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Water vapour diffusion through textile fabrics plays a crucial role in maintaining body comfort. Developing and producing comfortable textiles is a major challenge for manufacturers of fibres, yarns and fabrics. This study aims to develop a simple model to predict the water vapour permeability of textile fabrics as a function of their structural parameters to assist manufacturers in developing comfortable fabrics. To achieve this goal, geometric modeling of the woven structure was proposed to calculate porosity at the micro-and macro-pores level. Two mathematical models were introduced based on the principle of diffusion of water vapour through a textile fabric. To validate the two models, a series of 18 samples was prepared with three basic fabric structures: Plain, Twill and Turc Sateen. To vary the compactness of the structures, three weft densities were chosen: 18, 21 and 24 picks/cm. In addition, since the material influences water vapour diffusion, two types of weft yarns were inserted: 50% CO/50% PET and 100% PET. The results show that the two models are reliable for predicting water vapour resistance (Ret) depending on the structural parameters of the textile fabric. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to investigate the dynamic measurement of the water vapour resistance. The water vapour diffusion kinetics depends on the fibre's material. So, water vapour resistance measurement times till the equilibrium steady state can vary in the case of natural fibres compared to synthetic fibres. Devices for determining water vapour resistance according to the ISO 11092 standard allow static values to be measured. Design/methodology/approach: In this study to investigate the dynamic of the water vapour resistance, a new parameter named "holding period" was introduced and defined as the time from sample placement on the measuring head until the measuring process begins. The holding period was varied as 0, 30, 60, 90, 120, 180, 240 and 300 s. Wool and cotton knitted fabrics were tested as natural fibres and compared to 100% polyester and 90% polyester/10% elastane as synthetic fibres. Measurements were conducted under both air velocities of 1 and 2 m/s. The experimental test data were statistically analysed based on ANOVA and four-in-one residual plots. Findings: Statistical analysis of experimental tests shows that the holding period affects water vapour resistance in both air velocities of 1 and 2 m/s and on the measured values in the case of hydrophilic fibres. Research limitations/implications: The study of the dynamic relative water vapour permeability of natural and synthetic is an important area of interest for future research. Practical implications: It is recommended to hold the samples on the top of the head measurement before starting the test. Originality/value: Following the ISO 11092 standard, the static values of the water vapour resistance were measured without considering the dynamic behaviour of the water vapour diffusion through the textile fabrics. This paper fulfils an experimental dynamic measurement of the water vapour resistance. [ABSTRACT FROM AUTHOR]

The main aspect of this research was to predict the drape parameters and describe clearly the drape phenomenon using fuzzy logic method. Forecasting features allow manufacturers to save time and improve their productivity. The bending rigidity, (in warp, weft, and skew direction), shear rigidity, and weight of fabric samples were used as the key input variables for the model, whereas drape coefficient, drape distance ratio, folds depth index, and node number were used as output/response variables. The results show that changing the values of fabric parameters significantly affected the fabric drape and a representative correlation values were found between the experimental values and those calculated by the fuzzy system.

An artificial neural network (ANN) model was developed to predict the drape coefficient (DC). Hanging weight, Sample diameter and the bending rigidities in warp, weft and skew directions are selected as inputs of the ANN model. The ANN developed is a multilayer perceptron using a back-propagation algorithm with one hidden layer. The drape coefficient is measured by a Cusick drape meter. Bending rigidities in different directions were calculated according to the Cantilever method. The DC obtained results show a good correlation between the experimental and the estimated ANN values. The results prove a significant relationship between the ANN inputs and the drape coefficient. The algorithm developed can easily predict the drape coefficient of fabrics at different diameters.

The aim of this study is to enhance the fiber-matrix interface of cotton waste reinforced composite panels by a specific chemical treatment. For this purpose, cotton fibers are treated in sodium hydroxide (NaOH) solution with three different concentrations (0.5 M, 1 M, and 1.5 M) and three different soaking times combinations (1 h, 3 h, and 5 h). Mechanical evaluation of treated and untreated reinforcements and composite panels are characterized using tensile test whereas the chemistries of fiber reinforcements are investigated using Fourier-transform infrared spectroscopy analysis and the fiber-matrix interactions are morphologically examined using scanning electron microscopy. Results indicate a remarkable enhancement in mechanical properties of composites via improving the interfacial adhesion and compatibility between fiber and matrix with a significant increase of Young modulus up to 270% for reinforcements and to 70% for composite materials compared to untreated materials.

A new method for predicting correlation between fabric parameters and the drape is developed. This method utilises a Principal Component Analysis (PCA) of intercorrelated influencing parameters (bending rigidity, weight, thickness) and the drape parameters (drape coefficient and the node number). This paper describes the PCA procedure and presents the similarities and contrasts between variables.

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Satisfaction of wearing of clothing is generally affected by clothing comfort properties and specifically by psychological perceptions of the wearer. A woven fabric mostly contains protruding fibers on the surface, which should be removed by burning, clipping, or brushing for appropriate processing. This paper deals with the effect of brushing on thermo-physiological comfort properties of woven fabrics. Three basic woven structures (plain, twill and sateen) were selected for this study. Thermal conductivity, thermal resistance and thermal absorptivity of these fabrics were measured by the Alambeta tester. Moreover, also water vapor permeability and air permeability were experimentally determined. The brushing treatment was applied manually by 1% and 3% of weight loss. A sample without brushing was considered as reference. Consequently, brushing affected the thickness, thermal properties, air permeability and water vapor permeability. With the increase in brushing application water vapor transmission decreased but thermal resistance increased. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a saturation rate during the capillary rise of a textile fabric was determined. A mathematical model based on the Archie's law, considering the electrical resistivity, saturation rate and fabric tortuosity was established. In order to determine the saturation exponent a calibration method was introduced. According to this method the spatiotemporal distribution of the saturation rate during the capillary rise is presented. This method was also used to evaluate the saturation rate during the horizontal and downward capillary rise. It was found that the saturation rate remains constant for the case of the horizontal and descending impregnation. [ABSTRACT FROM AUTHOR]

The effect of a stain repellent treatment on the water-oil repellency characteristics of plush knitted fabrics is investigated. We compared the efficiency of two methods of modeling; a Multicriteria analysis was employed by means of surface response method and an artificial intelligence-based system approach is presented by fuzzy logic modeling in which the effects of the operating parameters and intrinsic features of fabrics are studied. These parameters were pre-selected according to their possible influence on the outputs which were the contact angle and the air permeability. An original fuzzy logic-based method was proposed to select the most relevant parameters. The results show that air permeability was influenced essentially by knitted structure's parameters but the variation of treatment parameters has a great effect on the contact angle. Thus, it is believed that artificial intelligence system could efficiently be applied to the knit industry to understand, evaluate, and predict water-oil repellency parameters of plush knitted fabrics more than Multicriteria analysis. [ABSTRACT FROM AUTHOR]