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Modeling the geometry of textile reinforcements for composites: TexGen
Abstract
This chapter provides an overview of TexGen, the open-source software package for 3D modeling of textiles and their composites developed at the University of Nottingham. The modular design of the cross-platform software and its modules (Core, Renderer, Export, Python Interface, and Graphical User Interface) are described. The underlying modeling theory is then discussed, followed by descriptions of applications utilizing TexGen in the fields of textile mechanics, textile composite mechanics, and permeability. Developments for creation of models for 3D weaves are described including the extension of modeling to more complex shapes such as T-pieces and a framework for optimization of these geometries. Finally, future developments, including further automation of the modeling process, improvements to methods of dealing with yarn interpenetration, issues of variability and optimization of complex structures are considered, all of which will enable a more robust design process for new, complex 3D woven structures.
... A meso-mechanical RUC model is developed to study the effect of intrayarn hybridisation and weave architecture on the homogenised properties and meso-stress fields. The open-source software TexGen [28] is used to model the geometry of 2D woven composite laminae with intrayarn fibre hybridisation for the meso-mechanical RUC model. The twoscale homogenisation framework is implemented in Python and is integrated with Abaqus/Standard [29]. ...
... Three geometric parameters are considered for meso-scale modelling: yarn cross-section, yarn path and yarn volume fraction. The local fibre orientation is assigned along the yarn path [28]. The yarn cross-section is assumed to be a constant lenticular shape along the yarn path, and the shape is defined by polar coordinate interpolation functions by specifying the height, width, and power of the cross-section. ...
... The weave architecture is generated by interlacing the yarns in the weft and warp directions while avoiding yarn overlaps and small yarn gaps [28]. The homogenised yarn properties obtained from the micromechanical RVE model are employed for the RUC model. ...
In this paper, the effect of intra-yarn fibre hybridisation on the homogenised elastic properties and micro- and
meso-scale matrix stress fields in 2D woven composite laminae (i.e. plain, 2/2 basket, 2/2 twill and 5-harness
satin) is studied with a two-scale homogenisation scheme—employing a representative volume element model
at micro-scale and a repeating unit cell model at meso-scale. The study is focused on Sglass/polypropylene/epoxy woven laminae with intra-yarn fibre hybridisation. A modified random sequential
expansion algorithm generates microstructure for the micro-mechanical model, and a periodic meso-structure
is used to generate the weave architecture for the meso-mechanical model. Both models are verified using
analytical models. It is found that intra-yarn fibre hybridisation can significantly alter the homogenised
properties as well as the micro- and meso-scale matrix stress fields—depending on the degree of hybridisation
(i.e. the combination of S-glass and PP fibre volume fractions). Moreover, the homogenised lamina properties
are found to be less sensitive to weave architecture and yarn thickness, but more so to the degree of intra-yarn
fibre hybridisation, yarn width and yarn spacing. It is shown that the lamina properties can be tailored, and the
micro- and meso-stress fields can be manipulated, by intra-yarn fibre hybridisation and weave architectures.
... The structure of the mesoscale RUC model used to analyse 3D orthogonal-woven flax/E-glass composite laminae, developed using TexGen [45], is presented in Figure 2. The composite comprises flax/E-glass hybrid yarns and matrix, with warp, weft, and binder yarns aligning with the X, Y, and Z axes, respectively. The model includes three weft yarn layers, two warp yarn layers and a single binder yarn, with a warp-to-binder yarn ratio of 2:1. ...
This study investigates the novel role of yarn-level fibre hybridisation in tailoring thermomechanical properties and thermal residual stress (TRS) fields in the resin at both micro- and meso-scales of 3D orthogonal-woven flax/E-glass hybrid composites. Unlike previous studies, which primarily focus on macro-scale composite behaviour, this work integrates a two-scale homogenisation scheme. It combines microscale representative volume element (RVE) models and mesoscale repeating unit cell (RUC) models to capture the effects of hybridisation from the fibre to lamina scale. The analysis specifically examines the cooling phase from a curing temperature of 100 °C down to 20 °C, where TRS develops due to thermal expansion mismatches. Microstructures are generated employing a random sequential expansion algorithm for RVE models, while weave architecture is generated using the open-source software TexGen 3.13.1 for RUC models. Results demonstrate that yarn-level hybridisation provides a powerful strategy to balance mechanical performance, thermal stability, and residual stress control, revealing its potential for optimising composite design. Stress analysis indicates that under in-plane tensile loading, stress levels in matrix-rich regions remain below 1 MPa, while binder yarns exhibit significant stress concentration, reaching up to 8.71 MPa under shear loading. The study quantifies how varying fibre hybridisation ratios influence stiffness, thermal expansion, and stress concentrations—bridging the gap between microstructural design and macroscopic composite performance. These findings highlight the potential of yarn-level fibre hybridisation in tailoring thermomechanical properties of yarns and laminae. The study also demonstrates its effectiveness in reducing TRS in composite laminae post-manufacturing. Additionally, hybridisation allows for adjusting density requirements, making it suitable for applications where weight and thermal properties are critical.
... This area consists of 4 Â 4 geometric unit cells, in both the warp and weft directions, representing a single repeat of the weave pattern, specifically a 2/2 twill weave, as shown in Figure 4(a). The geometric arrangement of yarns forming a 3D textile assembly was initially generated using open-source TexGen software, 40 and the resulting geometry was extracted as a STEP file for further processing. The STEP file was then imported into commercially available Abaqus software for simulation. ...
