The effects of yarn number and liquid ammonia treatment on the physical properties of hemp woven fabrics

The effects of yarn number and liquid ammonia (L/A) treatment on the physical properties of woven fabrics prepared with pure hemp spun yarns were investigated. As a result of L/A treatment, the crystal structure of hemp fiber was changed from cellulose I to the mixtures of cellulose III and cellulose I and its crystallinity was slightly decreased by 13 %. The crease recovery of hemp fabric treated with L/A was improved upto 78 %. The washing shrinkage of hemp fabric treated with L/A decreased significantly to less than 0.4 %, while the washing shrinkage of hemp fabric prepared with the fined yarn was superior to that of hemp fabric prepared with the coarsed yarn. Especially, the wicking speed and drying ratio of hemp fabrics treated with L/A were higher than those of the untreated as yarn number increased. However, it was found that there is no significant effect on the UV protection of the L/A treated hemp fabrics.     

Mechanical,thermal and interfacial properties of green composites from basalt and hybrid woven fabrics

Composites based on pure Basalt and Basalt/Jute fabrics were fabricated. The mechanical properties of the composites such as flexural modulus, tensile modulus and impact strength were measured depending upon weave, fiber contents and resin. Dynamic mechanical analysis of all composites were done. From the results it is found that pure basalt fiber combination maintains higher values in all mechanical tests. Thermo-gravimetric (TG/DTG) composites showed that thermal degradation temperatures of composites shifted to higher temperature regions compared to pure jute fabrics. Addition of basalt fiber improved the thermal stability of the composite considerably. Scanning electron microscopic images of tensile fractured composite samples illustrated that better fiber-matrix interfacial interaction occurred in hybrid composites. The thermal conductivity of composites are also investigated and thermal model is used to check their correlation.     

Mechanical properties of breathable waterproof fabrics with seaming and sealing processes

Waterproof fabrics are seamed and sealed by waterproof sealing tape to prevent water from penetrating through the stitch holes. As this process may change the mechanical properties of breathable waterproof fabric related to its deformation with human body, the changes in mechanical properties were investigated. In both of parallel and perpendicular directions, tensile characteristics were remarkably changed with seaming and sealing processes. The increase of LT and WT means that the clothing sealed by waterproofing tape may produce somewhat discomfort feeling. On the other hand, the bridge of the sewing thread seemed to be reinforced by waterproofing tape. Shear characteristics such as G, 2HG, and 2HG5 gradually increased with seaming and sealing processes in parallel direction. However, they decreased with sealing process in perpendicular direction because the seam line work as an axis located at the center of the testing range.     

Enhanced visualization of simulated woven fabrics

The woven fabric graphics designed with available computer aided design (CAD) systems using different colored warp and weft yarns look quite different from the appearance of their actual fabrics. To enhance the visual effects of designed woven fabric graphics, this paper reports a modified CAD woven fabric system, which allows users to design a fabric using parameters including fabric weaves, yarn number, yarn material, fabric count, crimp shape of interwoven yarns, and illumination. This enhanced system can design both yarns and fabrics, and consider the transitional color effect around interweaving points of warp and weft yarns. Its simulation image quality of woven fabrics has been greatly improved, and several textile mills and universities are currently using this woven fabric design system.     

Low stress mechanical properties of fabrics woven from bamboo viscose blended yarns

This paper presents the low stress mechanical properties of plain fabrics woven from cotton, bamboo viscose and cotton-bamboo viscose blended yarns. Three blends (100 % cotton, 50:50 cotton-bamboo and 100 % bamboo) were used to produce three yarn counts (20, 25 and 30 Ne). Each of these yarns was used to make fabrics with different pick densities (50, 60 and 70 picks per inch). It was found that bending rigidity, bending hysteresis, shear rigidity, shear hysteresis and compressibility is lower for bamboo fabrics as compared to those of 100 % cotton fabrics. On the other hand, extensibility, tensile energy and compressional resilience are higher for 100 % bamboo fabrics than 100 % cotton fabrics. Higher pick density increases linearity of load-elongation curve, bending rigidity, shear rigidity and compressional resilience. Shear and bending rigidities show very good correlation with the respective hysteresis values.     

