Virtual Fibers Research Articles

Quasi-fiber scale modeling of 3D needled composites based on the virtual fiber embedded method

The objective of this paper is to propose a fiber-level modeling method for simulating tensile fracture of 3D needled composite. The complex fiber structure of 3D needled nonwoven preform is reproduced using virtual fibers. Micro-scale model of the composite is established by embedding virtual fiber structure into the voxel meshes of matrix material. The novel stiffness correction method is developed to solve the problems of volume redundancy and loss of reinforcing effect in transverse and shearing directions of the virtual fiber embedded element. The stiffness of the virtual fiber is not changed by the stiffness correction, ensuring that the stress of the virtual fibers is accurate. Damage initiation and evolution for fiber and matrix materials are characterized by the development of damage constitutive models. The tensile behavior of 3D needled composite is simulated. Influence of modeling parameters, including virtual fiber diameter and voxel mesh density on calculation accuracy is analyzed. Experimental tests are conducted to verify the simulation results. It is indicated that the predicted stress–strain response, strength, and fracture mode all agree well with the experimental results.

A microscale modeling method for predicting the compressive behavior of 3D needled nonwoven fiber preforms

The through-thickness compressive mechanism of 3D needled nonwoven fiber preforms is complicated due to the complex fiber structure and enormous fiber-to-fiber contacts. This work developed a microscale modeling method to predict compressive behavior of carbon fiber nonwoven preforms. A newly-developed virtual fiber is proposed based on the generalized beam elements, for which the low bending stiffness of the fiber is calibrated by experimental data and decoupled from the high tensile stiffness. The feasibility of the proposed virtual fiber method is demonstrated through a simulation example of three-point bending of 6 k carbon fiber yarn. Influence of modeling parameters including amount of virtual fibers in the yarn and the element length of virtual fibers on the simulations is analyzed. High precision model of 3D needled preform is then generated using the proposed virtual fiber method. Through-thickness and axial compressive deformations of the preform are simulated. The predicted load–displacement curves agreed well with the experimental results.

Investigation of forming process and deformation mechanisms of 3D warp interlock fabric

This article introduces a modeling method aimed at predicting the internal geometric structure of 3D warp interlock fabric. Inspired by the digital element method, the method employs truss elements to model the yarns as fiber bundles, and considers their material properties. This technique allows for predicting the microstructure of 3D woven fabric based on simple input characteristics. By varying the elastic modulus of virtual fibers, the friction coefficient between fibers, and the tension load at the ends of yarns, and designing compression molding molds to compress the fabric into shape, the virtual fiber fabric predicted the influence of variables on the fabric. The study found that the structure of the samples obtained through CT scanning is generally consistent with the structure of the virtual fiber fabric. The elastic modulus has a relatively minor impact on the fabric structure, whereas the friction coefficient and tension load significantly affect the cross-sectional shape of the yarns. During compression molding, deformation within the mold leads to interlayer fabric slippage and changes in the cross-sectional shape of the fabric. This suggests the feasibility and applicability of virtual simulation testing methods for analyzing the behavior of various types of 3D woven fabrics.

Supervised tractogram filtering using Geometric Deep Learning.

A tractogram is a virtual representation of the brain white matter. It is composed of millions of virtual fibers, encoded as 3D polylines, which approximate the white matter axonal pathways. To date, tractograms are the most accurate white matter representation and thus are used for tasks like presurgical planning and investigations of neuroplasticity, brain disorders, or brain networks. However, it is a well-known issue that a large portion of tractogram fibers is not anatomically plausible and can be considered artifacts of the tracking procedure. With Verifyber, we tackle the problem of filtering out such non-plausible fibers using a novel fully-supervised learning approach. Differently from other approaches based on signal reconstruction and/or brain topology regularization, we guide our method with the existing anatomical knowledge of the white matter. Using tractograms annotated according to anatomical principles, we train our model, Verifyber, to classify fibers as either anatomically plausible or non-plausible. The proposed Verifyber model is an original Geometric Deep Learning method that can deal with variable size fibers, while being invariant to fiber orientation. Our model considers each fiber as a graph of points, and by learning features of the edges between consecutive points via the proposed sequence Edge Convolution, it can capture the underlying anatomical properties. The output filtering results highly accurate and robust across an extensive set of experiments, and fast; with a 12GB GPU, filtering a tractogram of 1M fibers requires less than a minute.