Numerical modeling of textile structures at the yarn level is challenging, yet provides information not obtainable through experimental studies alone. This study is focused on the development and finite-element analysis (FEA) of a three-dimensional (3D) woven structure with an in-plane negative Poisson’s ratio (NPR) effect, with the aim of exploring its potential applications in polymer composite reinforcement. While experimental and geometrical studies of 3D auxetic woven structures provide primary information, they have limitations in explaining the auxetic behavior of the structure at the yarn level. Additionally, prediction of the auxetic behavior of the 3D woven structure by varying material properties is only possible through FEA. Therefore, to overcome these limitations, a 3D FEA model of the structure was developed using commercially available software (Abaqus CAE-2020) to simulate the auxetic behavior. The structure was then studied for different binding yarn properties once a good agreement had been found between simulated and experimental results. The FEA provides new insights and provokes fresh discussion on the auxetic behavior of the 3D woven structure. One significant finding from the FEA is the strong influence of the axial ([Formula: see text]) and radial ([Formula: see text]) moduli of the binding yarn on the Poisson’s ratio of the 3D woven structure; [Formula: see text] has an inverse relationship, while [Formula: see text] demonstrates a direct relationship with the auxetic behavior of the structure. The developed FEA model is expected to provide a better foundation for the future development of 3D auxetic structures, particularly concerning their application in polymer composite reinforcement.
... In recent times, employing finite element analysis to forecast the mechanical characteristics of composite materials with intricate geometries has emerged as a highly effective strategy for achieving optimal design before the manufacturing phase, and numerous scholars have likewise created plugins tailored to diverse applications based on their specific requirements and contexts [47][48][49][50][51][52]. In this context, the aforementioned multi-scale modeling strategy was utilized to estimate the mechanical properties via ABAQUS software. ...
This study aims to investigate the compression behavior of newly designed 3D weft-knitted pyramidal composites. These structures consist of upper and lower surface layers interconnected by two truncated incomplete pyramids, formulated in three varied core geometries. The 3D integrated knitted samples were manufactured on an electronic flat knitting machine using E-glass yarns and were impregnated with epoxy resin using a resin transfer molding technique. A novel ABAQUS plugin has been developed to gain insight into the deformation and failure mechanisms, facilitating the prediction and enhancement of Hashin’s benchmark data. The compressive performance of the designed structures was compared with the integrated corrugated sandwich structures containing three triangular, trapezoidal, and rectangular cross-sections. The results extracted from the experiments suggest that the structural height exerts a considerable influence on the mechanical characteristics of the 3D composite structures. Consequently, the compressive strength of the specimens exhibits a notable decline as the thickness increases. Also, the geometric configuration of the interconnected layers within the reinforcement structure is pivotal in establishing the compressive attributes of these 3D knitted reinforced composites. The developed 3D knitted composites demonstrated compressive behavior similar to honeycomb sandwich panels and showed better performance than integrated corrugated sandwich panels. The enhancements observed include a 50% increase in the fiber volume fraction, a 28.66% augmentation in the maximum compressive force, a 57.90% rise in absorbed specific energy, and an 86.55% improvement in strength compared to integrated corrugated sandwich panels. Ultimately, the comparative analysis of numerical and experimental force-displacement curves elucidated that the plugin proficiently predicts the behavior of these composites with a considerable degree of accuracy.
... Importantly, at the meso scale we used TexGen software [21], an open-source software developed at the University of Nottingham and licensed under the General Public License, serves as a powerful tool for modeling the geometry of textile structures. It not only offers cutting-edge insights into weaving technology and 3D fabrics but also delves into weaving preparation, mechanics, limits of the weaving processes, pattern design, and applications. ...
This paper integrates numerical and experimental approaches to predict the mechanical properties of a woven composite with carbon fiber-based fabrics. Initially, a multiscale modeling approach based on the finite element method ascertained the micro-scale properties of the composite tows, taking into account the effect of voids present in the epoxy resin. Subsequently, a meso-scale model was built and employed to predict the mechanical properties of the composite at this scale. The representative volume elementary (RVE) was generated using TexGen software, and was then imported and used by Abaqus software to compute the effective mechanical properties. Lastly, a macro-scale model of a composite beam was created, simulating a three-point bending test using the effective mechanical properties obtained previously. Concurrently, a physical counterpart of the composite beam was manufactured and subjected to a laboratory three-point bending test, measuring the flexural modulus and many other parameters. A comparison of the two sets of results revealed a high degree of consistency.
... We note that careful considerations on selecting the appropriate RVE and the associated effects of microstructural features [24] and resolutions [25] can be important when considering multiphysics problems, including nonlinear constitutive behaviors. We created these woven structures using the open-source software TexGen [26]. The morphology of the composite was assumed to remain constant for each simulation. ...
... 27 The geometries to be scanned are generated with the open source software TexGen. 28 The segmented ground truths are received by voxelizing the input surface meshes in the same frame of reference as the simulated scan is performed. This is shown in Figure 7. ...
... In addition to this, several factors such as scatter in fiber diameter, kinks in fiber, scatter in fiber length, and surface roughness can lead to discrepancies between numerical predictions and experimental results. 21 Concerning the effective permeability prediction of fabrics, idealized unit cell models have been conventionally created for mesoscopic analyses by textile software such as TexGen 22 and WiseTex. 23 However, they usually did not take into account the fact that the actual crosssectional profiles of the warp and weft tows are not ideally regular if the variability of the real local structure is not analyzed and inputted. ...
Permeability quantifies the flow conductivity of fabric reinforcements and is key to predicting mold filling times and resin flow in liquid composite molding (LCM). Flow depends on the micron‐level channels within the tows and the millimeter‐level channels between them. This study presents a general multi‐scale permeability prediction framework for fabrics considering realistic inter‐ and intra‐tow geometry. A misaligned fiber representative volume element model was constructed by a random perturbation method at the micro‐scale with orientation parameters identified from microscopic images of the cross‐section. At the meso‐scale, a tow cross‐section wrapping algorithm and an interference elimination algorithm were proposed to construct continuous as‐woven tows from the virtual fiber compression simulation. The governing fluid dynamics equations were solved to obtain the flow field within the multi‐scale gaps and compute the permeability. The simplified model's permeability predictions differed from experimental results by 12.7% to 16%. This work provides valuable insights for further research and development in LCM.