Investigation of mechanical properties of basalt woven fabrics by theoretical and image analysis methods

This paper explains a study conducted to evaluate mechanical properties of woven structures of basalt. The mechanical properties like shear strength and tensile strength were studied. Tensile properties of basalt hybrid and non-hybrid fabrics are predicted by computational tool and verified with experimental data. The shear strength was investigated by using picture frame fixture. The tests were recorded by a CCD monochrome camera during displacement of specimen at various positions. The images were used for image analysis program developed in MATLAB. The results of image analysis were compared with the actual experimental results. The results illustrate that the mechanical properties of fabrics experience a marked improvement when hybridization of basalt with polyester and polypropylene in different sets of weaves takes place. These findings are important requirements for using such fabrics for high-tech applications and composite forming.     

The effect of different connections in double layered woven fabrics on comfort properties

With the increasing demand of fabrics for special usage areas, more complex woven structures are designed and from the structural point of view, especially the parameters which affect the comfort properties become more important. This paper reports the effect of structural parameters of double layered woven fabrics, such as number of interlacing picks, period of interlacing and number of weft skips on the basic comfort properties of the fabrics (thickness, air permeability and wicking properties) produced according to Taguchi orthogonal array design. The investigated parameters were determined before and after finishing treatment. According to the results, it is found that period of interlacing has an important effect on the thickness and air permeability of both untreated and treated fabrics whereas in terms of drying coefficient, the effect of the investigated parameters is not statistically important.     

Empirical modelling of tensile strength of woven fabrics

Aesthetic properties of fabrics have been considered as the most important fabric attribute for years. However, recently there has been a paradigm shift in the domain of textile material applications and consequently more emphasis is now being given on the mechanical and functional properties of fabrics rather than its aesthetic appeal. Moreover, in certain woven fabrics used for technical applications, strength is a decisive quality parameter. In this work, tensile strength of plain woven fabrics has been predicted by using two empirical modelling methods namely artificial neural network (ANN) and linear regression. Warp yarn strength, warp yarn elongation, ends per inch (EPI), picks per inch (PPI) and weft count (Ne) were used as input parameters. Both the models were able to predict the fabric strength with reasonably good precision although ANN model demonstrated higher prediction accuracy and generalization ability than the regression model. The warp yarn strength and EPI were found to be the two most significant factors influencing fabric strength in warp direction.     

Mechanical and water absorption properties of woven jute/banana hybrid composites

This work aims to predict the mechanical properties of woven jute/banana hybrid composite. Woven fabrics are arranged in three layers of different sequence. Resin used in this work is Epoxy LY556 with hardener HY951. Composite specimen are prepared by hand-layup techniques. The effect of layering sequence on the mechanical properties namely tensile, flexural and impact was analysed. It is found that the tensile and flexural strength of hybrid composite (Banana/Jute/Banana) is higher than that of individual composites. Similarly, the impact strength of Jute/Banana/Jute hybrid composite is better than other types of composite. It is found that the moisture absorption of woven banana fiber composite is lesser than the hybrid composite. Fractography study of the fractured specimen is carried out using scanning electron microscope to analyse the fracture behaviour of the hybrid composite.     

Mechanical properties and tactile sensation of naturally colored organic cotton fabrics

This study was carried out to investigate mechanical properties of naturally colored organic cotton (NaCOC) fabrics, to evaluate tactile sensory perceptions, and finally to identify the related mechanical parameters with the sensory perceptions. Two species, coyote-brown and green NaCOC fiber, commercially available, were selected and woven into plain and twill fabrics. Seventeen mechanical properties were measured by KES-FB system. Then, primary hand value (PHV) and total hand value (THV) were calculated by KN-203-LDY and KN-302-SUMMER, respectively. For sensory perception evaluation, 30 participants answered the questionnaire consisted of nine different bipolar adjectives dealing with tactile sensation using the semantic differential scale (SDS). As the result of mechanical properties, there were meaningful differences in shear, surface, compression properties, thickness, and weight of 4 NaCOC fabrics. For hand value, a coyotebrown twill fabric was evaluated as the most appropriate for lady’s summer dress applications. In sensory perception evaluation, meaningful differences of sensory perception were shown among 4 specimens except ‘fineness’ and ‘wetness’ perceptions. Prediction models for sensory perceptions of NaCOC fabrics were extracted by regression analysis in ‘softness’, ‘fineness’, ‘warmth’, ‘pliability’, ‘limpness’, ‘thinness’ and ‘wetness’ perceptions.     

Behaviour of the twill weave woven fabrics during relaxation

This work looks into the behaviour of the twill weave woven fabrics during relaxation (when the weaving tension is released). Ten, 50-metre rolls of twill weave woven fabrics were produced. The fabrics were marked in a rectangular form at the weaving loom. After 48 hours of relaxation, the new shapes and sizes were recorded. The shapes of almost all of the samples were changed to parallelogram, even though they differed in size. The work showed that the manner of fabric deformation during relaxation depends upon the fabric structure. It indicates that contraction due to relaxation of the twill weave causes the woven fabric to skew. in the direction of the twill. The quantity of the skewness is related to the float length andthe twill type. Fabrics with longer float length have higher skewness.     

