Fabric Structure Research Articles

Directionally Oriented Reinforcements of Warp-Knitted Fabrics for Composite Preforms

This paper focuses on the development of a methodology for the directional structural modification of warp-knitted fabrics by sewing on carbon fiber tapes. Four-, five-, and six-axial geometric systems were designed to optimize the qualitative distribution of stresses on the surface of the tested product. Through a numerical experiment in the ANSYS environment, the impact of the change in the axiality of a textile structure on the mechanical properties of the modeled geometric configuration was assessed. This analysis was experimentally verified by measuring the multiaxial force distribution on the knitted surface, which demonstrated that Variant 7, with six axes 30° apart, was the most favorable.

Influence of projectile shape on ballistic behavior of 3D shallow straight-joint woven fabrics

This study investigates the influence of projectile shape on the ballistic behavior of 3D shallow straight-joint woven fabrics (3DSSWFs). Utilizing a series of numerical simulations, we analyze the impact resistance and energy absorption capabilities of 3DSSWFs when subjected to projectiles of varying geometries. The projectile setup includes spherical, conical, flat, and hemispherical projectiles to comprehensively assess their effects on fabric deformation, damage mechanisms, and overall ballistic performance. Results indicate that projectile shape significantly affects the penetration resistance and failure modes of 3DSSWFs. Spherical projectiles tend to cause extensive delamination and localized fabric failure, whereas conical and flat projectiles exhibit different interaction dynamics, influencing the energy dissipation patterns within the fabric matrix. The findings of this study provide critical insights into the complex relationships between projectile geometry and fabric response in 3DSSWFs. By elucidating the role of projectile shape in determining the ballistic limit, energy absorption capacity, and failure mechanisms, this research contributes to the broader understanding of impact dynamics in advanced textile structures.

Mechanical Properties of Spunlace Non-Wovens with a Porous Structure

The paper describes the influence of the drum system construction of two modern carding machines on the porous structure of spunlace non-wovens composed of polyester and viscose. The non-woven fabric structure, including the number and size of the pores, determines the tensile strength of the composites obtained. The spunlace non-wovens were subjected to tensile strength tests in the machine, and cross-directions and microscopic observations of their structure were made. The results of the experiments were used to determine the relationship between the strength of the material and the porosity of its structure. This knowledge was used to prepare recommendations for the manufacturer of wet wipes in order to enable the selection of a carding machine for the mass production of final products with strength properties that meet market requirements and satisfy the end customer.

Smart Green Cotton Textiles with Hierarchically Responsive Conductive Network for Personal Healthcare and Thermal Management.

Whereas cotton as an abundant natural cellulose has been widely used for sustainable and skin-friendly textiles and clothes, developing cotton fabrics with smart functions that could respond to various stimuli is still eagerly desired while remaining a great challenge. Herein, smart multiresponsive cotton fabric with hierarchically copper nanowire interwoven MXene conductive networks that are seamlessly assembled along a 3D woven fabric template for efficient personal healthcare and thermal comfort regulation is successfully developed. The robust hierarchically interwoven conductive network was "glued" and protected by organic conductive polymer poly(3,4-ethylenedioxythiophene) along a 3D interconnected fabric template to enhance interfacial adherent and environmental stability. Benefiting from the robust multiresponsive hierarchically interwoven conductive network, smart cotton fabric exhibits real-time response to various external stimuli (light/electrical/heat/temperature/stress), and the details of human activities can be accurately recognized and monitored. Furthermore, the porous structure of 3D smart fabric induced strong capillary force and confinement to phase change materials PEG, which exhibits a wide range of phase transition temperatures for efficient thermal comfort regulation. After further encapsulation with transparent fluorosilicone resin, the smart cotton fabric exhibits excellent self-cleaning performance with water/oil repellent. The smart multiresponsive cotton fabrics hold great promise in next-generation wearable systems for efficient personal healthcare and thermal management.

