Plain Woven Fabrics Research Articles

Green hybrid composites partially reinforced with flax woven fabric and coconut shell waste-based micro-fillers

This research is focused on hybrid green composites using flax woven fabric in which the matrix phase was further reinforced with coconut shell waste-based cellulosic microparticles as fillers. Mesoscale mechanical models were successfully developed to simulate the tensile properties of such hybrid composites based on hybridization of fibers and biobased materials using epoxy resin. S-glass fabrics with plain, twill and biaxial constructions, were used as the outer layers, while plain-woven flax fabric was used as the middle layer. A high level of agreement was observed between the experimental and predicted values. The static tensile tests were followed by cyclic tensile tests, microscopic analysis of fracture surfaces and dynamic mechanical analysis. The influence of the hybrid fabric geometry and combination with biowaste-based micro cellulosic material was observed to significantly influence the tensile properties determined by both experimental and numerical analysis. Dynamic mechanical analysis also validated the quasistatic measurements. A higher storage modulus and loss modulus were registered for the hybrid composites impregnated with a 1 % bio filler-based matrix. The damping factor (tan delta) was lower for the hybrid composites than for the nonhybrid samples and the control samples from the pure matrix. This difference is attributed to the stronger interface between the fibers and the particle-based matrix, which restricts the molecular mobility and increases the stiffness of the composites. Fractographic images were obtained by scanning electron microscopy (SEM) to study the failure modes and mechanisms of the composite samples. The microparticles were uniformly dispersed in the epoxy resin and thus enabled microcracking rather than macrocracks. The failure mainly occurred due to fiber failure, matrix cracking and delamination. Such hybrid composites are useful for exterior and interior components in automotive applications.

A Novel-Potential Wave-Bump Yarn of Plain Weave Fabric for Fog Harvesting.

With the variety of fibers and fabrics, the studies of the surface structure of the textile yarns, the weave fabric, and their surface wettability are still potential factors to improve and optimize the fog harvesting efficiency. In this work, inspired by the fog harvesting behavior of the desert beetle dorsal surface, a wavy-bumpy structure of post-weave yarn (obtained from woven fabric) was reported to improve large droplet growth (converge) efficiency. In which, this study used tetrabutyl titanate (Ti(OC4H9)4) to waterproof, increase hydrophobicity, and stabilize the surface of yarns and fabric (inspired by the feather structure and lotus leaf surface). Moreover, PDMS oil was used (lubricated) to increase hydrophobicity and droplet shedding on the yarns (inspired by the slippery surface of the pitcher plant) and at the same time, enhance the fog harvesting efficiency of the warp yarn woven fabric (Warp@fabric). In addition, a three-dimensional adjacent yarn structure was arranged by two non-parallel fabric layers. The yarns of the inner and outer layers were intersected at an angle decreasing to zero (mimicking the water transport behavior of Shorebird's beaks). This method helped large droplets quickly form and shed down easily. More than expected, the changes in fabric texture and fiber surface yielded an excellent result. The OBLWB-Warp@fabric's water harvesting rate was about 700% higher than that of the original plain weave fabric (Original@fabric). OBLWB-Warp@fabric's water harvesting rate was about 160% higher than that of Original-Warp@fabric. This shows the great practical application potential of woven fabrics with a low cost and large scale, or you can make use of textile wastes to collect fog, suitable for the current circular economy model. This study hopes to further enrich the materials used for fog harvesting.

