Roughness Surface Methodology for Predicting the Performance of Heat and Mass Transfer Process in Liquid Desiccant Dehumidifier

Abstract

The heat and mass transfer process in liquid desiccant dehumidification system (LDDS) is very complicated because it is affected by a combination of input parameters. In this paper, the numerical optimization method is applied to optimize the performance of LDDS depending on experiment data taken from previous study for authors. The input data includes air temperature (Ta), humidity ratio (Wa) and solution temperature (Ts) and ranged between (27 to 34.5 °C), (20.5 to 25 g/kg), and (27.5 to 38.5 °C) respectively. Whereas the responses are the rate of moisture removal (MRR) and effectiveness (ε). The statistical analysis shows that the (Wa) has the most considerable effect on MRR while the (Wa) and (Ts) have the most considerable effect on ε. The optimization analysis for MRR and ε are found to be 0.54 g/s and 0.50 with minimum desirability 0.92 and 1 respectively.