Moisture and heat transfer in hybrid weft knitted fabric with artificial intelligence

Abstract

AbstractOne of the most important properties of clothes is their ability to help the body's thermal system to keep the body temperature in its natural range, even if the environmental conditions or physical activities are outside the body's ideal range. Perspiring is one of the most important effects of physical activities in warm weather for shedding the body's excessive heat. Therefore, the basic requirement of a fabric worn next to the skin is to transfer this moisture to the atmosphere to reach comfort through the avoidance of a feeling of wetness and clamminess and also through the generation of a situation for the best surface evaporation of moisture. The main goal of this study was to achieve a kind of fabric that guarantees comfort for the body by good heat and moisture transport. To achieve this goal, a group of double‐surface fabrics containing hydrophilic and hydrophobe fibers were knitted, and their simultaneous heat and moisture transport was evaluated with the help of a perspiration‐simulation machine; the results were analyzed as transfer process plots. Also, the transmission of heat and moisture was evaluated for all of the samples by differential modeling as an artificial neural network. Effective parameters on heat and moisture transfer were taken into consideration with modeling and statistical methods. The results were analyzed to find a suitable fabric with optimum comfort. The final results showed that a fabric made of micropolyester filaments and cotton yarns on the bottom and top surfaces, respectively, had the best heat and moisture transfer. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009