AbstractThis research aims to evaluate the properties of cotton single jersey knitted fabrics (SJKF) produced from cotton/spandex yarns at different Lycra states. So, four different SJKF were produced, namely 100% cotton, cotton with additional Lycra (full-platted), core, and dual-core-spun (DCS) yarns with the same loop length. The thermal comfort properties, fabric recovery, total hand value (THV), moisture management parameters, and air permeability were measured. The experimental results showed that the use of DCS yarns in the SJKF improves the fabric elastic recovery by 100%. The obtained values of air permeability, THV, and overall moisture management capacity of stretched SJKF are lower than 100% cotton fabric sample. Thermal absorptivity of core and dual-core samples increased by 27% and the water vapor permeability decreased by 18% compared to 100% cotton fabric sample.

Compression bandage (CB) as a porous material should provide both graduated pressure and thermal comfort properties to enable air permeability, heat transfer, and liquid perspiration out of the human body. The main factors affecting thermal comfort properties are the temperature difference between environment and skin, yarns’ structure and material, fabric thickness, porosity, areal density, number of fabric layers, trapped air, and fabric structure. Thermal resistance (Rct) and water vapor resistance (Ret) are evaluated for four types of woven CBs. All bandage types were applied at the range of extension (10–80%) using both two- and three-layer bandaging on thermal foot model (TFM). Rct values are compared with measured results by the Alambeta instrument, whereas Ret test is performed on the Permetest device. Thermal resistance is significantly decreased when increasing the bandage extension from 10 to 40%, then it is slightly increased by increasing the extension from 40 to 60%, after that it is decreased especially at 80% extension due to lower bandage thickness and higher compression.

The aim of this work is to estimate the effect of loop length and Lycra weight percent (Lwp) on the geometrical and thermo-physiological comfort of elastic plain knitted fabric. Fifty single jersey knitted fabric samples were produced at five levels of Lycra weight percent (Lwp) (4%, 5%, 6%, 7%, and 8%) and loop length (2.7 mm, 2.9 mm, 3.1 mm, 3.3 mm, and 3.4 mm) with full plaited (fp) and half plaited (hp) of bare Lycra. The thermo-physiological comfort properties (thermal conductivity, absorptivity, and water vapor permeability), air permeability, and geometrical properties were measured at standard of each one. The results showed that the elastic single jersey knitted fabric thickness ranged between 3.12 times and 4.2 times of the yarn diameter (d). The fabric thickness increased when loop length is increased and decreased when Lwp is increased. The thermal conductivity, absorptivity, and water vapor resistance (WVR) decreased with Lwp increasing.

In this study, an algebraic model and its experimental verification was carried out to investigate the effect of moisture content on the heat loss that takes place due to conduction of sock fabrics. The results show that increasing moisture content in the studied socks caused a significant increase in their conductive heat loss. Plain knitted socks with different fiber composition were wetted to a saturated level, and then their moisture content was reduced stepwise. When achieving the required moisture content, the socks samples were characterized by the Alambeta testing instrument for heat transfer. Three different existing modified mathematical models for the thermal conductivity of wet fabrics were used for predicting thermal resistance of socks under wet conditions. The results from both ways are in very good agreement for all the socks at a 95% confidence level. In the above-mentioned models, the prediction of thermal resistance presents newly a combined effect of the real filling coefficient and thermal conductivity of the so-called “wet” polymers instead of dry polymers. With these modifications, the used models predicted the thermal resistance at different moisture levels. Predicted thermal resistance is converted into heat transfer (due to conduction) with a significantly high coefficient of correlation.