Analysis of Liquid Transport Performance of Cotton Knitted Fabric Made by the TransDry Technology

ABSTRACT In order to improve a competitiveness of cotton in textile market, an innovative TransDry® technology has been developed. The aim of the work was to investigate the liquid moisture transport in cotton knitted fabrics: standard and made using TransDry® technology. The measurement has been performed using Moisture Management Tester. Additionally, fabrics have been measured in the range of water-vapor permeability and thermal insulation using Permetest and Alambeta. Results showed that both calculated parameters: R – accumulative one-way transport index and OMMC – overall moisture management capacity do not reflect the advantages of the TransDry® technology. The advantages of TransDry® technology have been demonstrated in values of the following parameters: WTT – wetting time for top surface, MWRB – maximum wetted radius for the bottom surface, SST and SSB – spreading speed on both sides of fabric. Results showed that only an in-depth analysis of results of individual parameters and graphs from the MMT software allowed for a detailed examination of movement of liquid moisture in tested fabrics and demonstration of the advantages of TransDry® technology. It has been also concluded that the changes of the structure of knitted fabrics cause the changes of moisture transport properties of the fabrics.

Vibroacoustic characterization of small woven fabrics

This study is aimed to analyze the vibroacoustic behaviour of woven fabrics utilized in small acoustic devices for ingress protection. We first concentrate on predicting and describing the vibration behaviour of the woven fabric structure through flip around, since lumped modelling comes first. A vibration experiment is also conducted to measure the motion of the woven fabric structure under external excitation to validate the modelling. The numerical model is then employed to simulate the vibroacoustic behaviour of the woven fabric via transmission loss calculation; the simulation is then compared with transmission loss measurement based on the four-microphone method. This research demonstrates that despite some limitations, both the numerical and lumped models show a good degree of accuracy in predicting the vibration of the woven structure; the numerical model also performs well in vibroacoustic modelling.

A viscoelastic-plastic model for the core of various close-packings of multifilament polyamide-6 yarns

Different forms of close-packed yarns can be produced by varying the number of monofilaments in the core region, ranging from one to five. Numerous efforts have been made to model or simulate the mechanical response of close-packed yarns; however, previous studies have predominantly focused on one or two monofilaments in the core. In this study, we propose an analytical approach that combines a geometrical model with an artificial neural network (ANN) to predict the tensile behavior of close-packed yarns containing 2 to 5 monofilaments in the core region. The novelty of this hybrid model lies not only in accounting for more than two monofilaments in the core but also in extending the prediction range from elastic to viscoelastic-plastic behavior. Validation of the proposed method showed excellent agreement between experimental and theoretical results. Numerical simulations further confirmed that the results align with theoretical predictions, demonstrating the model’s accuracy in predicting the tensile behavior of close-packed yarns. This modeling approach has the potential to significantly improve the understanding and modeling of textile structures.

Overview of textile tensile surface structures with the largest uniform area

The innovative design of tensile surface structures is often a distinguishing feature of the entire construction project. The use of membranes gives buildings a sense of lightness and often a futuristic look. The construction materials used in the design of membrane roofing are, in addition to the steel cables tensioning and supporting the roof membrane, technical fabrics. This article focuses on describing structures made of continuous tensioned membranes spanning a rope or bar network with a total uniform area of more than 20,000 m2. Five structures with the largest uniform load-bearing area are described. The most commonly used yarn materials and coatings are described. The basic strength parameters of the most commonly used fabrics are summarized. The principles of shaping membrane surfaces were described. Attention was drawn to the difficulty of transferring laboratory test results to real objects. It is very likely that, for reasons of usability and manufacturing technology, continuous membrane surfaces with larger areas than described will no longer be designed.

