Fiber Orientation Research Articles

Evaluation of Frictional Influence and Thermal Analysis of Flexible Paper‐Based Materials Used in the Vertical Form–Fill–Seal Process: An Experimental Study

ABSTRACTThis study evaluated the frictional behaviour of flexible polymer‐coated and dispersion‐coated materials used in vertical form–fill–seal (VFFS) machines. A laboratory‐scale friction measurement device was developed to investigate the relationship between different surface topographies, roughness and frictional properties. Furthermore, surface roughness, contact angle and surface energy of the material were analysed and a microscopic analysis was performed to further understand the effect of material properties on friction. Thermal camera analysis was performed to measure the temperature changes within the material during the film‐transport stage of the VFFS machine. The friction measurement results indicated that the sliding direction did not affect the static and kinetic coefficients of friction. The significant influence of friction on the surface topography of the plate (forming shoulder and tube) was particularly evident. Some materials experienced the stick–slip phenomenon during sliding, depending on the surface type. Teflon tape, which is commonly used in the forming tubes of VFFS machines, exhibited the lowest coefficient of friction. Thermal camera analysis revealed that polymer‐coated paper materials generated more heat than dispersion‐coated papers during VFFS trials and thermoplastic films generated the least heat. No clear relationship between the surface roughness of the paper, fibre orientation, surface energy and friction coefficient was noted. Furthermore, paper‐based materials exhibited a higher coefficient of friction, which is possibly related to the dispersion components of surface energy. The findings of this study provide additional knowledge for designing the forming tube, shoulder geometry and surface plate to minimize the occurrence of defects, such as wrinkles, in paper‐based packages.

Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results than standard methods such as Constrained Spherical Deconvolution and two state-of-the-art deep learning methods. For voxels with one and two fibers, respectively, our method shows an agreement rate in terms of the number of fibers of 77.5% and 22.2%, which is 3% and 5.4% higher than other deep learning methods, and an angular error of 10° and 20°, which is 6° and 5° lower than other deep learning methods. To determine baselines for assessing the performance of our method, we compute agreement metrics using densely sampled newborn data. Moreover, we demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical external datasets of newborns and fetuses. We validate fetal FODs, successfully estimated for the first time with deep learning, using post-mortem histological data. Our results show the advantage of deep learning in computing the fiber orientation density for the developing brain from in-vivo dMRI measurements that are often very limited due to constrained acquisition times. Our findings also highlight the intrinsic limitations of dMRI for probing the developing brain microstructure.

Buckling optimization of variable-stiffness composite plates with two circular holes using discrete Ritz method and potential flow

Potential flow around two equal-radius cylinders is derived analytically and applied to generate the curvilinear fiber path of variable-stiffness composite (VSC) plates with two circular holes. As complex variable theory and conformal mapping are used to generate the potential flow around two equal-radius cylinders, the location and size of the two equal-radius circular holes are arbitrary. By changing the angle of incoming flow, the global fiber angle of a variable-stiffness lamina can be simulated and the local fiber orientation angle at any point is determined by the global potential flow field. Buckling performance of variously-shaped VSC plates with two circular holes are investigated via a novel numerical method − discrete Ritz method (DRM). DRM combines the extended interval integral, Gauss quadrature, and variable stiffness within a rectangular domain and builds a discrete energy system to simulate the plate, which allows the geometric boundaries of the plate to vary. The strain energy of a plate is modeled in the rectangular domain, discretized using Gauss points, and is characterized by variable stiffness, which characterizes both the material distribution and plate geometry simultaneously. After that, a three-dimensional sampling optimization (3DSO) method is adopted to optimize the curvilinear fiber configurations of VSC plates, and its buckling performances are compared with those of constant stiffness composites (CSC) with optimal straight fibers. Significant improvements on load-carrying capacity can be achieved compared to straight ones, demonstrating that using potential flow is one of the most efficient way to generate curvilinear optimal fiber path with maximum load-carrying capacity for VSC plates with material discontinuity. Moreover, DRM exhibits good precision and stability for buckling analysis of VSC plates with complex geometries.

