Yarn Length Research Articles

Versatile fabrication of carbon nanotube yarn composites by in-situ interfacial polymerization of polyetherimide

Manufacturing of high-performance carbon nanotube (CNT)-based polymer composites has long been complicated by the difficulty of infiltrating the nanoporous network presented by continuous CNT materials; this can yield composites with heterogeneities that drastically worsen their mechanical properties. We show the synthesis of CNT-polyetherimide (PEI) composite yarns via in-situ interfacial polymerization (ISIP), which side-steps slow, viscous polymer transport by infiltrating and reacting monomer species in-situ via a rapid and scalable process. We demonstrate the ISIP technique on two distinct, industrially-produced CNT yarns, and identify processing parameters that achieve conformal polymer coatings, yielding statistically-significant increases to linear density-specific tensile properties. Using ISIP on pre-densified yarns results in composites with specific stiffness and tenacity of 142 N/tex and 2.2 N/tex, respectively. When ISIP is applied to lightly-processed, porous CNT yarn, the specific stiffness and tenacity reach up to 66 N/tex and 0.7 N/tex. The role of interfacial effects, particularly from amorphous carbon, on the composite properties is also explored. Finally, we demonstrate a prototype roll-to-roll ISIP apparatus which can process arbitrary lengths of yarn for continuous composite production.

Integration of recycled denim waste cotton fibre and jute fibre in thermoplastic bio composite applications

High-stiffness and high-strength natural fibres are commonly utilized in thermoplastic matrices to manufacture biobased thermoplastic composites. Low-end applications such as construction and furniture industries do not require a high load-bearing capacity, thus favoring cost-effective, moderately strong, sustainable natural materials and quickly manufacture thermoplastic composites. Recycled biobased cotton fibres collected from the denim industry can effectively penetrate this composite industry due to their cost-effectiveness and desirable physical and mechanical properties. However, retaining structural integrity and enhancing the reinforcing efficiency of recycled yarns in composites pose challenges. Addressing these issues, we propose a new method of extracting recycled cotton from denim waste fabric and transforming it into dry preform with minimal damage to the structural integrity of cotton fibres. Jute fibres have been introduced alongside recycled denim fibers within a polypropylene matrix to optimize the hybrid reinforcing efficacy of the composites. The effect of denim fibre length on composite quasi-static tensile and flexural test results showed that a yarn length of 20 mm yielded the highest tensile strength (⁓27.83 MPa), tensile modulus (⁓ 1.76 GPa), flexural strength (⁓62.35 MPa), and flexural modulus (⁓1.17 GPa). Composites comprising recycled denim yarn and jute fibre improved the tensile modulus to approximately ⁓2.1 GPa and the impact strength to approximately ⁓66.1 kJ/m2, following the hybrid rule of mixture, while jute fiber serves to increase the stiffness and toughness of the composites. This work demonstrates that recycled denim cotton fibre and strong jute fibre can be successfully integrated into thermoplastic composites to achieve tailored mechanical properties.

Bio-Inspired Textiles for Self-Driven Oil-Water Separation-A Simulative Analysis of Fluid Transport.

In addition to water repellency, superhydrophobic leaves of plants such as Salvinia molesta adsorb oil and separate it from water surfaces. This phenomenon has been the inspiration for a new method of oil-water separation, the bionic oil adsorber (BOA). In this paper, we show how the biological effect can be abstracted and transferred to technical textiles, in this case knitted spacer textiles hydrophobized with a layered silicate, oriented at the biology push approach. Subsequently, the transport of the oil within the bio-inspired textile is analyzed by a three-dimensional fluid simulation. This fluid simulation shows that the textile can be optimized by reducing the pile yarn length, increasing the pile yarn spacing, and increasing the pile yarn diameter. For the first time, it has been possible with this simulation to optimize the bio-inspired textile with regard to oil transport with little effort and thus enable the successful implementation of a self-driven and sustainable oil removal method.

Mathematical modeling of dynamic yarn input tension on circular weft knitting machine with positive storage feeding

Yarn input tension (YIT) during knitting has a profound impact on fabric quality. Modern high-speed circular knitting machines are mostly equipped with positive feed system, where a predetermined length of yarn is supplied to knitting zone. Several contributing factors affect YIT and keeping YIT in precise setting is a complex phenomenon. A plethora of studies addressed yarn tensile analysis for different knitting systems. However, a comprehensive description of generated YIT for a positive storage feed based circular weft knitting machine is still missing. This study aimed to navigate YIT mathematically through a model development by analyzing yarn tensile forces for different zones of yarn path in dynamic knitting operation. The model revealed several YIT contributing variables. After evaluating the governing equation, the impact of different variables, and their interdependence have also been discussed. The predicted YIT supported the actual YIT with a mean percentage error of around 10%.