Analyzing the Effect of Yarn Tension, Weft Yarn Type, and Weft Yarn Density on Thermal Resistance, Thermal Conductivity, and Air Permeability of Plain Woven Fabric

ABSTRACT Uncomfortable feelings during wear highly affect human health, work efficiency, and mental satisfaction. This study evaluated the thermal comfort of woven fabrics made from 16Ne ring and rotor spun weft yarns(x1). The other variables involved are warp tensions (x2) of 1 kilo newton (KN) and 2 kN, weft tensions (x3) of PFT/B- and PFT/B+T, and weft densities (x4) of 14 picks per centimeter (PPC) and 18 PPC. Comfort properties such as thermal conductivity, thermal insulation, and air permeability were measured and analyzed. The fabric produced from rotor-spun weft yarn showed better thermal comfort properties than the fabric made from ring-spun weft yarn. The results of the analysis revealed that when warp and weft yarn tension increased and weft density decreased, thermal conductivity and air permeability also increased. However, thermal insulation of the fabric decreased as yarn tension increased. On the other hand, as the weft density increased, the thermal insulation of the fabric increased. Air permeability increased as weft tension increased from PFT/B- to PFT/B+T and it decreased as weft density increased from 14 PPC to 18PPC. The maximum thermal conductivity and minimum thermal resistance were attained at 14 PPC weft density and ring-spun weft yarn.

Mechanism of pre-tension on the impact response of plain weave fabric: Experimental and numerical investigation

The fabrics made of high strength and toughness fibers are increasingly used in the structural and individual protection. The research on energy dissipation mechanism and the improvement methods for improving energy dissipation of the fabric under impact, as well as the change of ballistic limit velocity under pre-stress, is relatively mature. However, the transmission mode and velocity of transverse wave in the fabric, as well as the method of accurate finite element simulation is still lacking. In this paper, the transverse impact response of ultra high molecular weight polyethylene (UHMWPE) fabric subjected to fragment impact is studied experimentally and numerically. A novel biaxial pre-tension fixture was developed, and fragment impact test of the fabric in pre-tension state was realized using a gas gun. The displacement-time history of each point on the fabric in three-dimensional space was characterized through 3-D DIC technology, and the process of transverse wave transmission on the fabric after fragment impact was obtained. The calculated results of the finite element model established by truss element agrees reasonably well with the experimental results. The experimental and numerical results indicate that the impact velocity of fragment affects the velocity of transverse wave in the fabric, but does not change its transmission mode. With the increase of pre-tension amount, the propagation mode changes from a cross shape to a rhombic shape and finally to a circular shape, and the wave velocity increases greatly. The wave transmission process in yarns at a mesoscopic level was analyzed through finite element simulation, and the transmission path was determined. It was found that pre-tension accelerated the wave velocity on the stepwise path, causing the transverse wave to reach a farther position in the diagonal direction of the fabric, resulting in different modes of wave transmission. The research content may provide more ways for the application of fabrics in protection.

Effect of stabilising overfeed of draw textured yarns on woven fabric properties

The purpose of this study is to determine the effect of draw texturing of polyester yarn on various structural, mechanical, and physical characteristics of plain woven fabric. Partially oriented (POY) polyester filament yarn is taken as starting material for the experiment, which has undergone draw texturing treatment with seven different levels of stabilizing overfeed (SOF) percentage (2%–14%), keeping other texturing parameters constant. Plain woven fabrics are prepared by using the control and six textured yarns as weft on a water jet loom while warp yarn and other weaving parameters are kept unchanged. Thickness, porosity, tensile strength, tearing strength, bending stiffness, water vapour & air permeability, and dye-uptake ability of the control and six textured fabrics are evaluated and analyzed to find out the effect SOF on the fabric properties. It has been observed that the bending length, water vapour & air permeability, tear strength, and pore size of the fabrics are gradually reduced as SOF increases. Meanwhile, thickness, tensile strength, and dye absorbency increase as SOF increases.