FibrePlug – An ABAQUS plug-in for multi-scale modelling of textile composites

In this paper, a plug-in – FibrePlug – developed within the ABAQUSTM Simple GUI (RSG) and Fox GUI development environments is introduced. In contrast to traditional meso-scale modeling, FibrePlug provides an advanced user-friendly environment for simultaneously modeling fibers at micro- and meso-scales. With FibrePlug, the yarn level fabrics may be replaced by a specific user-defined number of representative bundles also known as virtual fibers. Further customizations, including the modification of the number of virtual fibers, are available within the GUI. In addition to the FibrePlug’s microscale modeling capabilities, readers are also introduced with the beam and solid element discretization features within the plug-in and their implications to computational efficiencies. The feature of the plug-in’s hybrid multi-scale model generation is also demonstrated. Furthermore, the accuracy of a uniform beam-element model generated with FibrePlug is validated by simple tensile tests performed with the 3D DIC equipment. Despite noticeable deviations in mechanical properties with respect to traverse direction, these properties are satisfactorily predicted along the loading direction.

A novel analysis method for mechanical properties of 3D needled twill composites based on virtual fibers

Compared with the traditional 3D needled composites with non-woven structure, the composites with twill layers have an extremely complex mesostructure. Three representative regions are divided based on the mesostructure observation of 3D needled twill composites. At the same time, the needling process of the 3D preform is simulated based on the digital element method, and the fiber deflection formulas in the needled region are built. Considering the distribution of different needling points, the periodic unit cell models of 3D needled twill composites that include three representative regions are established to predict the mechanical properties. It is verified that the results predicted by the proposed model agree well with the experimental data. Moreover, the effects of different needling angles and needling points on the mesostructure and mechanical properties of the composites are further studied, which helps guide the design and manufacture of 3D needled twill composites.

Experimental and numerical investigation of inter-ply shear behavior of 3D woven preform

The inter-ply shear deformation of 3D woven preform is inevitable in the forming process. Numerical simulation of the inter-ply shear process is therefore necessary to establish the high-precision fiber structure model and understand the deformation mechanisms. Here, a research strategy for inter-ply shear behavior of 3D woven preform is proposed. A new fixture is developed for inter-ply shear experiments. The unit cell model of the preform is generated using virtual fibers. Then the inter-ply shear test is replicated through numerical simulation. Micro-CT tests are carried out on the sample before and after inter-ply shear deformation, which confirmed that the virtual fiber model can accurately reproduce the fiber structure and micro-deformation. The virtual experiment results show that the macro-scale inter-ply shear deformation of the preform is composed of several yarn level deformations including the local tension, extrusion and buckling of warp/binder yarns, and slippage between warp and weft yarns.

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

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

Micro-scale modeling of 3D needled nonwoven fiber preforms

This paper proposes a numerical modeling method for generating the virtual fiber structures of 3D needled nonwoven preforms. Microstructures of the preforms are investigated using Micro-CT technology. Geometric parameters of the fibers, including length, orientation and aggregation are statistically analyzed. Then the virtual fibers are generated based on the statistical parameters. Each virtual fiber is a flexible chain connected by truss elements with very short length. After that the virtual fibers are assembled together and compressed to a certain thickness. Deformations and contacts of the virtual fibers are simulated by finite element method using an explicit dynamics algorithm. Finally, 3D needled nonwoven preforms are modeled by numerical simulation of the needling process. The virtual fiber structures and the Micro-CT images are found to be in excellent agreement with each other. The modeling method of this study would be helpful for understanding internal fiber structures of 3D needled nonwoven preforms and provides a good basis to analyze the permeability for resin flow and mechanical properties of the composites.

