Research on the Heat and Mass Transfer Performance of the Copper Foam Condensation Dehumidifier for Space Stations

A high-efficiency condensation dehumidification system utilizing copper foam driven by a Stirling refrigerator was developed to address the demands for high-efficiency heat transfer and a compact lightweight design in space stations. An experimental study was conducted to investigate its heat and mass transfer characteristics under various conditions. The experimental parameters were set as follows: air inlet temperature ranging from 20 ℃ to 30 ℃, relative humidity between 50% and 80%, cold plate temperature from 8 ℃ to 13 ℃, and inlet wind speed from 0.4 m/s to 1.4 m/s. The results indicated a positive correlation between the increase in the air inlet temperature and the enhancement of both the heat and mass transfer coefficients. Specifically, when the air inlet temperature increased from 20 ℃ to 30 ℃, the heat transfer coefficient increased by 10.5%, whereas the mass transfer coefficient exhibited a more substantial increase of 57.1%. Furthermore, variations in the relative humidity of the air inlet distinctly affected the heat and mass transfer coefficients: the heat transfer coefficient decreased by 31.6% with an increase in the relative humidity, whereas the mass transfer coefficient increased by 11.4%. Although reducing the temperature of the cold plate can effectively improve heat transfer, it leads to the accumulation of condensate water and reduces the efficiency of heat and mass transfer. Therefore, an appropriate cold plate temperature must be selected. Additionally, the efficiency of heat and mass transfer was markedly enhanced with increasing inlet wind speed. However, a continuous increase in wind speed resulted in higher system energy consumption. Thus, a balance between efficient heat transfer and high system energy consumption was essential. Based on extensive experimental data, the heat transfer model was refined using regression analysis. The standard deviation between the theoretical and experimental values was 8.21%, and the maximum deviation was 19.76%, demonstrating the strong predictive accuracy of the model.