Formability analysis of worsted woven fabrics considering fabric direction

Over years predicting fabric behaviour during garment manufacturing process was considered by researchers in order to reduce manufacturing problems and achieve high quality products. Fabric formability which is affected by bending and tensile behaviour through the application of small loads is a property which can predict fabric performance precisely. However, this property changes regarding fabric direction and is not constant. In this study, fabric formability is examined for worsted woven fabrics in a more detailed way by evaluating this property in various fabric directions. It was concluded that fabric formability could be expressed as a sinusoidal function of sample orientation towards warp direction. Moreover, studying several weave structures with different weft densities reveals that the less the firmness of fabric construction the more the value of fabric formability which indicates the better adaption of fabric to the exerted deformation.     

Antimicrobial treatment properties of Tencel Jacquard fabrics treated with ginkgo biloba extract and silicon softener

Tencel Jacquard fabric is one of the eco-fabrics used for underwear, sportswear, bedclothes, clothes for aged people, and hospital textiles. It is popular for these uses because it is easy to process into yarns and fabrics alone or in blends, very stable in washing and drying, thermally stable, and easy to dye with deep vibrant colors using direct, reactive, or vat dyes. In order to provide antimicrobial properties for Tencel Jacquard fabrics, they were treated with ginkgo biloba extract and silicon softener using two different processes so the results could be compared. One of the processes treated the fabrics with ginkgo biloba extract and silicon softener simultaneously, and the other process treated the fabrics with these agents sequentially. The treated Tencel Jacquard fabrics were characterized by scanning electron microscopy, and their antimicrobial properties were evaluated. In addition, water repellency, air permeability, water vapor permeability, and yellowness were measured. It was observed that the ginkgo biloba extract and silicon softener were present on the surface of the treated fibers, and the quantity of these agents before and after laundering was proportional to the measured antimicrobial activity of the fabrics before and after laundering. Fabrics treated with both agents had stronger water/oil repellency than fabrics treated with only ginkgo biloba extract. As the quantities of the two treating agents on fabrics were increased, their air permeability and water vapor permeability decreased. No significant changes were observed for yellowness based on the amounts of treating agents applied. From these results, it is expected that Tencel fabrics treated with ginkgo biloba extract and silicon softener are excellent for use as bedclothes.     

Mechanical properties and crystallization behavior of polypropylene non-woven fabrics reinforced with POSS and SiO2 nanoparticles

PP/POSS and PP/SiO₂ composite non-woven fabrics filled with polyhedral oligomeric silsesquioxanes (POSS) and SiO₂ respectively using a convenient blending method were prepared through melt-blown process with corona charging. The morphology of the composite fibers and the distribution of POSS and SiO₂ nanoparticles in PP matrix were investigated by field-emission scanning electron microscope (FSEM) and transmission electron microscope (TEM), respectively. POSS and SiO₂ can act as nucleating agent and accelerate the crystallization process during nonisothermal cooling. The shear storage modulus G??, loss modulus G??, and complex viscosity ??* of non-woven fabric reduce when 1 wt % POSS was added and increase for PP5/POSS composite non-woven fabric compared with pure PP non-woven fabrics. However, all G??, G?? and ??* of PP/SiO₂ non-woven fabric decrease with increasing SiO₂ content owing to plasticization by SiO₂. Both stress and elongation at break of the PP/POSS melt-blown non-woven fabrics are improved compared with PP non-woven fabrics, however decrease when SiO₂ was added, as compared to the neat PP non-woven fabric. The onset temperature of decomposition for both the PP/POSS and PP/SiO₂ composite non-woven fabrics is higher (5?C10 °C) than pure PP and char content is increased with increasing POSS and SiO₂.     

Simulation of the weave structural design of synthetic woven fabrics

This study surveys the basic procedure of data base system of the fabric structural design which can be linked with existing pattern design and garment design CAD systems. For this purpose, the theoretical and empirical equations related to the fabric structural design are analyzed and discussed with various fabric specimens. The fabric structural parameters such as weave density coefficient, cover factor and yarn density coefficient of various kinds of fabrics are calculated using the empirical equations. These calculated fabric structural parameters of many kinds of polyester and nylon fabrics are compared and discussed with weave pattern, and materials such as polyester and nylon. Furthermore the difference between fabric structural parameters calculated by empirical equations are analyzed with polyester and nylon fabrics as a basic study for data base system of the fabric structural design. Finally, the weave density coefficients of polyester and nylon fabrics were analysed and discussed with shrinkages of dyeing and finishing processes, and also surveyed according to the weaving company and weave structural parameters such as weave pattern and denier.     