Evaluating the optimum abrasive water jet machinability for CARALL composites with various fiber orientations

AbstractCarbon Fiber Reinforced Aluminum Laminated (CARALL) composites are widely used in aircraft structures due to their ability to be produced in different shapes with desired properties and their high impact resistance properties. As with other layered composite materials, processing of CARALL composites by conventional manufacturing methods results in many damage mechanisms such as fiber breakage, deformation in the hole region, stress concentration, resin‐fiber separation and microcracks. One of the modern manufacturing methods, Abrasive Water Jet (AWJ), is a processing method in which the material is removed by abrasion and almost any material can be cut without thermal degradation. There are no experimental studies in the literature on the drilling of CARALL composites by modern manufacturing methods. The aim of this study is to investigate the impact of machining parameters on the output variables (kerf taper angle (K), roundness error (Re) and material removal rate (MRR)) as well as the effect of fiber orientation on the drilling of CARALL composites with different fiber orientations on an AWJ machine. PROMETHEE‐GAIA weighted by Entropy Weighting Method were used to ascertain the optimum levels of control factors. CARALL composites with different fiber orientations were drilled with an 8 mm diameter AWJ with three different water pressures, three different nozzle feed rates. With PROMETHEE‐GAIA multi‐criteria optimization method, the optimum levels of the factors that provide both minimum Re and K values and maximum MRR value were obtained with twill woven material, 1680 mm/min feed rate and 1680 bar water pressure.Highlights CARALL composite materials with two different fiber orientations (twill weave and UD) were used. CARALL composite materials were drilled at different machining parameters. Abrasive water jet was used in drilling experiments. Optimum drilling parameters were determined to achieve minimum roundness error, minimum kerf angle and maximum material removal rate. PROMETHEE‐GAIA was used as a multi‐criteria decision‐making method.

Effect of steel fibre with different orientations on mechanical properties of 3D-printed steel-fibre reinforced concrete: Mesoscale finite element analysis

It is widely recognized that steel fibres exhibit directional distribution during the preparation of 3D-printed steel fibre reinforced concrete (SFRC). The degree of fibre orientation varies due to several factors, such as nozzle size and layer height. This variation in fibre orientation range may result in different mechanical performance exhibited by 3D-printed SFRC at hardened state. To explore the relationship between steel fibre orientation and the mechanical properties of 3D-printed SFRC at hardened state, this study firstly establishes three-dimensional mesoscale finite element models based on the distribution of fibres in 3D-printed SFRC. The steel fibre and matrix work together through a mechanism for fluid-structure interaction between models. Then, compares the simulation results with experimental data to verify the accuracy of the models. After that, different steel fibre distribution orientations were set, and parametric analysis was conducted for the compressive and tensile loading conditions to explore the effects of fibre orientation on the damage mode and strength of 3D-printed SFRC. The results indicate that 3D-printed SFRC exhibits different damage modes with varying steel fibre orientation ranges. Additionally, the strength of 3D-printed SFRC varies in steel fibre orientation range and exhibits anisotropic characteristics. This study provides a theoretical basis for improving and controlling the performance of 3D-printed SFRC in future engineering applications.

Quick insight into the dynamic dimensions of 4D printing in polymeric composite mechanics

Abstract 4D printing is recognised for its numerous potential applications due to its reaction towards stimulus factors. However, limited research has focused on what, why, and how this stimulus-response works. This study reveals the mechanism used to stimulate 4D printing reactions. Complex printing via design structure and mechanical control on fibre orientations are promising techniques compared with chemical modifications, which are difficult to control, particularly for commercialisation.

