Study on thermal and evaporative resistances of multilayered fabric ensembles

The present work deals with the study on thermal and evaporative resistance of multilayered fabric ensembles meant for cold weather applications. Three-layered structure is used to study the thermal comfort properties. Knitted fabric and polytetrafluoroethylene coated fabrics were used in inner and outer layer, respectively. Needle punched fabrics produced from polyester fibre were used in middle layer. Fifteen different non-woven fabrics were produced according to Box and Behnken experimental design for three variables and three levels by varying mass per unit area, punch density and depth of needle penetration. The produced fabrics were evaluated for thermal and evaporative resistances with and without inner and outer layer fabrics. Thickness, air permeability, bulk density and porosity of the needle punched fabrics were studied. The properties of the fabrics were analyzed for statistical significance by using ‘Design-Expert’ statistical software. Artificial neural network model was developed to predict the properties of fabrics and validation of model was done with the testing data-set. The performance of prediction was evaluated by mean square error, mean absolute error percentage and correlation coefficient. It was concluded that the predicted properties of fabric correlated well with the experimental results.     

Modeling of thermal properties of multilayered fabrics by ANN consisting of polypropylene needle-punched nonwovens

This paper presents the prediction of thermal and evaporative resistances of multilayered fabrics meant for cold weather conditions using artificial neural network (ANN) model. Thermal and evaporative resistances of fabrics were evaluated using sweating guarded hot plate method. The significance and interdependency of thickness on other fabric and process parameters and its effect on prediction performance of ANN model is analyzed in detail. For this purpose, two different network architectures were used to predict the thermal properties of multilayered fabrics. In both the networks, three-layer structure consisting of input, hidden and output layers was used. First, network was constructed with four input parameters, namely linear density of fiber, mass per unit area, punch density, and thickness of nonwoven fabric which predicts thermal and evaporative resistances. Second network was made with three input parameters, namely linear density, mass per unit area, and punch density. The network parameters were optimized to give minimum mean square error (MSE), mean absolute error percentage, and good correlation coefficient. The trend analysis was conducted and influence of various input parameters on the thermal properties of multilayered fabrics was studied. The significance of each input parameter in the prediction of thermal properties was studied by carrying out sensitivity analysis. The mean square error of the test dataset before and after the exclusion of the corresponding input parameter is taken for analysis. The input parameters were ranked based on the MSE ratio of test dataset. The predicted thermal properties of multilayered fabrics are correlated well with the experimental values. It was observed that the ANN model with minimum input parameters, namely linear density of fiber, mass per unit area, and punch density can predict the thermal properties of multilayered fabrics with good accuracy.     

Analysis of thermal properties of multilayered fabrics by full factorial and Taguchi method

The present paper reports the thermal and evaporative resistances of multilayered fabric ensembles meant for cold weather conditions. A three-layered structure was used to simulate the multilayered fabric ensemble. Knitted, through air-bonded nonwoven and coated fabrics were used as inner, middle and outer layer fabrics, respectively. Inner and middle layer fabrics were varied in mass per unit area in three different levels. Three different coated fabrics, namely, polyester polymer-coated fabric and two different polytetrafluoroethylene-coated fabrics which vary in pore size and porosity were used in outer layer. Taguchi’s L₉ orthogonal array, meant for three variables and three levels were used to form nine different multilayered fabric ensembles. Signal to noise ratio was studied to predict and optimize the thermal properties of multilayered fabric ensembles. Full factorial design was used to study the effectiveness of predicting thermal properties of multilayered fabrics using Taguchi’s approach. Regression equations were developed and contour plots were drawn to analyse the effect of chosen parameters on thermal properties of fabrics. In both the methods, the percentage contributions of each factor for thermal and evaporative resistances of multilayered fabrics were studied using sum of squares method. It was found that the Taguchi’s method reduces the number of experiments significantly and predicts the thermal properties of multilayered fabrics with good prediction performance. Mass per unit area of inner layer was found to have no significant effect on thermal and evaporative resistances of multilayered fabric ensembles. Mass per unit area of through air-bonded nonwoven fabric was found to be the most significant parameter in determining the thermal resistance of multilayered fabrics. Mass per unit area of middle layer and pore size of coated fabrics were found to contribute almost equal level in deciding the evaporative resistance of multilayered fabrics.     