Highlights
Fabric permeability framework considers realistic tow geometry for prediction.
Microscale misaligned fiber SVE model predicts tow permeability.
Adaptive winding & interference algorithms aid tow description transition.
A simplified model predicts permeability reasonably without 3D measurements.
... Compared to the unidirectional fiber composite, now local material orientation is present for the yarns, illustrated in Fig. 9. The 3-d finite element model is constructed using TexGen [52] The real linear elastic properties of the two phases are adapted from [9] and can be found in Tab. 5. The matrix is isotropic while the carbon fiber tows are assumed to be transversely isotropic in the local material frames. ...
Deep Material Network (DMN) has recently emerged as a data-driven surrogate model for heterogeneous materials. Given a particular microstructural morphology, the effective linear and nonlinear behaviors can be successfully approximated by such physics-based neural-network like architecture. In this work, a novel micromechanics-informed parametric DMN (MIpDMN) architecture is proposed for multiscale materials with a varying microstructure characterized by several parameters. A single-layer feedforward neural network is used to account for the dependence of DMN fitting parameters on the microstructural ones. Micromechanical constraints are prescribed both on the architecture and the outputs of this new neural network. The proposed MIpDMN is also recast in a multiple physics setting, where physical properties other than the mechanical ones can also be predicted. In the numerical simulations conducted on three parameterized microstructures, MIpDMN demonstrates satisfying generalization capabilities when morphology varies. The effective behaviors of such parametric multiscale materials can thus be predicted and encoded by MIpDMN with high accuracy and efficiency.
... This example is chosen here in order to outline the proposed multiscale procedure. A weave fabric unit cell with two yarns per direction has been generated by texgen [36]. The dimensions are: Yarn spacing = 2, Yarn width = 0.8, Fabric thickness = 0.2. ...
Homogenization for complex, nonlinear materials, including composites and textiles, is considered. The effect of the microstructure, including nonlinearity, for various loadings is transferred to the homogenized medium through the Representative Volume Element technique. The classical approach through nested finite element analysis, the so-called FEM2 method, is very expensive. Data-driven techniques have been proposed, where the homogenization is replaced by a surrogate model based on data generated through selected numerical or physical experiments. An artificial neural network surrogate constitutive model leads to a FEANN method. Furthermore data-driven solution methods have been recently proposed, as a development of the LATIN iterative method. A short review of recent contributions is presented, with examples from composites, including woven composites and auxetics. Research topics will be discussed, including the development of Physics Informed Neural Network surrogates.
... The 3-d finite element model is constructed using TexGen [50] with 4 volume fraction values for the tows, see Fig. 33. Three of them (vf = 0.459, vf = 0.608 and vf = 0.729) constitute the parametric sample set P and are used to generate training dataset, while vf = 0.537 is used to test interpolation accuracy. ...
Deep Material Network (DMN) has recently emerged as a data-driven surrogate model for heterogeneous materials. Given a particular microstructural morphology, the effective linear and nonlinear behaviors can be successfully approximated by such physics-based neural-network like architecture. In this work, a novel micromechanics-informed parametric DMN (MIpDMN) architecture is proposed for multiscale materials with a varying microstructure characterized by several parameters. A single-layer feedforward neural network is used to account for the dependence of DMN fitting parameters on the microstructural ones. Micromechanical constraints are prescribed both on the architecture and the outputs of this new neural network. The proposed MIpDMN is also recast in a multiple physics setting, where physical properties other than the mechanical ones can also be predicted. In the numerical simulations conducted on three parameterized microstructures, MIpDMN demonstrates satisfying generalization capabilities when morphology varies. The effective behaviors of such parametric multiscale materials can thus be predicted and encoded by MIpDMN with high accuracy and efficiency.
... In the next step, a mesoscale plain woven RVE is generated using the geometric textile modeling software package TexGen (Brown and Long, 2021). A textile weave model is created with elliptical yarn crosssections and with a yarn spacing of 10 mm, a yarn width of 8 mm, and a fabric thickness of 2 mm. ...
Time-consuming and costly computational analysis expresses the need for new methods for generalizing multiscale analysis of composite materials. Combining neural networks and multiscale modeling is favorable for bypassing expensive lower-scale material modeling, and accelerating coupled multi-scale analyses (FE2). In this work, neural networks are used to replace the time-consuming micromechanical finite element analysis of unidirectional composites, representing the local material properties of yarns in woven fabric composites in a multiscale framework. Leveraging the fast multiscale data generation procedure, we presented a second neural networks model to estimate the elastic engineering coefficients of a particular weave architecture based on a broad range of dry resin and fiber properties and yarn fiber volume fraction. As an outcome, this paper provides the user with a generalized, neural network-based approach to tackle the balance of computational efficiency and accuracy in the multiscale analysis of elastic woven composites.
... Besides, the modeling of woven composite is complex, especially the discretization of the matrix mesh and processing of the contact relationship between the matrix and the fibers, which require considerable manual operations. TexGen software, 17,18 enabling the parametric modeling of woven composite, has been well-received since its introduction. Furthermore, TexGen contains the interface of commercial FEM software, which can be directly connected to finite element calculations. ...
This work presents a beam element approach for the modeling and high-efficiency simulation of mechanical properties of 2.5D woven composite. For the beam element model, a technical scheme for the parametric modeling of 2.5D woven fabrics was produced. Considering the constraint relationship between the matrix and the fibers, we proposed a method for creating matrix beam elements. Then, a beam element solver was compiled to simulate the mechanical properties of the 2.5D woven composite. Meso-scale analysis of curved shallow-crossing linking 2.5D woven composite using the proposed model obtained the accurate tensile modulus. Full-scale analysis was implemented to simulate bending behavior of straight shallow-crossing linking 2.5D woven composite, and the simulation results agreed well with the experimental results. The above analysis could automatically complete modeling, analysis and post-processing in a relatively short time, reflecting the efficiency advantages of the method in this paper.