The impact of the coupling relationship between projectile size and yarn dimension on the ballistic performance of plain weave fabric

Aramid fibers, due to their relatively high inter-yarn friction, high strength, high modulus, and other characteristics, have become a typical representative of flexible anti-ballistic materials in modern warfare. Current research on the anti-penetration of aramid fabrics mostly focuses unilaterally on the structure and performance of aramid fabrics or the shape and size of projectiles, with fewer studies on the coupled effect of both on ballistic performance. This study analyzes how the coupling relationship (or size effect) between the projectile and fiber bundle dimensions affects the fabric ballistic performance from a mesoscopic scale perspective. Taking plain weave aramid fabric as the research object, considering different diameter projectiles, through a large number of ballistic impact tests and numerical simulations, parameters such as ballistic limit velocity, average energy absorption of fabric, and specific energy absorption ratio (average energy absorption of fabric divided by projectile cross-sectional area) are obtained for ballistic performance analysis. The influence law of projectile size on the ballistic performance of high-performance fabrics is as follows: The relative range of fitted ballistic limit velocity at different target positions gradually decreases and then stabilizes as the projectile diameter increases, indicating that the fabric structure effect gradually disappears at a projectile diameter of 12 mm; The average ballistic limit velocity at three impact positions, P1, P2, and P3, provides the corresponding ballistic limit velocity for 1000D aramid fabric, which increases with projectile diameter but the rate of increase slows down at an inflection point, which in this study occurs where the fabric structure effect nearly disappears at a projectile diameter of 12 mm; The energy absorption ratio increases and then decreases as the projectile diameter increases from 4 mm to 20 mm, reaching a peak at the diameter of 12 mm due to the gradual disappearance of the fabric structural effect. The projectile diameter of 12 mm corresponds to the coupling size of 11.159, which provides a size design reference for the macroscopic-based continuum models of aramid plain weave fabrics.

Ti3C2Tx MXene/reduced graphene oxide/cellulose nanocrystal-coated cotton fabric electrodes for supercapacitor applications

Textile-based electrodes are the most important components of wearable and portable supercapacitors. Ti3C2Tx MXene and reduced graphene oxide (rGO) have a great potential for the fabrication of high-performance textile supercapacitor electrodes. In this work, rGO was synthesized with the presence of cellulose nanocrystal (CNC) and Ti3C2Tx/rGO/CNC dispersions with different rGO/CNC contents were prepared. The plain-woven cotton fabrics were coated by homogenous Ti3C2Tx and Ti3C2Tx/rGO/CNC dispersions (5% wt., 15% wt., 30% wt. and 50% wt. rGO/CNC content) and characterized by X-ray Diffraction, Fourier Transform Infrared spectroscopy and Scanning Electron Microscopy techniques. The electrochemical characterization techniques showed that Ti3C2Tx/rGO/CNC loaded fabric electrodes up to 15 wt.% rGO/CNC content exhibited a high specific capacitance of 501.1 F g−1 at a current density of 0.3 A g−1 with low internal electrode resistance, and a good electrochemical stability. The results also showed that MXene/rGO/CNC based high-performance textile supercapacitor electrodes can be prepared by simple drop-casting method.Graphical

Scalable and Ultra-Sensitive Nanofibers Coaxial Yarn-Woven Triboelectric Nanogenerator Textile Sensors for Real-Time Gait Analysis.

Yarn-woven triboelectric nanogenerators (TENGs) have greatly advanced wearable sensor technology, but their limited sensitivity and stability hinder broad adoption. To address these limitations, Poly(VDF-TrFE) and P(olyadiohexylenediamine (PA66)-based nanofibers coaxial yarns (NCYs) combining coaxial conjugated electrospinning and online conductive adhesive coating are developed. The integration of these NCYs led to enhanced TENGs (NCY-TENGs), notable for their flexibility, stretchability, and improved sensitivity, which is ideal for capturing body motion signals. One significant application of this technology is the fabrication of smart insoles from NCY-TENG plain-woven fabrics. These insoles are highly sensitive and possess antibacterial, breathable, and washable properties, making them ideal for real-time gait monitoring in patients with diabetic foot conditions. The NCY-TENGs and their derivatives show immense potential for a variety of wearable electronic devices, representing a considerable advancement in the field of wearable sensors.