Study on thermal resistance of multilayered fabrics under different compressional loads

In this work, the thermal resistance of multilayered fabric ensembles meant for cold weather conditions were studied under different compressional loads. An instrument has been developed to study the thermal resistance of fabrics under different compressional loads. The instrument consists of a test plate, guard plates and a bottom plate. The test plate and guard plates were assembled together as a single entity, which can be moved up and down with a screw shaft. A load cell was connected to the plate assembly to apply the required compressional load on the fabric specimen. Thermal resistance of multilayered fabrics was studied in the developed instrument under different loading conditions. Single-jersey knitted fabric, needle punched fabric and polytetraflouroethylene (PTFE) coated fabrics were used in the inner, middle and outer layer, respectively. Twenty different multilayered fabric ensembles with the same inner and outer layers were studied. The middle layers, i.e. needle punched nonwoven fabrics, were produced from polyester hollow fibres, with varying linear density of fibre, mass per unit area and punch density. The thermal resistance of multilayered fabrics obtained from the developed instrument was compared with the thermal resistance of instruments, namely sweating guarded hot plate (SGHP) and Alambeta. Regression equations were developed and the contour plots were drawn to analyse the effect of the fibre, fabric and process parameters. ANOVAs were conducted to find the significance of the compressional load, linear density of fibre, mass per unit area and punch density on the thermal resistance of fabrics. It was found that the thermal resistance obtained from the instrument follows the same trend as that of thermal resistance obtained from SGHP and Alambeta. Mass per unit area was found to have significant effect on the thermal resistance of multilayered fabrics under different compressional loads. The effect of punch density decreases with the increase in compressional load on the thermal resistance of multilayered fabrics. The thermal conductivity of multilayered fabrics was observed to increase with the increase in the compressional load.     

Electrical resistance of jute needle-punched non-woven fabric – effect of punch density,needle penetration and area density

The electrical resistance of jute needle-punched non-woven fabric has been studied. Statistical model using central composite rotatable experimental design is developed for electrical resistance depending on the three important parameters of needled non-woven fabric, i.e. punch density, depth of needle penetration and mass per unit area. From this model and its contour diagrams, the effects of different parameters can be understood on electrical resistance of those fabrics. Prediction of electrical resistance can be made knowing the values of independent parameters. The correlation coefficients between observed and predicted values are found to be significant in all the cases. As depth of needle penetration increases for a particular punch density, electrical resistance increases and after reaching to maximum, it decreases having optimum at about 140 punches/cm² and 12?mm depth of needle penetration. With the increase of area density, resistance decreases. As punch density increases for a particular area density, resistance increases for high needle penetration.     

Permeability and impact properties of warp-knitted spacer fabrics for protective application

An experimental investigation was carried out to study the effect of interlining material on the comfort and dynamic deformation characteristics of body armour. Suitable plies of interlining materials were selected based on the fabric comfort properties and the impact resistance specified for ballistic application. Kevlar woven fabric was used to block the projectile, and the spacer fabric was used as an interlining material to ensure wearing comfort and for imparting impact resistance. The yarn denier of the middle and bottom layers of the spacer fabrics was maintained constant, and three different deniers were used for the face layer. Three different plies of spacer fabrics were analysed by means of thermophysiological comfort properties to select the suitable interlining material for body armour. The experimental results confirm that the number of plies of spacer fabrics has significant influence on the ballistic armour characteristics than the face layer denier as proved by two-way ANOVA. The substantiated spacer fabric was used as an interlining material, and the depth and area of deformation were analysed. The research findings demonstrated that the three-plied warp-knitted polyester spacer fabric produced better results than single- and five-plied spacer fabrics. One-way ANOVA and Turkey’s HSD also confirmed the influence and interaction of different plies of spacer fabrics.     