Excellent thermal, moisture-permeable weft-knitted fabric with core-sheath yarn structure for foot protection in cold environments

In extremely cold environments, maintaining body temperature and reducing heat dissipation is essential for maintaining human health and life safety, but the field of thermal insulation shoe upper fabric has not been deeply studied. In this paper, based on the dual-scale structure of the yarn and shoe upper fabric, a composite yarn with a core-sheath structure is designed, and a using plating stitch pattern weft-knitted whole garment thermal insulation shoe upper fabric with double-layer structure is proposed. By testing the mechanical properties and thermal and moisture performance of the shoe upper fabric and the thermal insulation performance of the whole shoe, the thermal insulation mechanism of the weft-knitted whole garment shoe upper fabric with a double-layer structure and dual-scale structure design was systematically studied. The results show that the shoes made of polyimide/hollow polyester composite yarn with core-sheath structure yarn have good thermal insulation performance. The use of core-sheath yarns can improve the thermal insulation performance of the shoe, and, with the increase of the ratio of core-sheath yarn, the thermal insulation performance of the shoe is better. Starting from the dual-scale shoe fabric structure, this article proposes a novel method for the industrial production of thermal insulation shoe upper fabrics, which is expected to provide guidance for the further development of thermal insulation shoe upper fabric in the future.

One-step fabrication of a novel fiber-based absorber for flexible, tunable and boosted microwave absorption

The increasingly intricate electromagnetic environment necessitates higher anti-electromagnetic interference capabilities for electronic devices, thereby demanding a flexible absorbing material that can adapt to multiple forms, is lightweight, and exhibits excellent electromagnetic wave (EMW) absorption properties. In this study, we have developed a novel flexible absorbing material (FAM) based on glass-coated amorphous magnetic fibers (SFs) and Dallenbach-like absorbing structures through wet forming technology. By combining high-performance absorbing fiber with textile structures, the FAM demonstrates EMW absorption performance along with lightweight flexibility and shape adaptability. This paper explores the influence of process parameters in wet forming technology on FAM formation; as well as examines the construction of broadband absorbers through structural optimization. A single-layer FAM with a thickness of 1.7 mm (SFs length 8 mm, content 3 g/m2) achieves an impressive reflection loss (RL) value of −60.1 dB at 11.6 GHz. Furthermore, optimized multi-layer FAM attains effective absorption bandwidth (EAB: RL ≤ −5 dB) across a wide range from 3–14 GHz. This work presents a new approach for developing ’lightweight, thin, wide, and strong’ absorbing materials based on fiber and textile structures which holds significant implications for civilian electromagnetic interference protection as well as military electromagnetic stealth technology.

Automated model discovery for textile structures: The unique mechanical signature of warp knitted fabrics

Textile fabrics have unique mechanical properties, which make them ideal candidates for many engineering and medical applications: They are initially flexible, nonlinearly stiffening, and ultra-anisotropic. Various studies have characterized the response of textile structures to mechanical loading; yet, our understanding of their exceptional properties and functions remains incomplete. Here we integrate biaxial testing and constitutive neural networks to automatically discover the best model and parameters to characterize warp knitted polypropylene fabrics. We use experiments from different mounting orientations, and discover interpretable anisotropic models that perform well during both training and testing. Our study shows that constitutive models for warp knitted fabrics are highly sensitive to an accurate representation of the textile microstructure, and that models with three microstructural directions outperform classical orthotropic models with only two in-plane directions. Strikingly, out of 214=16,384 possible combinations of terms, we consistently discover models with two exponential linear fourth invariant terms that inherently capture the initial flexibility of the virgin mesh and the pronounced nonlinear stiffening as the loops of the mesh tighten. We anticipate that the tools we have developed and prototyped here will generalize naturally to other textile fabrics–woven or knitted, weft knit or warp knit, polymeric or metallic–and, ultimately, will enable the robust discovery of anisotropic constitutive models for a wide variety of textile structures. Beyond discovering constitutive models, we envision to exploit automated model discovery for the generative material design of wearable devices, stretchable electronics, and smart fabrics, as programmable textile metamaterials with tunable properties and functions. Our source code, data, and examples are available at https://github.com/LivingMatterLab/CANN. Statement of significanceTextile structures are rapidly gaining popularity in many biomedical applications including tissue engineering, wound healing, and surgical repair. A precise understanding of their unique mechanical properties is critical to tailor them to their specific functions. Here we integrate mechanical testing and machine learning to automatically discover the best models for knitted polypropylene fabrics. We show that warp knitted fabrics possess a complex symmetry with three distinct microstructural directions. Along these, the behavior is dominated by an exponential linear term that characterize the initial flexibility of the virgin mesh and the nonlinear stiffening as the loops of the fabric tighten. We expect that our technology will generalize naturally to other fabrics and enable the robust discovery of complex anisotropic models for a wide variety of textile structures.