A novel multiscale prediction strategy for simulating the progressive damage behavior of plain-woven bamboo fabrics reinforced epoxy resin composites

This study proposed a novel multiscale prediction strategy, including mesoscale and macroscale damage evolution modeling, to investigate the effective properties and progressive damage failure behavior of plain-woven reinforced composites (PWRCs) under various external loads (tension, compression). A high-precision mesoscale representative volume element (RVE) that could accurately describe the local mechanical behavior of PWRCs was developed by combining experimental characterization (scanning electron microscope and X-ray computed tomography) and numerical simulation. To solve the problem of inaccurate prediction results caused by multiscale characteristics and complex stress changes in the damaged area of PWRCs, the strain-based 3D Hashin failure criterion and the multiscale damage models were used to predict the damage initiation and evolution of mesoscale reinforcement (bamboo fiber yarn bundle) and macroscale composites, respectively. Considering the damage evolution law of isotropic materials, a damage model based on the Von Mises criterion was used to characterize the damage initiation and evolution of mesoscale matrix epoxy resin (EP) under external loading. The effective properties and mechanical behavior of the PWRCs were transferred from mesoscale to macroscale through the progressive homogenization method. The bilinear constitutive relationship of the mixed-mode cohesive element was used to characterize the interlaminar failure of the PWRCs. Finally, the corresponding mechanical characterization (tension, compression) of the PWRCs was carried out. Moreover, the experimental results were highly consistent with the simulation results, verifying the reliability of the novel multiscale prediction strategy in investigating the mechanical response of the PWRCs at multiple scales and revealing the damage mechanism of the PWRCs.

Preparation and characterization of carbon fiber spread tow needled preform and its composite based on novel short yarn needling method

AbstractDue to the high fiber volume fraction of carbon fiber spread tow plain weave fabrics, it is difficult for short fibers to be brought into the thickness direction to form needled fiber bundles during the needling process. The interlaminar performance of the carbon fiber spread tow needled preform is weak, and the in‐plane damage is also severe. Responding to this issue, this article proposed a new method for preparing carbon fiber spread tow needled preform based on short yarn needling, which was expected to manufacture high‐performance carbon fiber spread tow needled preform and composite. We conducted experimental research on the preparation and structural characterization of the preform, as well as the Mode I interlaminar mechanical properties and in‐plane tensile properties of composites. The results showed that the fiber volume fraction of the preform significantly increased, reaching to 55.7%–56.1%, which was 25.5%–25.9% higher than that of traditional needled preform. The Mode I interlaminar property of carbon fiber spread tow needled composite reached to 905–4376 J m−2, which was improved by 29.3%–525.1% and 125.8%–1054.6% compared to traditional needled composite and laminated composite, respectively. At the same time, the tensile strength and tensile modulus were also improved by 191.5%–212.2% and 66.2%–78.1% compared to traditional needled composites. The preparation method of carbon fiber spread tow needled preform based on short yarn needling has laid the foundation for the 3D printing molding of dry fiber fabrics and is expected to be applied to high‐quality needling of high thickness and large curvature‐shaped fabric preforms.Highlights A novel method was proposed for preparing high‐performance carbon fiber spread tow needled preform based on short yarn needling. The fiber volume fraction of novel carbon fiber spread tow needled preform significantly increased, reaching to 55.7%–56.1%. The GIc of the novel carbon fiber spread tow needled composite was improved by 29.3%–525.1% compared to the traditional needled composite. The tensile strength and tensile modulus were also improved by 191.5%–212.2% and 66.2%–78.1%, compared to traditional needled composites.