Application of artificial neural network (ANN) for the prediction of thermal resistance of knitted fabrics at different moisture content*

Thermal resistance of the fabrics is one of the decisive parameters in terms of comfort; however it can change due to wetting. Therefore, thermal resistance of wetted fabric is important for comfort performance of garments. In recent years, artificial neural networks (ANN) have been used in the textile field for classification, identification, prediction of properties and optimization problems. ANNs can predict the fabric thermal properties by considering the influence of all fabric parameters at the same time. In this study, ANNs were used to predict thermal resistance of wetted fabrics. For this aim, two different architectures were experienced and high regression coefficient (R²) between the predicted (training and testing) and observed thermal resistance values were obtained from both models. The obtained regression coefficient values were over 90% for both models. Then it can be said that ANNs could be used for predicting thermal resistance of wetted fabrics successfully.     

Study of stiffness and abrasion resistance of needle‐punched nonwoven blankets

The properties of needled fabrics depend on the nature of component fibers and the manner in which fibers are arranged in the structure. Fiber properties along with the various machine and web parameters contribute to the structure that emerges from the needling operation. In this paper, the effect of machine parameters such as depth of needle penetration and punch density on fabric stiffness and abrasion resistance of needled blankets has been studied. The effect of calendering and sandwiching hollow polyester fibers between two layers of fine polyester fibers on the abrasion resistance and fabric stiffness has also been studied. It was observed that fabric stiffness first increases and then decreases as the depth of needle penetration increases. Increase in punch density leads to a decrease in fabric stiffness only at higher levels of depth of penetration due to fiber rupture. Calendering improves the fabric abrasion resistance properties but fabric stiffness also increases. Sandwiching of hollow polyester fibers between the two layers of fine denier polyester fibers improves the abrasion resistance without increasing the fabric stiffness.     

Study on heat transmission through multilayer clothing assemblies under different convective modes

The present work reports a detailed study on dry thermal resistance of multilayered clothing assemblies under different modes of heat transmission (i.e. non-convective mode, natural convection and forced convection). A series of multilayered fabric assemblies have been created with different combinations of fabric layers (like plain woven, nonwoven wadding, warp-knitted spacer fabric, weft-knitted breathable coated and weft-knitted aluminium coated) and air gaps of different thicknesses between fabric layers. Significant impacts of thickness of air gaps and mode of heat transmission on thermal resistance of multilayered clothing assemblies have been observed. The thermal resistance of the fabric assemblies increases with the increase in the thickness of air gap in between fabric layers. The thermal resistance of all the fabric assemblies at any given air layer thickness is highest under non-convective mode of heat transmission, followed by natural convection mode and the forced convection mode shows least thermal resistance. Incorporation of coated fabric in the outer layer reduces the effect of forced convection. ANOVA has been prepared and F value has been calculated to find the effect of modes of convection, type of fabric and thickness of air layer on thermal transmission properties. The results obtained from this detailed study will help in designing multilayered clothing assemblies suitable for different climatic conditions.     

风速对单双层着装状态下运动服针织面料湿阻的影响

为构建软风范围内单双层着装状态下运动服面料的湿阻预测有效模型,选取常用的12种T恤、8种外套面料,实验测试了4种风速下的面料湿阻,通过聚类分析获取代表性的T恤和外套面料,模拟T恤和外套的双层着装状态,测试不同风速下T恤与外套双层运动服针织面料之间的湿阻。构建了T恤和外套面料湿阻与风速的三阶多项式模型、双层组合面料湿阻与内外层面料湿阻之间的线性模型。研究结果表明:在软风范围内,T恤、外套及其双层组合面料均随风速增大而减小,内层T恤面料湿阻对双层组合运动服面料的湿阻影响更大;T恤、外套面料湿阻预测模型平均绝对百分比误差分别为2.22%、4.85%,双层组合湿阻模型平均绝对百分比误差为3.20%。     

Thermo-physiological comfort properties of double-face knitted fabrics made from different types of polyester yarns and cotton yarn