Examining the effect of the shear coefficient on the prediction of progressive failure of fiber-reinforced composites

The ultimate damage of composites under tension usually results from fiber damage, which includes both tensile and shear contributions. In this study, the shear coefficient α of the fiber yarn is incorporated into the failure criterion to consider the shear effect of the fiber yarn. An analytical model is then proposed that combines a homogenization method and the enhanced failure criterion to facilitate quick evaluation of the progressive damage and failure of the composite. The sensitivity of α on the behaviors of progressive damage and failure are comprehensively explored for different types of fiber-reinforced composites, including a laminate, a plain weave composite, a two-dimensional triaxially braided composite, and a three-dimensional woven composite. The results indicate that damage and failure behaviors are generally sensitive to the shear coefficient, and composites with more complex textile structure demonstrates greater sensitivity to the α. An analysis of the sensitivity of α for different failure criteria was also conducted, and the results reveal that the Hashin–Hou criterion shows more sensitivity to α than the Chang–Chang criterion, the Hoffman criterion, or the Tsai–Wu criterion. Therefore, the identification of the shear coefficient is significant for exploring the damage and failure behaviors of fiber-reinforced composites.

Large-torque and fast-response electrothermal-motivated liquid crystal elastomer twisted yarn actuators

Analogous to biological muscles, twisted yarns with the capacity to output torsional torque and reversible rotation are of significant value in the development of soft robotic systems. However, how to achieve large torque while efficiently integrating electrical control elements to the soft actuators remains scientific and engineering challenges. Here, by concentric twisting a flexible silver-plated polyamide strand (SPS) with multi-layer liquid crystal elastomer fibers (LCEFs), a twisted yarn actuator with the skin-core structure that exhibits outstanding rotational motion under the electrical current control is fabricated. It has been proved that this multi-layered twisting structure efficiently improves the actuating performance. The yarn actuator can produce a peak torque of 33.4 N m kg−1 which outperforms reported commercial rotating motors and a specific power density of 21.2 W kg−1 that is comparable to the human skeletal muscle. As conceptual applications, electrical soft rotors and a novel flexible lifter have been successfully constructed based on the twisted yarn actuator, demonstrating precise torque responsiveness and controllability. Furthermore, a smart crawling fabric embedded with the twisted yarn actuators has been weaving fabricated which can crawl forward continuously and achieve the crawling stroke of 19.9 mm in 55 s and a maximum speed of 1.1 mm s−1. The research provides insights for designing soft robots employing fabric structures.

Potential Penetration of Engineered Nanoparticles under Practical Use of Protective Clothing Fabrics.