Simulation method for filling stage in liquid composite molding based on a two-phase flow volume of fluid model

Liquid composite molding (LCM) is a process for manufacturing fiber-reinforced resin matrix composites. The chemical rheological properties of resin in the filling stage of LCM will produce a non-isothermal flow process that includes multi-field coupling of thermal field, flow field, and chemical field. During the filling stage, the resin is injected into a closed mold pre-laid with a fiber at a certain temperature and pressure to flow continuously and undergo a curing chemical reaction. The viscosity of resin changes constantly under the influence of temperature and the curing reaction, which affects the flow of resin. The simulation of this multi-field coupling filling stage in LCM can provide an effective reference for the design of process parameters. The simulation method of the filling stage in LCM is studied in this paper. The mathematical model of the filling stage is derived based on the air–resin two-phase flow volume of the fluid model. Based on the secondary development of the ANSYS FLUENT software, the mathematical model is solved to realize the simulation. The parameters of an alkali-free glass fiber plain weave fabric are measured and the calculation model of thermosetting resin viscosity is established by designed experiments, which are applied in simulation. The filling stage experiment of LCM is designed to verify the accuracy of simulation results. Meanwhile, by comparing with the traditional simulation method, it is found that the data error obtained by the simulation method in this paper is significantly reduced.

Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision

To address the issue of low accuracy in the yarn angle detection of glass fiber plain weave fabrics, which significantly impacts the quality and performance of the final products, a machine vision-based method for the yarn angle detection of glass fiber fabrics is proposed. The method involves pre-processing the image with brightness calculation, threshold segmentation, and skeleton extraction to identify the feature region. Line segment detection is then performed on this region, using the Hough transform. The concept of a “line segment evaluation index” is introduced, and it was used as a criterion for assessing the quality and relevance of detected line segments. Moreover, the warp and weft yarn extrusion area contours refer to the reconstructed outlines of yarn areas, achieved by combining the center of mass extraction with morphological operations and used to accurately determine the yarn angle. Tested under a range of challenging scenarios, including varied lighting conditions, fabric densities, and levels of image noise, this method has demonstrated robust stability and maintained high accuracy. These tests mimic real-world manufacturing environments, where factors such as ambient light changes and material inconsistencies can affect the quality of image capture and analysis. The proposed method has high accuracy, as shown by MSE and a Pearson’s r of 0.931. By successfully navigating these complexities, the proposed machine vision-based approach offers a significant enhancement in the precision of yarn angle detection for glass fiber fabric manufacturing, thus ensuring improved quality and performance of the final products.

Effect of Weft Yarn Type and Weaving Parameters on Surface Roughness and Drapeability of Woven Fabric

ABSTRACT Comfort is a qualitative feature and one of the requirements that modern garment buyers place on their purchases. The purpose of this work is to study the effect of weft yarn type, weft yarn tension, warp yarn tension, and weft density on drape and surface roughness properties of cotton plain woven fabric. Each factor was treated at two levels such as yarn type (ring-spun and rotor-spun), warp tension (1 kN and 2 kN), weft tension (PFT/B- and PFT/B+T) and weft density (14 picks/centimeter (PPC) and 18 PPC). Full factorial design was used to design the experiment and analyze the results of the experiment. The results of the analysis showed that fabric produced from ring-spun yarn has smoother surface and better drape than fabric produced from rotor spun yarn. As weft and warp yarn tension increased, the surface roughness of the fabric increased and fabric drape decreased. On the other hand, fabric drape decreased as the weft density increased and the surface roughness of the fabric increase as weft density decreased.

Interfacial Enhancement and Composite Manufacturing of Continuous Carbon-Fiber-Reinforced PA6T Composites via PrePA6T Ultrafine Powder.