... A software produced as a secondary development of Abaques CAE, UnitCells© [17], written in python, automates the modelling steps of unit cells of various types. Specialised preform generators WisTex [18] and TexGen [19] allow the creation of unit cells and larger size models of preforms that can be applied as input of preform deformation simulations. The automated tools mentioned above all predefine the yarn as a uniform shape, which cannot fully reflect the complexities within the composite, such as the variety of yarn cross-section shapes and yarn paths. ...
It has been confirmed in several other studies is that the effect of yarn geometry variations on composite properties is non-negligible. This work presented a parameterized and automated modelling method for generating 3D orthogonal woven composite RVE geometry including yarn geometry variations. In this method, an RVE was considered to be obtained by geometrically transforming several basic yarns containing some geometrical features. Yarn geometry variations are considered and in particular two special parameters are defined to adjust the binder yarn embedded modes and outer-warp transverse bending. The section and path geometry are described by several parametric splines, where common spline control points are defined to treat the geometric contact between the interwoven yarns. An actual 3D orthogonal woven preform was used to verified the validity of the proposed method. Finally, two sets of RVE models were established to study the effects of the binder embedded and outer-warp transverse bending on the material elasticity moduli.
... individual yarn cross-sectional areas and yarn path detours). One such popular open-source tool for modeling an idealized composite weave geometry at the mesoscale is TexGen [17]. ...
A new, machine learning-based approach for automatically generating 3D digital geometries of woven composite textiles is proposed to overcome the limitations of existing analytical descriptions and segmentation methods. In this approach, panoptic segmentation is leveraged to produce instance segmented semantic masks from X-ray computed tomography (CT) images. This effort represents the first deep learning based automated process for segmenting unique yarn instances in a woven composite textile. Furthermore, it improves on existing methods by providing instance-level segmentation on low contrast CT datasets. Frame-to-frame instance tracking is accomplished via an intersection-over-union (IoU) approach adopted from video panoptic segmentation for assembling a 3D geometric model. A corrective recognition algorithm is developed to improve the recognition quality (RQ). The panoptic quality (PQ) metric is adopted to provide a new universal evaluation metric for reconstructed woven composite textiles. It is found that the panoptic segmentation network generalizes well to new CT images that are similar to the training set but does not extrapolate well to CT images of differing geometry , texture, and contrast. The utility of this approach is demonstrated by capturing yarn flow directions, contact regions between individual yarns, and the spatially varying cross-sectional areas of the yarns.
... The PBC formulations are adequately detailed in a previous publication by the authors [30]. A Python implementation in TexGen software [51,52] is used to obtain the conformal mesh for the yarns owing to its superiority over voxel meshes [53] for interface definitions. ...
Prediction of underwater explosion response of coated composite cylinders using machine learning (ML) requires a large, consistent, accurate, and representative dataset. However, such reliable large experimental dataset is not readily available. Besides, the ML algorithms need to abide by the fundamental laws of physics to avoid non-physical predictions. To address these challenges, this paper synergistically integrates ML with high-throughput multiscale finite element (FE) simulations to predict the response of coated composite cylinders subjected to nearfield underwater explosion. The simulated responses from the multiscale approach correlate very well with the experimental observations. After validation of the multiscale approach, a representative and consistent dataset containing more than 3800 combinations is developed using high-throughput multiscale simulation by varying the fiber/matrix/coating material properties, coating thickness as well as experimental variables such as explosive energy and stand-off distance. The dataset is leveraged to predict the response of coated composite cylinders subjected to nearfield underwater explosion using a feed-forward multilayer perceptron-based neural network (NN) approach which shows excellent predictions. Overall, the synergistic approach powered by physics-based simulations presented here can potentially enable materials scientists and engineers to make intelligent, informed decisions in the purview of innovative design strategies for underwater explosion mitigation in composite structures.
... In addition, the use of continuous damage mechanics as well as element deletion techniques could be implemented. Here, an isotropic damage model (Zhou et al., 2014) could be used for controlling element deletion of the fibers. Further research on the fiber response of pin penetration should be done based on this modeling method using detailed material data and validated with experimental tests. ...
A new type of washer with integrated pin structures was developed and presented in a previous study for the use in mechanical joints of fiber-reinforced plastics (FRP) and metal sheets. Thereby, the pin-structured washer significantly increases the load-bearing capacity of mechanically joined FRP-metal combinations. To do so, the FRP hole area is to be relieved by transferring the occurring loads into the laminate via the pin structures. In thermoset FRP, the insertion of the pin-structured washer usually leads to fiber breaks. For fiber-reinforced thermoplastics (FRTP) the chance of fiber failures during the penetration process can be reduced by inserting the pin-structured washer via an ultrasonic-based locally invasive heating system. By doing this, the polymer is locally molten, allowing the fibers to move around the pin structures. However, the ultrasonic-based insertion does not allow visual observation of the fiber movement within the process. With the aim of getting information about the fibers, that are moved, stressed or broken depending on the pin tip geometries, a numerical investigation was carried out. Therefore, a 3 × 3 twill model of a dry woven fabric segment based on a Bézier curve for yarn simplifications was developed. With respect to the molten polymer during the penetration process, the effect of the matrix was neglected. With consideration of necessary simplifications regarding the calculation time, the stress distribution on the dry woven fabric and a regular pattern of the damage situation of the fibers could be investigated. To understand the mechanisms of the fiber behavior within the penetration process, three different pin diameters and pin tip angles were examined and compared in numerical simulations.
... The parametric method is widely used in the geometric modelling of composite preforms because of its high extendibility and computational efficiency. One of the most popular tools is the dedicated modelling package TexGen [7], which is used to construct the preform by scanning the cross-section of 2D fibre tows along the cubic spline. However, the drawback with this tool is that it cannot automatically eliminate the inter-penetration of fibre tows. ...