The commercial application of engineered nanoparticles (ENPs) has rapidly increased as their unique properties are useful to improve many products. ENPs, however, can pose a major health risk to workers through exposure routes such as inhalation and dermal contact. Research is lacking on the protective nature of lab coats when challenged with ENPs. This study investigated multiwalled carbon nanotubes (CNTs), carbon black (CB), and nano aluminum oxide (Al2O3) penetration through four types of lab coat fabrics (cotton, polypropylene, polyester cotton, and Tyvek). Penetration efficiency was determined with direct reading instruments. The front and back of contaminated fabric swatches were further assessed with microscopy analysis to determine fabric structure with contaminated and penetrated particle morphology and level of fabric contamination. Fabric thickness, porosity, structure, surface chemistry, and ENP characteristics such as shape, morphology, and hydrophobicity were assessed to determine the mechanisms behind particle capture on the four common fabrics. CNTs penetrated all fabrics significantly less than the other ENPs. CNT average penetration across all fabrics was 1.83% compared to 15.74 and 11.65% for CB and Al2O3, respectively. This can be attributed to their fiber shape and larger agglomerates than those of other ENPs. Tyvek fabric was found to be the most protective against CB and Al2O3 penetration, with an average penetration of 0.06 and 0.11%, respectively, while polypropylene was the least protective with an average penetration of 40.36 and 15.77%, respectively. Tyvek was the most nonporous fabric with a porosity of 0.50, as well as the most hydrophobic fabric, explaining the low penetration across all three ENPs. Polypropylene is the most porous fabric with a porosity of 0.77, making it the least protective against ENPs. We conclude that porosity, fabric structure, and thickness are more important fabric characteristics to consider when discussing particle penetration through protective clothing fabrics than surface chemistry.

A Highly Robust, Multifunctional, and Breathable Bicomponent Fibers Thermoelectric Fabric for Dual-Mode Sensing.

Wearable thermoelectric (TE) materials are seen as excellent candidates for flexible electronics because of their unique self-powered properties, multistimulus sensing and human waste heat conversion. However, currently reported flexible TE materials still face challenges such as poor durability, uncomfortable wearing and sensing signals crosstalking each other. Herein, this study describes a hot-air cross-linking method for the preparation of multifunctional TE fabrics with enhanced durability. Poly(ethylene terephthalate) (PET) fibers with core and sheath structures having different melting points were selected as flexible substrates. Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) and single-walled carbon nanotubes (SWCNTs) were embedded stably on the surface of the sheath layer in the presence of heat treatment. The fiber-welded structure created by thermal cross-linking improves the durability of TE fabrics, including consistent mechanical and electrical properties after a 6 h wash test and 6000 compression cycles. The unique fiber structure of TE fabrics ensures excellent breathability (313.7 mm s-1 at 200 Pa), which meets the breathability requirements for human wear. In addition, the fiber-prepared sensors have excellent compressive strain response (20 ms response time and 30 ms recovery time) and precise temperature discrimination (0.17 K minimum discrimination temperature) for accurate real-time monitoring of the sensed signals. Thus, the TE fabrics can be used for human motion recognition, including pulse monitoring, sign language expression, and motions in joint areas. Moreover, the fabricated wearable TE device is connected to a Bluetooth module for wireless transmission, which can be used for mechanical and temperature sensing of the robot arm without signals crosstalking. This new durable TE fabric paves the way for the next generation of smart wearable technology.

Quantification of shedding propensity of polyester fabrics in the washing process

Global microplastic (MP) pollution from primary and secondary sources is partly caused by the growing trend towards the use of plastics. One of the most important factors for the persistence of MP in the environment is their high resistance to degradation. The washing process has been identified as a risk and source of various pollutants in wastewater and numerous studies have been published. This study focuses on three different polyester fabrics: woven, knitted and double-faced plush fabrics, which were washed under standard conditions with the reference detergent ECE A at 60 °C for 40 min. Different methods were used to quantify the released fragments in a 5- and 10-cycle wash, to analyse the samples gravimetrically and to characterise the wastewaters by physicochemical parameters and filter cake. The results proved that the structure of polyester fabrics plays a role in shedding, although most fragments were released from all polyester fabrics in the first washing cycles.