Synthesis of conductive yarn to develop wearable electronic device

The demand for soft, flexible, and conformable devices that may offer electrical functionality along with the benefit of comfort is increasing with the emergence of wearable electronic devices in our daily lives. Electronic textiles (e-textile) fabrics have electronic components embedded in them and can be worn. This textile must be conformal to the body, and also smart. This article proposes the synthesis of a conductive yarn that can be knit together to textiles to fabricate a smart textile with integrated electronic capabilities, which can be used as a sensor that detects critical parameters from human body. The proposed conductive yarn has been synthesised from cotton yarn, utilising the simple dip-immersion, and drying technique. Different forms of carbon materials, such as activated carbon (AC), carbon nanotubes (CNTs), and graphite are used as conductive elements with polyvinyl acetate and deionised water as solvent. The conductive elements and the solvent are combined to prepare the conductive solution. The experiment has been carried out by varying yarn thickness and composition of conductive material with fixed yarn length. The coated yarns were analysed by developing their mathematical model using the linear fit technique. The change in resistance per unit length of the yarn was computed as the slope (kΩ/cm). The mathematical model of optimised conductive yarn is derived as y = 4.535 x + 1.93 with a conductivity of 4.17 S/m. The experimental work proves that a commercially available cotton yarn can be infused with electrical properties by coating it with a conductive material. Additionally, it has also been observed that textile-based wearable devices are possible to fabricate with simple and cost-effective techniques.

Towards an efficient multi-scale numerical model of the impact behavior of woven materials with global/local approach

This paper presents the global/local approach in the multi-scale modeling of woven material impact behavior. This approach optimally considers important microscopic mechanisms to accurately predict outcomes and reduce computational time. The inspiration for this approach stems from the specific behavior exhibited by woven materials under ballistic impact:(1) Zone 1 (Local) is a small square around the impact position, requiring comprehensive microscopic modeling to describe complex physical phenomena accurately.(2) Zone 2 (Global) represents the remaining fabric outside of Zone 1, exhibiting more global behavior and modeled with a mesoscopic model.Building upon a previous work's joining technique, an interface between these two zones is implemented and validated through numerical tensile testing. The proposed approach is then compared to the complete mesoscopic model already validated in the case of a 2D Kevlar KM2 woven fabric submitted to ballistic impact. The global/local approach demonstrates slightly greater flexibility due to the presence of microscopic yarns. It successfully predicts all microscopic phenomena while significantly reducing the degrees of freedom compared to full microscopic modeling along the entire yarn length.

Effect of braiding angle and yarn length compensating mechanism of carrier on braiding of branch-merge structure in multi-braider

Effect of braiding angle and yarn length compensating mechanism of carrier on braiding of branch-merge structure in multi-braider

Advancements in wearable ammonia sensors using polypyrrole/MWCNT coated yarn

In this study, we utilized a dip coating method to modify insulating yarn with polypyrrole and multiwall carbon nanotubes (MWCNTs) to convert it into a conductive yarn. The resulting fabricated conducting yarn underwent thorough characterization through scanning electron microscope, x-ray diffraction pattern, and thermal gravimetric analysis. Subsequently, we examined the ammonia sensing properties of the modified yarn at various stages of its development. Our findings revealed that the combination of MWCNTs followed by polypyrrole modification significantly enhanced the ammonia sensing capabilities compared to using MWCNTs or polypyrrole-coated yarn individually. Specifically, the MWCNTs followed by polypyrrole modified yarn demonstrated an excellent sensing response, remarkable repeatability (up to 24 continuous cycles), quick response time (11 ± 2 s), and recovery time (34 ± 5 s). Additionally, the sensor exhibited good linearity in detecting ammonia vapor concentrations within the range of 20–100 ppm. We also assessed the sensor’s performance with diverse vapors at room temperature, revealing its high selectivity for ammonia. Furthermore, the sensor’s response correlated linearly with yarn length. Remarkably, it demonstrated minimal sensitivity to humidity and exceptional stability over fifty days. These results have the potential to lead to the development of wearable room temperature ammonia sensors, suitable for use in agricultural and industrial chemistry, as well as in environmental, automotive, and medical applications.