The mesoscopic model of fibre-reinforced composites can provide key geometric and material related information for predicting the mechanical properties of composite components. In this study, an approach to build a mesoscale preform of a plain-weave composite component with complex geometry was established. This was achieved via parameterisation and integration - with a set of parameters, related to the preform geometry, and a macroscopic geometrical model, of the composite component, as the inputs. In this method, tow centrelines were simulated as sinusoids in curvilinear coordinates. A simplified model of the tow section is proposed at the mesoscale. Based on this method, the geometry of the plain-weave preform at the mesoscale can be obtained integrally according to the macroscopic shape of the component input. The credibility of this proposed method was verified with similar microscopic observations and experiments conducted in other studies. The applicability of this approach to a more complex component was also investigated. Finally, a characteristic layer was established to analyse the material aperiodicity in a complex component.
... [49][50][51][52][53][54] For 2D or 3D textile structural composites, the architectures of the preform are more complicated as the tows crimp and interlace. Although the geometry could be obtained with textile geometrical simulators such as Tex-Gen 55 or WiseTex, 56 they are idealized geometry without taking into account the geometrical imperfections or specificities of the materials. However, the high-resolution of μ-CT enable the visualization of each fiber tow and intra/ inter-tow voids that can be directionally introduced to finite element models, [57][58] which will provide a more real geometry of 3D composite reinforcements. ...
With the development of X-ray computed tomography over the last few decades, it is gradually considered to be a powerful tool in the field of materials research. This paper presents a comprehensive review of applications of CT imaging on fiber reinforced composites, from polymer composites to ceramic matrix composites. The principle of X-ray CT and experimental tomography setups was described firstly. Then, in situ experimental devices developed in recent years were illustrated. Furthermore, the applications of X-ray CT imaging on manufacturing process, modeling, mechanical damage, physical, and chemical behaviors were reviewed in detail. Besides, advantages and limitations of X-ray CT imaging were pointed out and the future development was prospected.
This paper investigates how combining natural and synthetic fibers within yarns, altering the degree of hybridisation, and varying weave architectures affect the homogenized elastic properties and stress distributions in 2D woven composite laminae using a two‐scale homogenization scheme. The novelty lies in integrating a micro‐scale representative volume element model with a meso‐scale repeating unit cell model to capture intra‐yarn natural/synthetic fiber hybridisation. The study focuses on 2/2 twill and 5‐harness satin woven laminae with flax/E‐glass, hemp/E‐glass and basalt/E‐glass hybrid yarns, all with a total fiber volume fraction of 0.6. Fiber distributions are created through a random sequential expansion algorithm for hybrid RVEs, while periodic meso‐structures are used to define weave architectures for RUCs. Results show that yarn‐level fiber hybridisation significantly influences matrix stress distributions, with variations of up to 22%. In contrast, weave architecture has a minimal effect, with variations in homogenized properties below 2%. Varying fiber types, degrees of hybridisation and weave architectures allow for the tailoring of yarn and lamina properties and altering the stress distributions at micro‐ and meso‐scales and potentially influencing damage mechanisms. The modeling approach for analyzing the mechanical behavior of intra‐yarn hybrid natural/synthetic woven laminae could potentially be used to tailor their tolerance to damage.
Highlights
Two‐scale homogenization integrates RVE and RUC for 2D woven hybrid composites.
Analyzed flax/E‐glass, hemp/E‐glass, basalt/E‐glass in twill and satin weaves.
Intra‐yarn hybridisation significantly affects properties and stress fields.
Hybridizing fibers offers tailored properties and may improve damage tolerance.
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.
In this paper, the effect of intra-yarn hybridisation on the macroscopic homogenised properties of natural fibre-based hybrid composites (NFHCs) was computationally investigated. Many researchers have experimentally investigated hybrid effects on their mechanical properties. Only a limited number of computational studies on NFHCs have been reported. Four hybrid plain weave laminates: jute-glass, hemp-glass, jute-carbon and hemp-carbon were studied using a two scale modelling approach. The approach is based on homogenisation in which micromechanical representative volume element (RVE) model and mesomechanical repeating unit cell (RUC) model are established separately. The results indicate that hemp-glass hybrid 2D woven composites may be more cost-effective than glass woven composites in structural applications.
This study presents the experimental and numerical characterization of composite laminates manufactured using a novel method known as Advanced Placed Ply (AP-PLY). The behavior of cross-ply and quasi-isotropic AP-PLY laminates under uniaxial tension is compared with that of baseline laminates. Stiffness is found to be unaffected by the preforming process, while the strength is dependent on the laminate configuration. A 3D multiscale numerical modeling framework is developed to capture the effect of the through-thickness fiber undulations present in the AP-PLY composites. The ability of the framework to accurately predict the stress–strain behavior and failure mechanisms at a relatively low computational cost is demonstrated. The approach is also exploited to investigate the influence of design parameters and improve the strength of the laminates. These results show the potential of the numerical framework to optimize the fiber placement preforming process to design AP-PLY components for structural applications.
In this study, the mechanical behaviors of a plain weave polyester fabric were investigated, along with the consequent changes in the internal structure under uniaxial tensile loading. Optical microscopy was used to establish relationships between the changes in the internal structure of the woven fabric during loading at several strain levels (from initial to pre-breakage stages). Using computer-aided design tools, a 3D geometric model of a woven pattern was built based on a lenticular plain weave model, and a corresponding engineering analysis was performed using the finite element method. A comparison of the model and experimental data showed good results for predicting the shape of the stress-strain curve for both directions of tensile testing, as well as for determining the geometric parameters of the woven fabric, such as the yarn spacing, migrations of individual filaments within the yarn cross-section, and changes in the yarn shapes in the fabric structure.
