Characterization and statistical modelling of thermal resistance of cotton/polyester blended double layer interlock knitted fabrics

• Main Authors: Afzal Ali, Ahmad Sheraz, Rasheed Abher, Mohsin Muhammad, Ahmad Faheem, Nawab Yasir
• Format: Article
• Language: English
• Published: VINCA Institute of Nuclear Sciences 2017-01-01
• Series: Thermal Science
• Subjects: thermal resistance; response surface regression; modelling; double layer interlock knitted fabric; cotton/polyester
• Online Access: http://www.doiserbia.nb.rs/img/doi/0354-9836/2017/0354-98361500201A.pdf
• ISSN: 0354-9836; 2334-7163

The aim of this study was to analyse and model the effect of knitting parameters on the thermal resistance of cotton/polyester double layer interlock knitted fabrics. Fabric samples of areal densities ranging from 310-495 g/m2 were knitted using yarns of three different cotton/polyester blends, each of two different linear densities by systematically varying knitting loop lengths for achieving different cover factors. It was found that by changing the polyester content in the inner and outer fabric layer from 40 to 65% in the double layer knitted fabric has statistically significant effect on the fabric thermal resistance. Fabric thermal resistance increased with increase in relative specific heat of outer fabric layer, yarn linear density, loop length, and fabric thickness while decrease in fabric areal density. It was concluded that response surface regression modelling could be successfully used for the prediction of thermal resistance of double layer interlock knitted fabrics. The model was validated by unseen data set and it was found that the actual and predicted values were in good agreement with each other with less than 10% absolute error. Sensitivity analysis was also performed to find out the relative contribution of each input parameter on the air permeability of the double layer interlock knitted fabrics.