Research on Siro fancy yarn properties based on the novel drafting rubber roller

Due to the intimate relationship with the yarn’s properties, rubber rollers are an integral component of the drafting process. An innovative method for generating colored Siro yarns with regularly variable linear density is discussed in this article. To manufacture Siro yarns, the procedure includes altering the rubber rollers on a ring-spinning machine. By modifying the sorts of back-top rubber rollers and including roving slivers of different hues, this form of Siro yarns may be manufactured. These alterations to the shape of the rubber rollers produce exquisite yarn. Due to the employment of rubber rollers with dynamically varying diameters, a jaw with an imperfect engagement is formed. This leads to an incomplete draft, which forms a coarse knot with a continuous variance in yarn density along the yarn length direction. The Siro fancy yarns are spun using two distinct colors of roving slivers and drafting multiples. The objective of this study was to examine the impact of two rubber rollers of different diameters on the coarse knot cycles, the rear zone drafting multiplier, and the linear density of slub Siro colored yarns.

The Detection of Yarn Roll's Margin in Complex Background.

Online detection of yarn roll's margin is one of the key issues in textile automation, which is related to the speed and scheduling of bobbin (empty yarn roll) replacement. The actual industrial site is characterized by uneven lighting, restricted shooting angles, diverse yarn colors and cylinder yarn types, and complex backgrounds. Due to the above characteristics, the neural network detection error is large, and the contour detection extraction edge accuracy is low. In this paper, an improved neural network algorithm is proposed, and the improved Yolo algorithm and the contour detection algorithm are integrated. First, the image is entered in the Yolo model to detect each yarn roll and its dimensions; second, the contour and dimensions of each yarn roll are accurately detected based on Yolo; third, the diameter of the yarn rolls detected by Yolo and the contour detection algorithm are fused, and then the length of the yarn rolls and the edges of the yarn rolls are calculated as measurements; finally, in order to completely eliminate the error detection, the yarn consumption speed is used to estimate the residual yarn volume and the measured and estimated values are fused using a Kalman filter. This method overcomes the effects of complex backgrounds and illumination while being applicable to different types of yarn rolls. It is experimentally verified that the average measurement error of the cylinder yarn diameter is less than 8.6 mm, and the measurement error of the cylinder yarn length does not exceed 3 cm.

Development and Performance Evaluation of a Small Scale Kenaf Fibre Spinning and Reeling Machine

Abstract A developed small scale kenaf spinning and reeling machine was evaluated in this study. The machine uses the principle of the ring spinning technique to produce spun kenaf-yarn (single or double-ply). The machine component includes two 0.5 kW electric motors positioned on a 640×433×10 mm mild steel frame (with speeds of the electric motors controlled by 0.5 kW variable frequency drives), twisting spindle, inlet frustum, feed roller shaft, reeling and spinning shafts, bearings, and a bevel gear. The machine was evaluated using different spinning speeds (90, 100 and 110 rpm), reeling speeds (60, 70 and 80 rpm) and a kenaf sample (Ifeken DI 400). At the spinning and reeling speeds combination of 90 and 80 rev·min−1, the developed machine was able to produce a continuous length of kenaf yarn twisted at 95.5 turns per minute with a production speed of 0.94 m·min−1 at the highest efficiency (88.9%) of the machine. The level of twist of the spun yarn spun provides information on the required twist level for kenaf fibre as deviation from this value was discovered to cause deformation on the spun yarn. This machine was able to reduce the drudgery involved in the production of spun kenaf-yarn and the technology is expected to positively influence kenaf’s growth and utilization in Nigeria.

A systematic investigation for mode-I fracture properties of stitched composites

Three-dimensional stitched composite (3DSC) is one kind of 3D textile structural composite with higher performance on the interlaminated properties. This work demonstrates a systematic analysis of the Mode I fracture behavior of the 3DSC by designing the stitch pitch and fineness of the stitch yarn in the experiments. In the finite element model, a mixed model combining the homogeneous and microstructural parts was developed to reveal the mechanism of stitch pitch and fineness of the stitch yarn on the mode I fracture behavior of the 3DSC. The results show that the effect of the stitch pitch on the mode I fracture behavior of the 3DSC is related to the crack propagation length of the first stitch yarn, which is also dependent on the tension properties of the stitch yarn. The thickness of stitch yarn can significantly improve the fracture toughness of the 3DSC. However, the relative improvement efficiency of the stitch yarn gradually decreases with the rise of the yarn fineness. According to this phenomenon, this work proposed an optimized design to improve the mode I fracture properties of the 3DSC.