Stab-resistant property of the fabrics woven with the aramid/cotton core-spun yarns

Aramid fibers are mainly used for industrial applications and human body protection against ballistic threats. But they are used mostly in forms of composites. And fabrics woven with a high yarn count offer a moderate protection performance against the knife stabbing due to the low shear strength. This research is focused on investigating the effect of the aramid core-spun yarns on the stab resistance of the woven fabrics. With the aramid core-spun yarns with core to sheath weight ratio of 1 to 2.5 the armor specimens having different fabric densities were prepared and the knife edge impact test was conducted. On the impact energy of the knife at the level 1 according to the NIJ standard, the drop tower test results demonstrated that fabric density of the armor specimens affected the stab resistance significantly. The penetration depth of the impactor through the armor specimens was associated with the thickness and mass of the armor sample in different ways. Being the stab resistance introduced by considering the penetration depth of the impactor via thickness and weight per surface area, the effects of the fabric conditions on the anti-stabbing property could be systematically analyzed and turned out that there was an optimal level of the fabric density, showing the most effective stab resistance.     

Predicting bending rigidity of woven fabrics by neuro-genetic hybrid modeling

The possibility of prediction of bending rigidity of cotton woven fabrics with the application of Neuro-genetic model has been explored. For this purpose, number of cotton grey fabrics meant for apparel end-use was desized, scoured, and relaxed. The fabrics were then conditioned and tested for bending properties. A feed-forward neural network model was first formed and trained with adaptive learning rate back-propagation with momentum. In the second model, a hybrid learning strategy was adopted. A genetic algorithm was first used as a learning algorithm to optimize the number of neurons and connection weights of the neural network. Later, a back-propagation was applied as a local search algorithm to achieve global optima. Results of hybrid neural network model were compared with that of back-propagation neural network model in terms of their prediction performance. Results show that the prediction by Neuro-genetic model is better in comparison with that of back-propagation neural model.     

Static lateral compression of hemp/filament hybrid yarn knitted fabrics

The novel designed hemp/filament hybrid yarns were used to produce knitted fabrics in order to investigate the influence of the unique internal structure of hybrid yarns on compressional behavior of clothing textile materials. The knitted fabrics are subjected to successive compression-release cycles and the compression-release curves obtained made it possible to calculate the particular compression parameters such as recoverable and irrecoverable compression. By using the parameters the non-elastic deformation components (viscoelastic and plastic deformation) are determined. In spite of generally accepted fact that van Wyk’s theory has some limitations, since it does not explain the hysteresis caused by fiber slippage and friction effects, the two-parameter mechanical model derived from van Wyk’s compression theory is applied successfully to determine the compression hysteresis.     

Predicting bending rigidity of woven fabrics using artificial neural networks

This paper reports an investigation on the predictability of bending property of woven fabrics from their constructional parameters using artificial neural network (ANN) approach. Number of cotton grey fabrics made of plain and satin weave designs were desized, scoured, and relaxed. The fabrics were then conditioned and tested for bending properties. Thread density in fabric, yarn linear density, twist in yarn, and weave design were accounted as input parameters for the model whereas bending rigidity in warp and weft directions of fabric formed the outputs. Gradient descent with momentum and an adaptive learning rate back-propagation was employed as learning algorithm to train the network. A sensitivity analysis was carried out to study the robustness of the model.     

Predicting the air permeability of polyester/cotton blended woven fabrics

The aim of this study was to model the air permeability of polyester cotton blended woven fabrics. Fabrics of varying construction parameters i.e. yarn linear densities and thread densities were selected and tested for air permeability, fabric areal density and fabric thickness. A total of 135 different fabric constructions were tested among which 117 were allocated for development of prediction model while the remaining were utilized for its validation. Four variables were selected as input parameters on basis of statistical analysis i.e. warp yarn linear density, weft yarn linear density, ends per 25 mm and picks per 25 mm. Response surface regression was applied on the collected data set in order to develop the prediction model of the selected variables. The model showed satisfactory predictability when applied on unseen data and yielded an absolute average error of 5.1 %. The developed model can be effectively used for prediction of air permeability of the woven fabrics.