Multiscale numerical simulation of the forming process of biaxial braids during thermoplastic braid-trusion: Predicting 3D and internal geometry and fiber orientation distribution

Thermoplastic braid-trusion is a composite manufacturing process that combines braiding and pultrusion of hybrid yarns containing reinforcement and polymer fibers. During pultrusion, the melting of the polymer fibers leads to complex morphological changes at the macro, meso and micro scales. We introduce here a multiscale numerical simulation methodology to model this process. In this methodology, braided yarns are modeled as bundles of virtual discrete fibers using chains of truss elements. A thermoplastic composite braided rod was pultruded according to the simulated braid-trusion. During braid-trusion, it was observed that the braid architecture was significantly modified, which was reliably predicted by the model through macroscopic measurements of 7.6% pitch elongation, 44.0% diameter reduction, and 45.0% nominal angle reorientation. The model also predicts yarns’ cross-section area having high local fiber volume fraction of about 60% due to yarn compaction during pultrusion. These predictions of mesoscopic morphology and internal geometry are quantitatively validated using X-ray micro-computed tomography (CT) scans of the braid-truded rod. Three local fiber orientation distributions of the in-plane, out-of-plane, and with respect to the longitudinal braid axis are extracted using micro-scale analysis of virtual fibers. We found that a significant amount of fibers are oriented around specific radii ranging from 30–70% and 60–100% of the outer radius before and after pultrusion, respectively. By contrast, the local fiber orientation is uniformly distributed along the pitch length. The microscale model also shows considerable discrepancies between local and nominal braid angles.

Fiber-level numerical simulation of biaxial braids for mesoscopic morphology prediction validated by X-ray computed tomography scan

This paper proposes a modeling methodology to predict the 3D and internal geometry of biaxial braids. Inspired by the digital element approach, braided yarns are modeled as a bundle of virtual fibers. Here we adopt truss elements to a virtual fiber with actual material properties instead of beam elements that have limitations due to the beam flexural rigidity. The mesoscopic morphology prediction of two common braid patterns of the diamond (1/1) and regular (2/2) are validated by a comprehensive quantitative comparison with X-ray micro-computed tomography (CT) scans of braided carbon fibers. We find that the fiber-level frictional behavior is able to explain the jammed state of braids wherein the frictional dissipation energy quickly grows, while the braid has a stable elongation, diameter, and braid angle. Parametric studies illustrate how the increase in the coefficient of friction affects the yarn cross-sectional shape, whereas it has an insignificant effect on the crimp and jammed state of braids. Models also reveal that changing a wide range of the fiber modulus of elasticity hardly impacts the mesoscopic morphology and crimp of the braids.

Kinematic and mechanical response of dry woven fabrics in through-thickness compression: Virtual fiber modeling with mesh overlay technique and experimental validation

The through-thickness compressive behavior of fabric reinforcements is crucial in liquid composite molding manufacturing processes. Predictive simulations of the compressive response are thus necessary to enable a virtual processing workflow. These are complex however, as the compressive behavior of the reinforcement fabrics is non-linear. Altough virtual fiber modeling has proven to be a strong kinematical tool, it cannot predict the compressive response due to the lack of bending stiffness in the virtual fibers. Here, we describe a solution that enables predictive compressive simulations through hybrid virtual fibers. It is based on an overlay mesh-element technique, combining both (i) finite elements that determine the in-plane fiber properties as well as (ii) finite elements that determine out-of-plane fiber bending. Using these hybrid virtual fibers, the through-thickness compression of a twill woven fabric ply is simulated and experimentally validated using both μCT-based as compliance-based measurements. Excellent agreement between simulation and experiment is obtained for the right set of input parameters.

Modeling method of irregular cross section annular axis braided preform based on finite element simulation

The irregular cross section annular axis braided preform is modeled by using finite element simulation instead of geometric modeling. The braiding process is simulated by using a finite element software to obtain the yarn path. And the braided preform is modeled by using nine virtual fibers to form irregular cross section shape of yarn. Meanwhile, a modified vertical braiding machine is used to braid the actual preform, to compare with results from the simulation model. The results show that the simulation model is consistent with the actual braided preform, braiding angle is about 36°, and yarn spacing is about 6 mm. The finite element method can predict the yarn path more accurately without the need of complex analysis and derivation, especially when the irregular mandrel is used for braiding. In addition, the cross-section shape of yarn composed of virtual fibers can be used to achieve a more realistic simulation result. FEM is an efficient simulation method, and can also provide an effective basis in studies of the actual cross-sectional shape of yarn and the properties of its composite reinforcements.