Viscoelastic behavior of warp-knitted spacer fabrics in iterative compression and decompression

In this study the viscoelastic behavior of warp-knitted spacer fabrics was investigated for compressional deformation. The fabric specimens were tested via loading and unloading time intervals under predetermined conditions. Following the upside tests, specimens were relaxed for 24 h to examine the recovery prior to completing the downside tests. The data obtained from the compression and decompression cycles were examined for stress relaxation and creep through stress–time plots. From the results it was observed that, despite the non-homogeneous structure of the spacer fabric, the specimens demonstrated exponentially changing behavior within the given time intervals. Since the response of fabrics to compression and decompression cycles can be expressed as a function of time, a mathematical approach was expressed in accordance with the time-dependent behavior of the fabrics regarding the monofilaments as bent beams. The responses of the fabrics to the experimental set up conditions were evaluated to determine the potential usage performances of the fabrics. Fabric thickness, number of monofilament yarns in the structure, and thickness of the monofilaments had the major effects on the performance of the fabrics. Future research could consider modeling studies to predict usage performance, and tailoring the fabrics before production.

Design optimization of a three-dimensional hexagonal braiding technique

The three-dimensional hexagonal braiding technique, utilizing an individually controllable horn gear mechanism, enables the automatic generation of a wide range of intricate fabric preforms for structural composites. However, the limited yarn-carrying capacity and the potential risk of collisions between horn gears hinder the development of this type of braiding machine. This study proposes an optimized hexagonal braiding technique to enhance the machinery and control system, aiming to improve the yarn-carrying capacity and prevent collisions. Specifically, the optimization includes modifying the switch device, developing a new algorithm for controlling each horn gear, and designing a control panel to facilitate human–computer interaction. Additionally, simulations of various fabric structures demonstrate improved braiding capability compared to traditional hexagonal braiders. Moreover, a prototype braider is assembled, capable of automatically braiding diverse fabrics using the control system, thereby demonstrating its potential to manufacture complex composite preforms.

A simulation model of thermal uniformity ratio applied in conductive thermal woven fabrics

Wearable technology based on conductive textiles generally focuses on the development of textile sensors and electric thermal textiles. The primary preparation methods currently used are coating and interweaving. Compared with the coating method, interweaving provides better deformability, durability, and a larger target functional range. Among them, woven conductive fabrics offer good stability, and by designing various jacquard patterns, multi-layer material structures can also be formed. Using woven conductive thermal textiles as a base, this paper established a thermal uniformity ratio simulation model through the design of fabric structure parameters and the analysis of thermal performance. This methodology provides possible design direction for such textiles, thereby enabling a reduction in production expenditure. Furthermore, it offers avenues for the realization of personalized adaptation and the transition towards the industrial-scale manufacturing of woven thermal textiles.

Effect of geometric configurations and curvature angle of corrugated sandwich structures on impact behavior

AbstractThe aim of this study is to numerically investigate the low‐velocity impact behavior of carbon fiber reinforced orthogonal woven fabric composite sandwich structures with five different geometric configurations and four different curve angles. Low velocity impact simulations were performed in LS DYNA finite element program to investigate the effects of core configuration and curve angle on peak contact force, energy absorption efficiency and damage mode. A progressive damage analysis based on the combination of the Hashin damage criterion and the Cohesive Zone Model (CZM) with bilinear traction‐separation law was performed using the MAT‐54 (ENHANCED_COMPOSITE_DAMAGE) material model. Among the five different cores, Trapezoidal core has the highest peak force average of 2.9 kN while Triangular core sandwich structure has the lowest with 1.23 kN. Absorbed energy efficiency average was highest for rectangular core with 0.95 and lowest for sinusoidal core with 0.69. The specific absorbed energy value was highest for Triangular core with 0.312 J/g and lowest for Sinusoidal core with 0.178 J/g. The damage area on the structure increased with increasing curve angle. It was determined that the core structure and curve angle is an effective parameter on peak force and energy absorption efficiency.Highlights Impact behavior of sandwich composite structures was examined. The effects of core type and curve angles on peak force, energy absorption efficiency and specific absorption energy were investigated. Specific absorption energy rates were compared with studies in the literature.