The 2.5D woven composite material has good resistance to delamination and impact load. However, its fatigue behavior is lack of investigation. In this work, first-order bending vibration fatigue tests were conducted on cantilever beam specimens made of 2.5D woven composites under different nominal stress levels. Test results showed that rapid damage evolution and accumulation occurred in the woven composites under a high stress level. However, under a low stress level, crack growth showed arrest behavior. The square root of residual stiffness showed a linear relation with resonance frequency, so the normalized full-time domain curves can be used to characterize the residual stiffness. On that basis, a residual stiffness model for the studied vibration fatigue specimens under other stress levels was proposed. Besides, a formula of ɛ-N curve was established for guiding the design and analysis of the 2.5D woven composite. To further reveal the failure mechanism, a multi-scale model of the woven composite was proposed. Numerical results showed that the high interlaminar shear stress between the yarn and the matrix near the compressed surface of the specimen caused material damage. This was consistent with the observed fracture topography, which verified the applicability of the multi-scale model.
The paper presents the results and analysis of interdisciplinary research concerning electromagnetic field shielding, conductive polymers printed on textiles and numerical simulation using the finite element method (FEM). The use of conductive, layered textiles for shielding electromagnetic interference (EMI) has been proposed. After establishing the optimal conditions for deposition of polyaniline (PANI) and polypyrrole (PPy) on polyacrylonitrile (PAN) fabric, conductive composites were made by means of reactive inkjet printing. For this purpose, polyacrylonitrile (PAN) fabrics were coated with polyaniline or polypyrrole, obtained by chemical oxidation of aniline hydrochloride and pyrrole by ammonium peroxydisulfate. The morphology of the obtained coatings was observed using a scanning electron microscope (SEM). The conductive properties (surface resistance) of the fabrics were measured using the four-wire method, and the tests of the effectiveness of electromagnetic shielding were carried out using the waveguide method in the frequency range from 2.5 to 18 GHz. The results of experimental shielding effectiveness (SE) tests and numerical simulation showed that the composites of polyacrylonitrile with polyaniline PAN/PANI and polyacrylonitrile with polypyrrole PAN/PPy achieved very good and good EMI shielding efficiency, respectively. Moreover, the obtained measurement results were verified by numerical modeling with the use of FEM–ANSYS HFFS software.
Three-dimensional networked fabric is a type of multilayer fabric consisting of distributed separate and combined sections. The combined sections interconnect adjacent sublayers of the fabric. This paper reported the influence of the combined sections on the response of networked fabric against ballistic impact utilising ballistic impact testing and finite element (FE) method. Energy absorption measured in the experiments was used to validate the FE modelling, showing that ABAQUS/Explicit is effective to simulate the ballistic impact process with high accuracy. Stress propagation, transverse deformation and movement of the secondary yarns related to the combined section have been evaluated. It has been found that the combined sections introduce stronger interaction between yarns than the separate sections do when the fabrics are impacted at the separate sections. This increases the energy transfer from primary yarns to secondary yarns. The combined sublayers serve like a modulator between the impact zone and the far-field boundary, leading to a delayed fracture of the primary yarns. As a result, the networked fabric absorb impact energy more efficiently than their counterpart layup of plain-woven fabrics. The findings revealed a new way to engineer soft fabrics for improved ballistic performance.
A meso-scale modelling framework is proposed to simulate the 3D woven fibre architectures and the mechanical performance of the composite T-joints, subjected to quasi-static tensile pull-off loading. The proposed method starts with building the realistic reinforcement geometries of the 3D woven T-joints at the mesoscale, of which the modelling strategy is applicable for other types of geometries with weave variations at the T-joint junction. Damage modelling incorporates both interface and constituent material damage, in conjunction with a continuum damage mechanics approach to account for the progressive failure behaviour. With a voxel based cohesive zone model, the proposed method is able to model mode I delamination based on the voxel mesh technique, which has advantages in meshing. Predicted results are in good agreement with experimental data beyond initial failure, in terms of load-displacement responses, failure events, damage initiation and propagation. The significant effect of fibre architecture variations on mechanical behaviour is successfully predicted through this modelling method without any further correlation of input parameters in damage model. This predictive method will facilitate the design and optimisation of 3D woven T-joint preforms.
The application of 3D weaves has advantages over conventional uni-directional or 2D woven lay-ups. There is potential to produce near net-shaped preforms and to increase damage resistance due to the presence of through thickness reinforcement. Conventional 3D weaves typically consist of orthogonal yarns interwoven with through thickness binder yarns. This paper describes a feasibility study to find optimum architectures for 3D woven fabrics where some of the normal manufacturing constraints are relaxed. This will provide the basis for development of novel manufacturing methods based on optimum textile architectures. A framework has been developed for the automatic generation and analysis of 3D textile geometries, utilising the open-source pre-processor TexGen. A genetic algorithm is used to select an optimum geometry by evaluating results from finite element simulations using the commercial solver Abaqus. This paper highlights the flexibility of TexGen software to create complex 3D models by means of its Python scripting application programming interface (API). A standard layer-to-layer geometry is used as a starting point to which off-axis yarn rotations, in-plane shift of entire layers and adjustments to binder yarns can be applied. Geometric variables are selected to represent the textile architecture enabling the automation of unit cell creation and finite element analysis. A Genetic Algorithm is used to determine the optimum through thickness binder path, the number and the width of the binders, and yarn angles using a weighted objective function of the material elastic properties. The case studies show that the algorithm is efficient to converge to the optimum fibre architecture.
A unit cell based Computational Fluid Dynamics model is presented for predicting permeability of multilayer fabric structures. In Liquid Composites Moulding processes, fabric lay-ups undergo significant manufacture-induced deformation, combining compression, shear, and inter-layer nesting. Starting from the configuration of un-deformed fabric, the deformation is simulated geometrically by accounting for self-imposed kinematic constraints of interweaving yarns. The geometrical modelling approach is implemented in the open-source software TexGen. The permeability tensor is retrieved from flow analysis in ANSYS/CFX, based on TexGen voxel models. Using only measured geometrical data for un-deformed fabrics, deformed plain weave fabric and twill weave fabric lay-ups were modelled and their permeability tensors predicted. Comparison with experimental data demonstrates the generally good accuracy of predictions derived from the proposed numerical method.