Optical Dual Laser Based Sensor Denoising for OnlineMetal Sheet Flatness Measurement Using Hermite Interpolation.

Flatness sensors are required for quality control of metal sheets obtained from steel coils by roller leveling and cutting systems. This article presents an innovative system for real-time robust surface estimation of flattened metal sheets composed of two line lasers and a conventional 2D camera. Laser plane triangulation is used for surface height retrieval along virtual surface fibers. The dual laser allows instantaneous robust and quick estimation of the fiber height derivatives. Hermite cubic interpolation along the fibers allows real-time surface estimation and high frequency noise removal. Noise sources are the vibrations induced in the sheet by its movements during the process and some mechanical events, such as cutting into separate pieces. The system is validated on synthetic surfaces that simulate the most critical noise sources and on real data obtained from the installation of the sensor in an actual steel mill. In the comparison with conventional filtering methods, we achieve at least a 41% of improvement in the accuracy of the surface reconstruction.

Mechanical modeling of textile composites using fiber-reinforced voxel models

The fiber-reinforced voxel modeling technique is proposed to analyze the stress field and predict stiffness properties of textile composites. The textile reinforcements and matrix materials are modeled by virtual fibers and 3D voxel elements separately. Then the virtual fibers are “inserted” into the background voxel elements to construct the fiber-reinforced voxel elements. Stiffness properties of each fiber-reinforced voxel element are determined using volume average method based on the volume fraction and orientation of the virtual fibers it occupies. Geometry modeling and meshing of the complex reinforcements and matrix regions are avoided. As the reinforcements are generated in quasi-fiber scale, contact interactions and compaction deformations of the yarns can be modeled with high fidelity. A composite model containing one crimped yarn is used to verify the proposed method by comparing the calculating results of the fiber-reinforced voxel and traditional meso-scale models. The effect of voxel meshing density and virtual fiber radius on the simulation accuracy is also analyzed. Mechanical modeling of a multiply plain weave composite is performed by this model. Influence of nesting and compaction of the plies on the stress field can be fully characterized.

Micro-scale modeling of textile composites based on the virtual fiber embedded models

This paper presents a novel modeling method to analyze the stress and strain fields of the textile composites. Firstly, the fiber reinforcements are generated using virtual fibers. Then the virtual fibers are embedded into the background solid meshes to model the composites. Compared with traditional meso-scale finite element models, the proposed method simplifies the geometry modeling and meshing processes of the complex fiber structures within the composites. Compaction deformations of the yarns can be modeled with high fidelity using virtual fibers. A plain composite unit cell model is used to demonstrate the accuracy of the proposed method. Simulation results of the virtual fiber embedded models agree well with that of the traditional finite element models. The proposed method is employed to predict the mechanical response of a four-layer plain composite under tensile load. The calculated surface strain field is consistent with the DIC measurement. Effect of nesting between the plain layers on the stress and strain fields of the composite is investigated.

Experimental and numerical investigation of the needling process for quartz fibers

This paper investigates the deformation and damage of quartz preforms during the needling process. Effect of needling position and fabric thickness on the resistance force of the needle are experimentally researched. A numerical methodology based on the concept of virtual fibers is proposed to establish the geometry models of 2D broken twill and nonwoven fabrics. Then the needling process of the fabric plies is simulated by finite element method using an explicit dynamics algorithm. Deflection, stretch and breakage of the fibers are analyzed. The simulated fiber architectures of the needling positions are fairly close to the practical observations. Resistance force of the needling process can be predicted with satisfactory accuracy. The aim of the proposed approach is to generate the virtual fiber structure of needled preforms and obtain the effect of needling process on the fiber damage. This approach would be helpful for designing low-damage preforms and improve the mechanical properties of needled composites.

Differential involvement of corticospinal tract (CST) fibers in UMN-predominant ALS patients with or without CST hyperintensity: A diffusion tensor tractography study.