Semi-aromatic poly (hexamethylene terephthalamide) (PA6T) oligomer (prePA6T) ultrafine powder, with a diameter of <5 μm, was prepared as an emulsion sizing agent to improve the impregnation performance of CF/PA6T composites. The prePA6T hyperfine powder was acquired via the dissolution and precipitation "phase conversion" method, and the prePA6T emulsion sizing agent was acquired to continuously coat the CF bundle. The sized CF unidirectional tape was knitted into a fabric using the plain weave method, while the CF/PA6T laminated composites were obtained by laminating the plain weave fabrics with PA6T films. The interfacial shear strength (IFSS), tensile strength (TS), and interlaminar shear strength (ILSS) of prePA6T-modified CF/PA6T composites improved by 54.9%, 125.3%, and 120.9%, respectively. Compared with the commercial polyamide sizing agent product PA845H, the prePA6T sizing agent showed better interfacial properties at elevated temperatures, especially no TS loss at 75 °C. The SEM observations also indicated that the prePA6T emulsion has an excellent impregnation effect on CF, and the fracture mechanism shifted from adhesive failure mode to cohesive failure mode. In summary, a facile, heat-resistant, undamaged-to-fiber environmental coating process is proposed to continuously manufacture high-performance thermoplastic composites, which is quite promising in mass production.

Computational Evaluation of Weaving Process on Mechanical Stiffness of Plain Weave Fabric

Inherent structural stress in a plain weave is induced during the formation process of fabrics, and its evaluation is useful for estimating the mechanical stiffness of weaves. In this study, the effect of inherent stress distributed in a weave fabric was investigated to estimate its mechanical stiffness. Here, a numerical simulation method that imitates the fabrication process of fabrics is proposed to evaluate stiffness. A diagram illustrating the weaving process is defined in this evaluation method. For computational analysis, a unit cell model used in homogenization was developed based on the structural periodicity of the plain weave structure using the finite element method. The weaving state was accomplished by simulating the weaving behavior in this model. The weaving state included the geometric shape and stress/strain data. Subsequently, a model was built to estimate the mechanical stiffness based on the weaving state data. Finally, a uniaxial tensile simulation was conducted using the numerical model. Using this evaluation method, the effect of inherent stress on the mechanical stiffness of weaves was quantified, which indicated that the tensile stiffness improved in a small strain range. The effect gradually decreased as the tension progressed.

Influence of the mesostructure on the fatigue behaviour of textile composites

The aim of the present work is to analyze the influence of the mesostructure on the fatigue behaviour of textile composites. By affecting the stress distribution within a laminate, the mesostructure largely determines the damage evolution under cyclic loadings. In this work, plain woven fabrics with different number of layers were tested under cyclic loadings along the warp and weft directions, monitoring the damage evolution. The differences in meso- and micro-structure, together with the position of the bundle in the laminate, affect the fatigue-induced damage mechanisms. The stress fields obtained from 3D Finite Element analyses shed light onto the influence of the mesostructure on the damage onset. Eventually, a stress-based strategy to predict the life to crack initiation is proposed and validated against experimental data.

The investigation and fabrication of novel ballistic composites with checkerboard-shaped lay-up design to improve ballistic performances

High-performance and lightweight ballistic composites prepared through layer-by-layer lay-up of matrix and fabric have attracted significant interest. However, the traditional full-coverage lay-up design constrains the energy absorption of the composites during ballistic impact. Therefore, novel ballistic composites configured with checkerboard-shaped lay-up design were studied, using checkerboard-shaped polycarbonate (PC) films and aramid plain-woven fabrics. The effect of the size and cross-layered distribution of the checkerboard-shaped PC films was investigated. Compared with the full-coverage lay-up design, the checkerboard-shaped lay-up design can effectively improve the ballistic performances. For checkerboard-shaped lay-up design ballistic composites, the ballistic performances exhibited minor variation when impacting PC regions but gradually increased with the size of the fabric regions when impacting aramid fabric regions. The ballistic performances of interval cross-layered checkerboard-shaped PC films also increased with the number of interval layers. When impacting PC regions, the primary ballistic mechanisms were compression/shear and shear/tensile failures; however, when delamination and stress waves propagated into the regions without PC films, the checkerboard lay-up design allowing for effective energy absorption through tensile failure by fabrics. When impacting aramid fabric regions, the primary ballistic mechanisms were shear/tensile failure and tensile failure. However, when the size of aramid fabric region was insufficient, the near PC region can restrict transverse deformation of the fabrics, which did not benefit the ballistic performances.