A range of typical packing systems were examined and the unit cells were established for micromechanical analysis of particle-reinforced composites. The unit cells were capable of dealing with problems involving reinforcing particles of irregular geometries and local imperfections. The unit cells established could be subjected to arbitary combinations of macroscopic stresses or strains using a single set of boundary conditions. The effective properties of the composite represented by the unit cells were obtained through the analysis.
TetGen is a C++ program for generating good quality tetrahedral meshes aimed to support numerical methods and scientific computing. The problem of quality tetrahedral mesh generation is challenged by many theoretical and practical issues. TetGen uses Delaunay-based algorithms which have theoretical guarantee of correctness. It can robustly handle arbitrary complex 3D geometries and is fast in practice. The source code of TetGen is freely available.
This article presents the essential algorithms and techniques used to develop TetGen. The intended audience are researchers or developers in mesh generation or other related areas. It describes the key software components of TetGen, including an efficient tetrahedral mesh data structure, a set of enhanced local mesh operations (combination of flips and edge removal), and filtered exact geometric predicates. The essential algorithms include incremental Delaunay algorithms for inserting vertices, constrained Delaunay algorithms for inserting constraints (edges and triangles), a new edge recovery algorithm for recovering constraints, and a new constrained Delaunay refinement algorithm for adaptive quality tetrahedral mesh generation. Experimental examples as well as comparisons with other softwares are presented.
Scatter in composite mechanical properties is related to variabilities occurring at different scales. This work attempts to analyse fibre strength variability numerically from micro to macro-scale taking into account the size effect and its transition between scales. Two micro-mechanical models based on the Weibull distribution were used within meso-scale finite element models of fibre bundles which were validated against experimental results. These models were then implemented in a meso-scale model of an AS4 carbon fibre plain weave/vinyl ester textile composite. Monte Carlo simulations showed that fibre strength variability has a limited effect on the strength of the textile composite at the meso-scale and introduces variability of less than 2% from the mean value. Macro-scale strength based on the predicted meso-scale distribution was lower than the strength of the composite without variability by 1-4% depending on the model. The presented multi-scale approach demonstrates that a wide fibre strength distribution leads to a narrow distribution of composite strength and a shift to lower mean values.
For a 3D orthogonal carbon fibre weave, geometrical parameters characterising the unit cell were quantified using micro-Computed Tomography and image analysis. Novel procedures for generation of unit cell models, reflecting systematic local variations in yarn paths and yarn cross-sections, and discretisation into voxels for numerical analysis were implemented in TexGen. Resin flow during reinforcement impregnation was simulated using Computational Fluid Dynamics to predict the in-plane permeability. With increasing degree of local refinement of the geometrical models, agreement of the predicted permeabilities with experimental data improved significantly. A significant effect of the binder configuration at the fabric surfaces on the permeability was observed. In-plane tensile properties of composites predicted using mechanical finite element analysis showed good quantitative agreement with experimental results. Accurate modelling of the fabric surface layers predicted a reduction of the composite strength, particularly in the direction of yarns with crimp caused by compression at binder cross-over points.
Predictive calculations of the physical properties of fibrous preforms and composite parts require an appropriate description of the preform geometry. Most internal dimensions of a preform are set during its manufacturing through mechanical interactions occurring between the tows and threads. However, the global shape and the interlacing patterns of the constituent textiles are determined independently. In this paper, a formal procedure for the description of the interlacing patterns is proposed. This procedure, which is based on the individual textile manufacturing processes, is general in the textiles considered and in the possible applications. The interlacing patterns are expressed by a series of vectors that follow a universal set of criteria and are generated from the values taken by the processing parameters. Defining examples are given for three-dimensional woven textiles and three-dimensional tubular braided textiles, and geometrical applications are also presented. Further examples for warp-knitted textiles and multiple-layer stacks will be given in a subsequent paper, together with examples of physical applications.
The processing properties of fibrous preforms and the final properties of liquid moulded composite parts are strongly related to the internal architecture of the preforms. The architecture of a preform is determined by the individual textile layers from which it is made. In order to calculate the processing and final properties in the same way over all the volume of a preform or part made from different types of textile, some sets of equations that generate similar definitions of the textiles from their manufacturing parameters are required. The similarity of these definitions is assessed through a series of criteria stated in a previous paper by the present authors; definition modules for woven and braided textiles were also presented in that paper. This paper presents a definition module, or a set of equations, that generates similar definitions for non-crimp reinforcements assembled by warp knitting; the equations also apply for the stitched threads used to assemble multiple-layer preforms. The definitions obtained from this module obey the criteria mentioned previously. The sets of equations presented in both papers cover most technical textiles; similar sets of equations can be created for speciality reinforcements and applied to the calculation of diverse physical properties of the preforms and parts. As an example, this paper discusses the mapping of the voids which are defined between the tows and threads of non-crimp stitched reinforcements.
Textile permeability in general shows a high variance. The present work describes a method to model textile variability at the mesoscopic scale based on a generalised textile model. Inhomogeneities were introduced into the textile structure by randomly moving the tow paths at the cross-overs according to a given normal distribution. The effects of various factors on the evaluated permeability variation were explored and demonstrated, using non-crimp fabric and plain weave models. Fabric architecture was shown to be important in that it imposed a limit to the degree of variation of the tows. A linear relationship can be deduced for the relative variation of permeability as a function of the relative variation of fibre volume fraction, which links the predicted and measured values. When utilising predicted mesoscopic permeability values in macroscopic analyses, the domain size of the mesoscale model has to be related to the element size of the macroscopic analyses.
