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The purpose of this paper is to analyze the fit and thermal and moisture comfort factors to provide some reference value for the functional design of underwear.

The body size data of 100 male youths are measured to analyze the body shape of the lower body. Based on the complete body size, the authors selected the matching underwear, and obtained the relevant data for the mathematical model of thermal and moisture using Grey correlation analysis method.

In allusion to the defect of fit comfort and thermal-moisture comfort of the crotch, this paper presented a mathematical model, and experimental results showed that breathable fabric and breathable volume are the key factors.

It was clarified that which is the key to the thermal and moisture comfort. At the same time, male lower body characteristics index is clear.

In order to study the static and dynamic comfort of tight sportswear in winter, the subjective comfort was aimed to be evaluated by collecting sensory data such as humidity feeling, cold feeling and other perceptions. In this paper, the experiment was divided into standing, squatting, jumping, jogging, walking and so on.

Through particle swarm optimization-cuckoo search model, the sensory factors that affect the overall comfort were optimized, and it was found that there were great differences in the overall comfort factors under different motions. Then, analytic hierarchy process was used to sort the optimized sensory indicators in each experimental stage, and the influence degree of sensory indicators was studied. Finally, by the long short-term memory (LSTM) model, taking comfort senses of standing, squatting, jumping and jogging as input parameters, and regarding comfort senses of walking, lifting legs and resting as output parameters, the prediction model was founded.

The results showed that there were certain differences between the prediction value and the real subjective evaluation value, but most of the predicted values were consistent with the real values on the sensory level, and the overall prediction level was good, which meant that the LSTM model had more accurate prediction ability for subjective evaluation and could be extended to other sports.

The research results could provide scientific methods for the design of tight-fitting sportswear in winter.

The purpose of this paper is to measure the thermal and moisture resistance of the knitted upper fabrics with the foot model, which provided basis for designing and producing sports shoes with thermal-moisture comfort.

In this paper, different yarn materials and fabric stitches were selected as the changing factors. The three kinds of yarn materials and the three kinds of fabric stitches were combined to design and weave eight pieces of knitted upper fabrics. Human sweating was simulated by the thermal-moisture comfort foot model, and then tested the thermal and moisture resistance of eight pieces of fabrics in different parts of the foot. Finally, the relationship between yarn material, fabric stitch, and the thermal and moisture resistance in different parts of the foot was analyzed by data.

The composition of the yarn material and fabric stitch has certain effect on the thermal-moisture comfort in different sections of the foot. When the yarn material of the four parts of the lateral arch, medial arch, ankle and heel is composed of 31.1tex moisture wicking polyester/33.3tex spandex coated yarn, the yarn material of the instep and toes is composed of 31.1tex ordinary polyester/33.3tex spandex coated yarn, and all parts of fabric stitch choose single-sided loop transfer stitch, the knitted sports shoes have the best thermal-moisture comfort.

The study used the thermal-moisture comfort foot model to simulate the human body metabolism and sweating system. Through the quantitative analyze of the thermal and moisture resistance of knitted upper fabrics to provide basis for the producers to design and product knitted sports shoes with good thermal-moisture comfort.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

The comfort and fit of clothes are affected by fabric properties, dressed ease and environmental conditions, in which dressed ease is influenced by the interaction among complex shapes of human body, style design and fabric mechanical properties.

In this study, the dressed ease distribution at waist section, which is related to body surface convex angle, was investigated using 3D scanning. A series of surface convex angles on bust and back were formed after adjusting the mannequin. The mannequin was scanned by TC2 separately in garments with eight different ease allowances. Then the dressed ease distributions at waist under different convex angles of body surface have been acquired by calculating the distance between waist points and dressed surfaces along normal directions.

The results showed that the body surface convex angle was weakly related to the dressed ease when the garments’ bust ease allowance was below 4 cm. When the garments’ bust ease allowance was within 6–12 cm, the body convex angle had a great impact on the dressed waist ease distribution in the condition of 26º–33º bust convex angle and 13.96º–17.96º back slope angle. For slack garments with more than 16 cm ease allowance, the dressed waist ease distribution did not relate to the bust convex angle, while it strongly related to the bust convex angle between 13.96º and 17.96º. The regression model was statistically significant between the dressed ease value and the body surface convex angle.

According to the dressed waist ease distribution of different body surface convex angles, this paper gives an application of pattern modification in order to optimize the waist fit. The results can provide guidance for the optimization of different body shapes. At the same time, the application of gap data to 3D virtual fitting can greatly improve the authenticity of virtual simulation effect.

In this paper, the clothes made of synthetic and natural fibres were tested. The characteristics of selected physical parameters such as temperature, electrical resistance, thermal resistance of fabrics used for tested clothes have been presented. The electrostatical charge and temperature distribution of clothes were investigated on human body. The temperature distribution and the coefficient of heat transmission were measured by a new thermovision method.