Enhancing the dependence of blended jute yarn rather than hundred percent cotton yarn

Blending is a mixing process where two or more different fibers are combined into the desired percentage. In a yarn spinning system, different compositions, lengths, diameters, or colors may be mixed to create a blended yarn. In this system, various lots of fibers are combined into a homogeneous mass before being spun into a staple fiber yarn. Usually, jute and cotton fiber are blended together to make jute-cotton blended yarn. The diversified use of jute is one way to blend yarn. A 30%: 40%: 30% ratio was used for making the jute-cotton-viscose blended yarn. A rotor frame in a cotton spinning line produced the jute-cotton-viscose blended yarn and 100% cotton yarn. The physical properties like count, yarn Lea strength, and CSP were measured for both jute-cotton-viscose blended yarn and 100% cotton yarn. Among them, the average count of jute-cotton-viscose blended yarn and 100% cotton yarn are found approximately the same, i.e., 6.0 and 5.89, respectively. However, the yarn lea strength and CSP of both samples are 318.6 lb, 208 lb, and 1876, 1246, respectively, for 100% cotton yarn and jute-cotton-viscose blended yarn, which are far different from each other. There is the consistency of CV%, SD, and PMD of the blended yarn as well as 100 % yarn. In this study, viscose was first introduced for the blending process with jute and cotton to produce a jute-cotton-viscose blended yarn, and the physical properties were compared with both yarns.

An efficient virtual modeling regard to the axial tensile and transverse compressive behaviors of the twisted yarns

The mechanical properties of yarns have a decisive effect on the performance of fiber-reinforced composite materials. Predictive simulations of the mechanical response of yarns are, thus, necessary for damage evaluation and geometric reconstruction of textiles. This paper proposed a quasi-fiber scale virtual modeling method regard to the axial tensile and transverse compressive behaviors of the twisted yarns. A stochastic properties model of the yarn was established for characterizing the statistical distribution of tensile strength. The variation of modeling parameters, including coefficient of friction, the amounts of virtual fibers per yarn and element length, versus calculation accuracy has been determined based on axial tensile and transverse compressive behavior of quartz fibers. The relationship between modeling parameters and mechanical behavior of yarn was established within the scope of this study. Axial tensile and transverse compressive behavior of yarns with different twists were predicted. The results show that balance between the modeling precision and computational efficiency can be achieved using the parameters, the COF of 0.35, virtual fiber count of 122 and Le of 0.3. This efficient modeling method is meaningful to be developed in further virtual weaving research.

Topology based modelling of crochet structures

Crocheted textiles receive scarce scientific study and are at present not produced in automatized industrial scale. Computer-aided modelling and simulation offer capabilities for investigating possible technical fields of application. In this context a novel approach for modelling crocheted textiles consisting of chains, slip stitches and single crochets using a topology based and parameterized key point representation at the meso scale is proposed. According to the stitch size, yarn diameter and pattern spline interpolated models, which are free of interpenetrations up to approximately a 1/10 ratio of yarn diameter to stitch size, are generated by a developed Python program and software from the company TexMind. The models are suitable for finite element method (FEM) applications with LS-DYNA with which the mechanical properties of crocheted textiles can be studied. Exemplary simulations show anisotropic properties and homogeneous distribution of stresses in a crocheted textile. Due to the computationally simple and flexible modelling the presented approach may serve as a tool for designing planar crocheted textiles. This allows for estimation of the required yarn length and offers the prediction capabilities of simple and fast FEM simulations based on beam elements.

Numerical investigation on central tearing behaviors and propagation mechanisms of coated warp-knitted fabrics

To reveal the central tearing behaviors and propagation mechanisms of the architectural non-crimp fabric (NCF) composites with an initial crack, a microscopic finite element (FE) model was proposed and developed to simulate the tearing propagation process of materials in this paper. Firstly, the experimental program including the central crack tearing test of NCF composites and uniaxial tensile test of yarns was performed for gaining the material parameters. Secondly, a finite element (FE) model was developed and validated from the good agreement between numerical and experimental results. Furthermore, tearing damage mechanisms and failure performances of the NCF composites with an initial central crack were simulated and analyzed. Finally, the effects of initial crack length, yarn orientation, and arch curvature of weft yarn on mechanical properties were investigated in depth. The analysis and comparison results indicate that the NCF composite shows the unneglectable orthotropic characteristics, in which the initial crack length, yarn orientation, and arch curvature of weft yarn have the significant effects on the mechanical properties. This paper thus provides an adequately feasible and accurate FE model for the numerical simulation on the central tearing propagation behaviors of the NCF composites with an initial crack.