In this study, a finite element model to predict shear force versus shear angle for woven fabrics is developed. The model is based on the TexGen geometric modelling schema, developed at the University of Nottingham and orthotropic constitutive models for yarn behaviour, coupled with a unified displacement-difference periodic boundary condition. A major distinction from prior modelling of fabric shear is that the details of picture frame kinematics are included in the model, which allows the mechanisms of fabric shear to be represented more accurately. Meso- and micro-mechanisms of deformation are modelled to determine their contributions to energy dissipation during shear. The model is evaluated using results obtained for a glass fibre plain woven fabric, and the importance of boundary conditions in the analysis of deformation mechanisms is highlighted. The simulation results show that the simple rotation boundary condition is adequate for predicting shear force at large deformations, with most of the energy being dissipated at higher shear angles due to yarn compaction. For small deformations, a detailed kinematic analysis is needed, enabling the yarn shear and rotation deformation mechanisms to be modelled accurately.
Delaunay refinement is a technique for generating unstructured meshes of triangles for use in interpolation, the finite element method, and the finite volume method. In theory and practice, meshes produced by Delaunay refinement satisfy guaranteed bounds on angles, edge lengths, the number of triangles, and the grading of triangles from small to large sizes. This article presents an intuitive framework for analyzing Delaunay refinement algorithms that unifies the pioneering mesh generation algorithms of L. Paul Chew and Jim Ruppert, improves the algorithms in several minor ways, and most importantly, helps to solve the difficult problem of meshing nonmanifold domains with small angles.Although small angles inherent in the input geometry cannot be removed, one would like to triangulate a domain without creating any new small angles. Unfortunately, this problem is not always soluble. A compromise is necessary. A Delaunay refinement algorithm is presented that can create a mesh in which most angles are 30° or greater and no angle is smaller than arcsin[(, where φ⩽60°is the smallest angle separating two segments of the input domain. New angles smaller than 30° appear only near input angles smaller than 60°. In practice, the algorithm's performance is better than these bounds suggest.Another new result is that Ruppert's analysis technique can be used to reanalyze one of Chew's algorithms. Chew proved that his algorithm produces no angle smaller than 30° (barring small input angles), but without any guarantees on grading or number of triangles. He conjectures that his algorithm offers such guarantees. His conjecture is conditionally confirmed here: if the angle bound is relaxed to less than 26.5°, Chew's algorithm produces meshes (of domains without small input angles) that are nicely graded and size-optimal.
The quality of a composite material produced using a textile reinforcement depends largely on the way the textile deforms during processing. To ensure the production of high quality parts and minimise costs in designing such parts it is necessary to develop methods to predict the deformations of textiles.
This thesis employs a multi scale modelling approach in predicting mechanical properties of textile fabrics. The three scales involved are the microscopic, mesoscopic and macroscopic. This thesis concentrates on the micro and mesoscopic scales leading to results applicable to the macroscopic scale.
At the microscopic scale fibres are modelled as individual entities and the interactions between these entities are modelled. In compaction of yarns, the contact between fibres and bending resulting from these contacts governs the force response. A numerical model is developed to simulate this behaviour and results are validated against experimental studies found in the literature. The numerical model is extended to the mesoscopic scale where the shear of a plain woven fabric consisting of low filament count yarns is modelled.
At the mesoscopic scale a large part of the work consists of characterising the geometry of textile fabrics. New and existing algorithms are combined together to form a consistent modelling approach. This work was performed in conjunction with the development of a software package named TexGen where these algorithms are implemented. The geometric models created by TexGen are then used to predict mechanical properties of textile unit cells using a finite element method which takes yarn properties as an input. Validation is performed for a series of woven fabrics subjected to compression and in-plane shear.
Permeability models based on the structure of the fabric are attractive for any design process to enhance the experimental permeability data. The authors have proposed two efficient numerical approaches to predict permeability based on the architecture of the fabric. The 'Stream Surface' method reduces the complexity of the flow domain by representing the 3D volumes with their 2D curvilinear mid-surfaces while retaining the 3D attributes. The second method, 'Grid Average', discretises the 3D domain into a 2D regular grid with weighted average permeabilities for the individual elements. Flow equations are solved for the reduced meshes generated from these two approaches to calculate the effective permeability. These approaches are applied firstly to a single tow model, and then to a 2×2 twill weave fabric, whereby the effects of in-plane shear and the statistical behaviour of fabrics is discussed. Comparisons with the computationally intensive CFD approach are favourable.
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Modelling mechanical performance including damage development for textile composites using a gridbased finite element method with adaptive mesh refinement
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on Textile Composites (TexComp 8), October 2006 Nottingham.
Modelling and simulations of fabrics using TexGen
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Lin, H., Sherburn, M., Long, A.C., Clifford, M.J., Rudd, C., 2009. Modelling and simulations
of fabrics using TexGen. In: Proceedings of the Fibre Society's Spring 2009 Conference.
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Meso-scale optimisation of 3D composites and novel preforming technologies
- M Matveev
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Matveev, M., Long, A.C., Brown, L.P., 2019. Meso-scale optimisation of 3D composites and
novel preforming technologies. In: 22nd International Conference on Composite Materials.
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Systematic predictive permeability modeling using commercial CFD and dedicated calculation method
- F Robitaille
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Robitaille, F., Wong, C.C., Long, A.C., Rudd, C., 2003. Systematic predictive permeability
modeling using commercial CFD and dedicated calculation method. In: Proceedings of the
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Permeability Prediction for Multi-Layer Textile Preforms
- C C Wong
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of Nottingham.
CFD flow simulation for impregnation of 3D woven reinforcements
- X S Zeng
- A Endruweit
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Zeng, X.S., Endruweit, A., Long, A.C., Clifford, M.J., 2010. CFD flow simulation for
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