Artificial neural network and multiple linear regression modeling for predicting thermal transmittance of plain-woven cotton fabric

The present research compares a machine learning model with a statistical model, with specific emphasis on artificial neural networks and multiple linear regression models. The aim of this study is to forecast the thermal transmittance of a plain-woven cotton fabric using input data such as thread density measured in ends per inch, picks per inch, and fabric thickness. The artificial neural network is built using a network with feed-forward backpropagation, and the MATLAB software’s training function trainlm is used to modify its weight and basic values based on Levenberg–Marquardt optimization techniques. The sigmoid transfer function is used to set the layer output and measure network performance in terms of the root mean squared error, mean absolute error percentage, and coefficient of determination which were determined. For the artificial neural network prediction model, the root mean squared error and mean absolute error percentage were 1.05 and 3.132%, respectively, while the coefficient of determination was 0.9307. In contrast, the multiple linear regression prediction model had root mean squared error and mean absolute error percentage values of 2.98 and 8.97%, respectively, along with a coefficient of determination of 0.4727. The results reveal that the artificial neural network model outperforms the multiple linear regression model, showing superior accuracy and robustness in capturing the intricate interactions between important fabric parameters (ends per inch, picks per inch, and thickness) and thermal transmittance values. This research emphasizes the efficiency of artificial neural network modeling as a superior tool for forecasting thermal transmittance in textile applications rather than employing the time-consuming trial-and-error process for delivering significant insights for material engineering and energy-efficient design.

Research on the automatic modeling and performance prediction of plain-woven composites based on beam elements

This work presents an approach for the automatic modeling and high-efficiency simulation of the mechanical properties of plain-woven composites. For the beam element finite element model, a technical scheme for the automatic modeling of plain-woven fabrics is presented. Considering the constraint relationship between the matrix and the fibers, a method for creating matrix beam elements is proposed. Then, a beam element solver was compiled to simulate the tensile properties of the plain-woven composites. In addition, a method of rendering a three-dimensional model of yarn and the simulation results were presented, and a comparison between real fabric images and modeled fabric structure confirmed that the method proposed in this work could effectively model plain-weave fabric structures. Experimental results showed that the deviations of the tensile modulus and strength were 0.41% and −7.59% respectively, which verified the validity of the beam element model used in this study. Moreover, testing verification of the method used in this study could realize the automatic modeling and simulation of representative cells of plain-woven composites in a few seconds. The above results show that this work offers the potential to handle the efficient calculations of large-scale woven structure models.

The Fatigue Response’s Fingerprint of Composite Materials Subjected to Constant and Variable Amplitude Loadings

This paper discusses the theoretical and experimental correlations between fatigue and static strength statistical distributions. We use a two-parameter residual strength model that obeys the qualitative strength-life equal rank assumption (SLERA) for guidance. The modeling approach consists of recovering the model’s parameters by best fitting the constant amplitude (CA) fatigue data at a given stress ratio, R, and the experimental Weibull parameters of the static strength distribution function. An extensive set of fatigue life and residual strength data for AS4 carbon/epoxy 3k/E7K8 Plain Weave Fabric with [45/−45/90/45/−45/45/−45/0/45/−45]S layups, obtained at different stress ratios, R, have been analyzed. The modeling approach consists of recovering the model’s parameters from pure tension or compression fatigue data at R = 0.1 and R = 5, respectively. Once the parameters are fixed, the model’s capabilities, potential, and limits are discussed by comparing its predictions with residual strength and fatigue life data obtained at stress ratios with mixed tension/compression loadings, namely R = −0,2 and R = −1. Moreover, from a preliminary analysis, the theoretical extension of the model’s capabilities to variable amplitude loadings is conceptualized. The application of Miner’s rule is also discussed and compared with a new damage rule to analyze the fatigue responses under variable amplitude loadings.