Development of a method and technology for the production of 3D knitted reinforcement grids

Abstract The use of fibre-reinforced plastic composites (FRP) for lightweight construction solutions is becoming increasingly important. The processing of 2D scrims into complete 3D FRP components has been carried out with the help of complex manual assembly steps. The disadvantages of this procedure are distortions in the textile and, thus, deviations in the fibre alignments from the calculated load path. This paper presents a newly developed basic technology for the production of 3D reinforcing grids with variable warp and weft yarn section lengths based on multiaxial warp knitting technology. For this purpose, a new type of machine module and associated control technology for the production of weft yarn reserves on a multiaxial warp knitting machine was developed. In combination with technology from previous research work on the production of warp yarn lengths suitable for component contours, a basis was created for the production of 3D reinforcing grids.

Yarn quality analysis in non-cellulosic and metal contents of cotton fibre of various locations

The fibre physical properties can be influenced by non-cellulosic and metal contents present in it which ultimately may impact the quality and spinning performance of resultant yarn. The concentration of these materials largely depends upon cotton variety, growing area and atmospheric conditions. In this back drop the present research study was planned to investigate the impact of various varieties and locations on non-cellulosic and metal contents of raw cotton and their eventual effects on subsequent yarn quality. So four varieties of single-season upland cottons from four different cotton-growing locations in Pakistan were selected for the study. The collected cotton samples were subjected to chemical and physical testing to know the concentrations of non-cellulosic and metal contents present in them along with other physical parameters. Then they were subjected to yarn manufacturing by conventional ring spinning method. At the end the yarn quality testing was carried in respect of its tensile and imperfections characteristics. The results disclosed significant impacts of selected variables on yarn quality. The reduction in non-cellulosic contents and metal contents put negative impact on Count Lea Strength Product (CLSP), yarn lea strength, single yarn strength, breaking length, evenness, thin spots, and neps count of resultant yarn.

Analysis of the package diameter in winding processes by image analysis and a linear regression model

Currently, industrial winding processes are often optimized by trial and error. A digital twin of winding processes could be helpful in order to assist industry to optimize the winding processes. Formulating the kinematic equations that form the basis of such a simulation of the winding process is straightforward in principle. However, a major challenge is to model the increase of the package diameter as a function of time or length of wound up yarn, respectively. In this paper, a kinematic model for the winding process is first outlined. The focus of the paper is the description of a workflow in order to find a model for the package diameter increase dependent on the wound yarn length. For that purpose, a new image analysis method is presented to derive the general class of the model function for the diameter increase. Then, the measurement results of a series of experiments are analyzed to find a parameterization of the model function. Here, the input process parameters winding tension, cradle pressure, winding speed, and traverse ratio are varied at two levels. Finally, the linear regression model for the package diameter increase is presented.

Effect of Industrial Washing and Laundering on the Colour Values of Knitted Denim

One of the most distinctive features of denim is that the warp yarn is dyed with indigo dye and the weft yarns are not dyed, i.e. white. Although warp yarns dyed with indigo dye are woven with different woven fabric weaves, classical denim fabrics weave are produced with 3/1 Z twill weave. The search for new products in denim has led businesses to produce denim-looking knitted fabrics. Denim-looking knitted garments are subjected to industrial washing at the production phase and repetitive household washing processes in daily life. Repeated washing and drying processes cause changes that can affect user satisfaction in terms of losing the colour of the fabric. Therefore, in this study, the colour values of knitted denim fabrics produced as an alternative to denim fabrics manufactured by traditional methods after various industrial (rinse, enzyme and stone washing) and home washes (5, 10, 20 times) were examined. For this, the CIELab colour system was taken as the basis for colour analysis on a spectrophotometer device. As a result of the washing processes performed on each fabric sample (household washing and rinse, enzyme, stone washing applications), it was observed that there were differences in colour values depending on the fibre type, loop yarn length, fabric construction and washing process.