Double-face knitted fabrics with hydrophobic inner and hydrophilic outer layers are characterised by their advantageous thermo-physiological comfort property that facilitates the transport of sweat from skin to outer fabric layer where it can be evaporated easily. In this study, for the production of double-face knitted fabrics, cotton yarn as hydrophilic yarn type and five different polyester filament yarns consisting of standard polyester, hollow polyester, micro polyester, textured polyester and textured micro polyester as hydrophobic yarn type were used. In order to determine the thermo-physiological comfort properties of the fabrics, air permeability, water vapour permeability, thermal conductivity, thermal resistance and overall moisture management capacity were measured. The results were comparatively analysed using statistical methods. The experimental results demonstrated that the polyester-type yarns and the combinations of them with the cotton yarn in fabric layers affected the thermo-physiological comfort properties significantly. The fabrics with polyester-type inner face and cotton outer face showed the best moisture transmission properties.     

An investigation of thermal comfort properties of Abaya woven fabrics

Abaya is a traditional Muslim woman’s outer garment. It is black in colour, and must be worn over the normal day-to-day clothing according to Islamic law. It is mandatory to wear Abaya in Arabian Gulf countries irrespective of the outside environmental temperature, which can be up to 50°C. Having many layers of clothing including Abaya makes it extremely uncomfortable for the wearer in a hot environment. Thermal comfort performance is, therefore, essential for fabrics used for Abaya. This study investigated some commercially available woven Abaya fabrics for thermal resistance, air permeability, thermal comfort, vapour resistance and fabric structural and surface properties. The results indicated that the Abaya fabrics with different weave structures, fibre composition and fabric weight have greater influence on the fabric thermal comfort performance.     

结构参数对超高分子量聚乙烯织物导热性的影响

为了提高服装热量的传导,采用导热率较高的超高分子量聚乙烯(UHMWPE)纱线作为纬纱与涤纶进行交织制成织物,并以电热片作为热源,通过铂电阻测温仪测量距离热源边界0、2、4 cm处织物表面温度随时间的变化。采用变量分离法测试纤维种类、纱线线密度、织物密度以及织物组织结构等因素对超高分子量聚乙烯织物导热性的影响。结果表明:含UHMWPE纱线交织物的导热性明显好于涤纶/涤纶和涤纶/锦纶交织物,且纱线越粗、织物密度越大、组织单元内纱线交织次数越少,织物导热性越好。     

消防员防护服面料的热湿舒适性

为研究消防员防护服面料的舒适性并考察其是否满足欧美国家相关标准,选取了我国消防员防护服常用的几种面料,进行单层织物热阻和湿阻以及多层织物热阻、湿阻和总热损失的测试与分析,考察空气层对多层织物热阻的影响,并将测试结果与欧美标准的相关要求进行对比。结果表明:在厚度大致相同时,外层面料的密度对热阻和湿阻影响较大;因为隔热层材料是非织造布结构,热阻和湿阻较大;空气层的位置对多层织物的热阻值影响不大,但其厚度对多层织物的热阻影响较大;选取的几种面料组合,湿阻低于30 Pa·m~2/W,总热损失高于205 W/m~2,均满足欧美国家相关标准要求。     

出汗热护式热板仪系统的设计分析与试验研究

为了解出汗热护式热板仪的工作原理及相关测量标准,对国际上2种典型的SGHP和M259B出汗热护式热板仪的设计特点进行分析,对相关标准下特别是等温湿阻和不等温湿阻的测量原理进行阐述。使用SGHP-10.5型热板仪测量了20块面料的热阻、等温湿阻和不等温湿阻,结果发现,外气流层温度设定的差异对测量结果没有影响。在湿阻测量中发现,等温湿阻比不等温湿阻普遍大,均值高17.7%,推断在不等温湿阻的二步法测量中,假设面料在干湿2种状态下的热阻相同是造成误差的主要原因。与文献中使用M259B型热板仪的测量数据进行比较发现,空板数据差异巨大,推测M259B型热板仪相较SGHP-10.5型存在更大的系统误差。     

