Abstract
An accurate heat and mass transfer model of a tumble drum has not been developed yet owing to complicated random motions of clothes in the tumble drum. In this study, heat and mass transfers of water from clothes to air, including the heat loss in the tumble drum of a clothes dryer, are measured with the temperature, humidity, airflow rate, and water content of clothes. The mass transfer rate increases as the air temperature, airflow rate, and water content of clothes increase; however, it decreases with an increase in the relative air humidity. The mass transfer rate enhancement is dominated by the increase in the temperature over the airflow rate; the increased temperature from 40 degrees C to 80 degrees C results in an increase in the mass transfer rate of 196%-238%, and the increased volumetric airflow rate from 2.5 CMM to 3.1 CMM leads to an increase in the mass transfer rate of 21%-23%. The heat loss in a tumble drum increases as the air temperature increases and continues to increase as the relative air humidity and water content of clothes decrease. Furthermore, although the heat loss is linearly proportional to the difference between the temperatures of ambient air and clothes, it has an insignificant relationship with the airflow rate. In addition, the prediction models of heat and mass transfers of water and heat loss in the tumble drum are developed using artificial neural network, exhibiting optimal agreements with the measured data. The developed prediction models can be used to optimize the tumble drum dryer, considering energy efficiency and short drying time.
NSTL
Elsevier