One of the most important properties of clothes is accompaning the body’s thermal system in order to keep body temperature in its natural extant, even if the environment conditions or physical activities are out of the body’s ideal extent. Perspiring is one of the most important effects of physical activities in warm weather. When human body perspires, the main objective is to loose heat from the body. This excessive heat is mainly lost through evaporation of the moisture at the surface of the skin. The moisture imprisoned among body and its clothing, often causes a feeling of wetness and clamminess and also can generate the afterchill feeling for the wearer. So the basic requirement of the fabric worn next to skin is to transfer this moisture to the atmosphere to reach comfortibility. For which, the main goal of this study is to reach a kind of fabric that guarantees comfortness for the body by a good heat and moisture traort. In order to reach this goal, a group of double-surface fabrics containing hydrophil and hydrophobe fibers are knitted and the simultaneous heat and moisture traort of them is evaluated with the help of perspiring simulating machine and the results are analysed as the transfer process plots. Also transmission of heat and moisture was evaluated for all of the samples by differential modeling as artificial neural network. Effective parameters on heat and moisture transfer were considered by using modeling and statistical methods. The results were analysed to find suitable fabric with optimum comfortness. Final results presented that the fabric made of micro PET filaments and cotton yarns at the bottom and top surface respectively, had the best heat and moisture transfer.