The Compressional Behaviour of Spunbonded Nonwoven Fabrics

Spunbonded nonwoven fabrics are extensively used in a number of technical applications because of their physical, tensile, and hydraulic characteristics. In many cases, fabric is subjected to normal compressive loads, and the physical, tensile, and hydraulic properties change with these loads depending on the compressional behaviour of the fabric. It is important to characterise the compressional behaviour of fabrics before their effective use in these applications. Two parameters, α and β, describing compression and recovery curves of different types of spunbonded fabrics have been evaluated. A comparative study on the compressional behaviour of different types of spunbonded-fabric structure is reported. The compressibility of spunbonded heat-sealed fabrics has been found to be much lower and their compressional resilience much higher than the compressibility and compressional resilience of needle-punched spunbonded fabrics. The compressibility of surface-calendered needle-punched spunbonded fabrics is lower than that of untreated needle-punched fabrics while their compressional resilience is higher than that of needle-punched spunbonded fabrics. However, the values of both compressibility and compressional resilience of surface-calendered needle-punched spunbonded fabrics are much closer to those of needle-punched spunbonded fabrics than those of heat-sealed spunbonded fabrics. The effect of fibre linear density on compressional behaviour for different types of spunbonded nonwoven structures has also been reported.     

Ranking fibre and process parameters affecting thermal resistance of needle-punched blankets using neural network model

In this paper, an artificial neural network (ANN) model has been designed to predict the thermal resistance of needle‐punched blankets. Web‐laying (parallel‐ and cross‐laid), fibre fineness, fibre degree of hollowness, fabric weight, depth of needle penetration and needle punch density are considered as input parameters to predict the thermal resistance of needle‐punched nonwoven blankets. In order to reduce the dependency of the results on a specific partition of the data into training and testing sets, three‐way cross validation tests were performed, that is, total data were divided into training and testing sets in three different ways. The predicted thermal resistance correlated well with the experimental thermal resistance. The relative contribution of each parameter to the overall prediction of the thermal resistance was studied by carrying out a sensitivity analysis of the test data set. The results of sensitivity analysis show that web‐laying is the most important input parameter, followed by depth of needle penetration, fabric weight, degree of fibre hollowness, needle punch density and fibre fineness.     

Modelling of thermal conductivity of knitted fabrics made of cotton–bamboo yarns using artificial neural network

Regenerated cellulosic fibre made from bamboo is gaining popularity for apparel use due to its improved functional properties. This paper presents the modelling of thermal conductivity of knitted fabrics made from blended yarns of cotton and bamboo fibres using an artificial neural network (ANN). Five parameters, namely knitted fabric structure type, yarn linear density, bamboo fibre proportion (%), fabric thickness and fabric areal density, were used as inputs to the ANN model. The developed model was able to predict the thermal conductivity of fabrics with very good accuracy. The trend analysis of the developed model revealed the influence of various input parameters on the thermal conductivity of knitted fabrics. These findings can be judiciously used for the selection of optimum material and structural parameters of knitted cellulosic fabrics for a particular end‐use.     

针织运动面料的差动毛细导湿性

 根据差动毛细效应的原理,利用内外层单纤线密度的差异,采用具有导湿快干性能的异形涤纶长丝,编织具有定向传导功能的针织运动面料,通过测试比较发现:织物内外层原料的单纤线密度差异越大,织物的差动毛细效应越显著;当织物内外层单纤线密度比值相同时,若织物组织结构不同,其差动效应大小也不同;以3层组织结构织物的差动效应尤为显著。     

消防服外层织物热防护性与舒适性综合评价

为保证消防服具有良好的热防护性能和较好的热湿舒适性能,选取7种消防服用外层织物为研究对象,测试了织物热防护性能及舒适性能相关指标,分析了织物原料及性能参数等因素对热防护性能与舒适性能的影响,并阐述其影响规律;采用模糊综合评判的方法综合评价织物热防护性能与舒适性能。结果表明：织物的热防护性能与其原料组成、织物厚度及紧度相关,舒适性能主要与织物密度、紧度以及织物厚度、面密度有关;在测试的7 种织物中芳纶防静电防护织物的综合性能最佳,而腈纶/ 棉混纺防护织物的性能较差。