, clarifying the thermo-mass coupling energy transfer mechanism. The findings indicate that key factors influencing system performance indicators include total thermal conductivity (αA), solution mass flow rate (ms), air-solution mass flow rate ratio (RA/S,D), and heat source temperature (tH). Furthermore, under the influence of distinct thermal conductivities, the optimal output values for performance indicators, including moisture removal rate, exergy efficiency and entransy efficiency, are determined as 8.4 g/s, 71.2%, and 12.3%, respectively. The results of synergistic influence analysis reveal that, for the performance indicator entransy efficiency, msand RA/S,D display a significant degree of synergistic influence, resulting in a strong positive effect and benefiting 68.53% of the total area. Multi-objective optimization indicates a trade-off relationship among the system performance evaluation indicators moisture removal rate, exergy efficiency and entransy efficiency, with optimal solution values of 3.25 g/s, 65.92%, and 12.01%, respectively.

Suggested Citation

  • Cao, Menglong & Wang, Zhe & Tang, Haobo & Li, Songran & Ji, Yulong & Han, Fenghui, 2024. "Heat flow topology-driven thermo-mass decoupling strategy: Cross-scale regularization modeling and optimization analysis," Applied Energy, Elsevier, vol. 367(C).
    • Handle: RePEc:eee:appene:v:367:y:2024:i:c:s0306261924007785
    DOI: 10.1016/j.apenergy.2024.123395
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