Diagnosis of amyotrophic lateral sclerosis (ALS) depends on clinical evidence of combined upper motor neuron (UMN) and lower motor neuron (LMN) degeneration, although ALS patients can present with features predominantly of one or the other. Some UMN-predominant patients show hyperintense signal along the intracranial corticospinal tract (CST) on T2- and proton density (PD)-weighted images (ALS-CST +), and appear to have faster disease progression when compared to those without CST hyperintensity (ALS-CST −). The reason for this is unknown. We hypothesized that diffusion tensor tractography (DTT) would reveal differences in DTI abnormalities along the intracranial CST between these two patient subgroups. Clinical DTI scans were obtained at 1.5T in 14 neurologic controls and 45 ALS patients categorized into two UMN phenotypes based on clinical measures and MRI. DTT was used to quantitatively assess the CST in control and ALS groups.DTT revealed subcortical loss ('truncation') of virtual motor CST fibers (presumably) projecting from the precentral gyrus (PrG) in ALS patients but not in controls; in contrast, virtual fibers (presumably) projecting to the adjacent postcentral gyrus (PoG) were spared. No significant differences in virtual CST fiber length were observed between controls and ALS patients. However, the frequency of CST truncation was significantly higher in the ALS-CST + subgroup (9 of 21) than in the ALS-CST − subgroup (4 of 24; p = 0.049), suggesting this finding could differentiate these ALS subgroups. Also, because virtual CST truncation occurred only in the ALS patient group and not in the control group (p = 0.018), this DTT finding could prove to be a diagnostic biomarker of ALS. Significantly shorter disease duration and faster disease progression rate were observed in ALS patients with CST fiber truncation than in those without (p < 0.05). DTI metrics of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were also determined in four regions of interest (ROIs) along the CST, namely: cerebral peduncle (CP), posterior limb of internal capsule (PLIC), centrum semiovale at top of lateral ventricle (CSoLV) and subcortical to primary motor cortex (subPMC). Of note, FA values along the left hemisphere virtual CST tract were significantly different between controls and ALS-CST + patients (p < 0.05) only at the PLIC level, but not at the CSoLV or subPMC level. Also, no significant differences in FA values were observed between ALS subgroups or between control and ALS-CST − groups (p > 0.05) in any of the ROIs. In addition, comparing FA values between ALS patients with CST truncation and those without in the aforementioned four ROIs, revealed no significant differences in either hemisphere. However, visual evaluation of DTT was able to identify UMN degeneration in patients with ALS, particularly in those with a more aggressive clinical disease course and possibly different pathologic processes.

Signal Processing for Fiber Optic Systems

This paper reviews the digital signal processing (DSP) methods used in coherent fiber optic communication systems. With the advances in high speed DSP, linear impairments such as chromatic dispersion (CD) and polarization mode dispersion (PMD) can be compensated for using fixed/adaptive equalizers. It is also possible to compensate for the interplay between dispersion and nonlinearity by digital back propagation (DBP), in which the virtual fibers whose signs of dispersion, loss and nonlinear coefficients are opposite of those of the transmission fiber, are realized in the digital domain by numerically solving the nonlinear Schrӧdinger equation (NLSE). DSP equalization enhances the transmission performance and error-free reach of coherent fiber optic systems significantly. Keywords: Chromatic dispersion, coherent communications, digital back propagation, digital signal processing, fiber optic communications, nonlinear fiber optics, perturbation techniques, polarization mode dispersion.

A Hyperelastic Constitutive Model for Chain-Structured Particle Reinforced Neo-Hookean Composites

A hyperelastic constitutive model is proposed to predict the mechanical behavior of macroscopically transversely isotropic composites containing chain-structured particles. In this model, each particle chain is treated as a “virtual fiber” and the composite is modeled as a virtual fiber reinforced composite. When the particles and the matrix are both neo-Hookean materials, the virtual fiber, which is a particle-reinforced composite itself, is modeled as a neo-Hookean material and its effective stiffness is predicted by the classical three phase model. A simple method is developed to construct the virtual fibers and the corresponding virtual fiber-reinforced model is derived for the chain-structured particle reinforced composite. The representative volume element models are created to verify the virtual fiber transformation and the constitutive model numerically. The effects of the microstructure, the disturbance of particle locations, and the choice of the virtual fibers are investigated. The numerical results show that the proposed virtual fiber reinforced composite model can well predict the mechanical responses of the composites with chain-structured particles.