Mercerization is one of the finishing treatments that often are used to improve the dye uptake properties and increase cotton fabrics' luster. Since comfort is a necessity of clothing and customers desire it more than ever, the finishing treatments that improve some properties of the fabric should not reduce clothing comfort. The aim of this paper was to investigate the effect of cold mercerization on the comfort properties of cotton fabrics.

A total of 15 woven fabric samples in different structures were randomly chosen. The samples were divided into two groups: the finished fabrics (i.e. those which were run through singing, desizing, and bleaching processes) and the mercerized fabrics (i.e. samples which underwent the singing, desizing, bleaching and mercerizing processes). The mechanical and thermo‐physiological comfort properties of these two groups were evaluated and results were compared.

The results showed that bending rigidity, shearing rigidity, air permeability, water vapour transmission and thermal resistance increased by cold mercerization. Moreover, frictional restraint, extensibility and wicking decreased. In other words, mercerization can improve some comfort properties of cotton fabrics and weaken the others.

The current literatures don't consider the effect of mercerization on the clothing comfort. The present work intends to evaluate the effect of cold mercerization on the mechanical (tactile) and thermo‐physiological comfort properties of cotton fabrics which are used as summer clothing.

The aim of this study is to investigate wearing comfort of summer work uniforms judged by construction workers.

A total of 189 male construction workers participated in a series of wear trials and questionnaire surveys in the summer of 2014. They were asked to randomly wear two types of work uniforms (i.e. uniforms A and B) in the two-day field survey and the subjective attributes of these uniforms were assessed. Three analytical techniques, namely, multiple regression, artificial neural network and fuzzy logic were used to predict wearing comfort affected by the six subjective sensations.

The results revealed that fuzzy logic was a robust and practical tool for predicting wearing comfort in terms of better prediction performance and more interpretable results than the other models. Pressure attributes were further found to exert a greater effect than thermal–wet attributes on wearing comfort. Overall, the use of uniform B exhibited profound benefits on wearing comfort because it kept workers cooler, drier and more comfortable with less work performance interference than wearing uniform A.

The findings provide a fresh insight into construction workers’ needs for work clothes, which further facilitates the improvement in the clothing tailor-made design and the enhancement of the well-being of workers.

The thermophysiological comfort of fabrics is prerequisite as customers covet adequate moisture, heat management-supported and UV protective clothing that measure up to their levels of activities and environmental conditions. Hitherto, scant tasks have been reported with the purpose of engineering both comfort and UV protection simultaneously. From that vantage point, the objective of this work is to develop a model for optimum UPF, air permeability, water-vapour resistance, thermal resistance, thermal absorptivity and areal density of knitted fabrics.

Weft knitted fabrics of various compositions were investigated. UPF was tested using the Labsphere UV transmittance analyser. The FX 3300 (Textest instruments) air permeability tester was used to test air permeability. Thermal comfort and water-vapour resistance were evaluated using the Alambeta and Permetest instruments, respectively. Based on image processing, the porosity was measured. Fabrics thickness and areal density were measured according to standard methods. Furthermore, parametric and non-parametric statistical test methods were applied to the data for analysis.

Linear regression was substantiated by Kolmogorov-Smirnov test. Then multiple linear regression of porosity and thickness together on UPF and comfort parameters were visually depicted by virtue of 3D linear plots. Residual analysis with quantile-quantile and probability plots, advocated the tests using the Shapiro-Wilk test. The result was validated by comparison with experimental data tested. The samples gave satisfactory relative errors and were supported by the z-test method. All tests indicated failure to reject the null hypothesis.

The predictive models were embedded into an interactive computer program. Fabric thickness and porosity are the inputs needed to run the program. It will predict the optimum UPF, areal density and thermophysiological comfort parameters. In a nutshell, knitters may use the program to determine optimum structural parameters for diverse permutations of UPF and thermophysiological comfort parameters; scilicet high UV protection together with low thermal insulation combined with low water-vapour resistance and high air permeability.

The mass transfer of textiles during movement is complicated as the energy consumption (EC) from skin, surface temperature of fabrics together with environment will work synergistically to determine the sensation and comfort of wearer. The purpose of this paper is to reveal the mass transfer in the human-textile-environment dynamic system.

With a simulated hotplate mounted on a rotational testing platform, this paper focuses on the dynamic mass transfer of a fabric so as to simulate the real-time mass transfer of clothing in movements.

It has been found that the EC and surface temperature (T) change against testing time, indicating the convex and concave shapes of the EC–t and T–t curves. The initial moisture regain of the fabric, rotational speed of the platform and the fiber materials of the fabric have shown a great effect on the dynamic mass transfer process.

Understanding the dynamic mass transfer of textiles will benefit the design of clothing with better comfort and will contribute to the well-being of wearers.

This work reveals the dynamic mass transfer of textiles in rotational movements. It contributes a new approach to studying the mass transfer of clothing in real service.