Determination of lubricating behavior of resin during the sliding process of unidirectional prepreg

Abstract In this paper, the lubrication behavior of resin during the molding process of unidirectional prepreg materials was scrutinized using a custom-made device. The thickness of the resin between prepregs under various conditions was calculated using Inverse Hydrodynamic Lubrication (IHL) theory to elucidate the lubrication mechanism. This calculation was confirmed by examining the surface morphologies of the prepreg and employing Digital Image Correlation (DIC) techniques for validation. Furthermore, the effect of unidirectional fiber orientation on the process of inter-ply sliding was quantitatively analyzed through the combined roughness. The study showed that factors such as sliding velocity, normal pressure, and fiber orientation play a key role in the lubrication mechanism. The lubrication behavior of unidirectional prepreg transformed to mixed lubrication under specific conditions. The results in our study of the lubrication mechanism have significant implications for the refinement of molding process and the enhancement of numerical simulations of unidirectional prepregs.

Non-Coagulant Spinning of High-Strength Fibers from Homopolymer Polyacrylonitrile Synthesized via Anionic Polymerisation.

The rheological properties, spinnability, and thermal-oxidative stabilization of high-molecular-weight linear polyacrylonitrile (PAN) homopolymers (molecular weights Mη = 90-500 kg/mol), synthesized via a novel metal-free anionic polymerization method, were investigated to reduce coagulant use, enable solvent recycling, and increase the carbon yield of the resulting carbon fibers. This approach enabled the application of the mechanotropic (non-coagulating) spinning method for homopolymer PAN solutions in a wide range of molecular weights and demonstrated the possibility of achieving a high degree of fiber orientation and reasonable mechanical properties. Rheological analysis revealed a significant increase in solution elasticity (G') with increasing molecular weight, facilitating the choice of optimal deformation rates for effective chain stretching prior to strain-induced phase separation during the eco-friendly spinning of concentrated solutions without using coagulation baths. The possibility of collecting ~80 wt% of the solvent at the first stage of spinning from the as-spun fibers was shown. Transparent, defect-free fibers with a tensile strength of up to 800 MPa and elongation at break of about 20% were spun. Thermal treatment up to 1500 °C yielded carbon fibers with a carbon residue of ~50 wt%, in contrast to ~35 wt% for industrial radically polymerized PAN carbonized under the same conditions.

Planar delamination behaviour of CFRP panels under quasi-static out-of-plane loading

In this study, a novel experimental approach was devised to investigate shear dominant and combined opening-shear planar delamination behaviours in composite laminates subjected to quasi-static out-of-plane loading. The patterns of planar delamination growth were depicted through different inspection techniques, including digital image correlation (DIC), C-scan, and microscopic observation. The artificially embedded delamination propagated in the direction parallel to the fibre orientation of the layer above the mid interface, but migrated to an upper interface in the direction transverse to the directing ply. A continuous stiffening process was recognized with increasing delamination area. Furthermore, a numerical analysis based on virtual crack closure technique (VCCT) indicated that the local mode II was dominant for delamination growth, while the local mode III triggered delamination migration.

Controlled Stiffness of Direct-Write, Near-Field Electrospun Gelatin Fibers Generates Differences in Tenocyte Morphology and Gene Expression.

Tendinopathy is a leading cause of mobility issues. Currently, the cell-matrix interactions involved in the development of tendinopathy are not fully understood. In vitro tendon models provide a unique tool for addressing this knowledge gap as they permit fine control over biochemical, micromechanical, and structural aspects of the local environment to explore cell-matrix interactions. In this study, direct-write, near-field electrospinning of gelatin solution was implemented to fabricate micron-scale fibrous scaffolds that mimic native collagen fiber size and orientation. The stiffness of these fibrous scaffolds was found to be controllable between 1 MPa and 8 MPa using different crosslinking methods (EDC, DHT, DHT+EDC) or through altering the duration of crosslinking with EDC (1 h to 24 h). EDC crosslinking provided the greatest fiber stability, surviving up to 3 weeks in vitro. Differences in stiffness resulted in phenotypic changes for equine tenocytes with low stiffness fibers (∼1 MPa) promoting an elongated nuclear aspect ratio while those on high stiffness fibers (∼8 MPa) were rounded. High stiffness fibers resulted in the upregulation of matrix metalloproteinase (MMPs) and proteoglycans (possible indicators for tendinopathy) relative to low stiffness fibers. These results demonstrate the feasibility of direct-written gelatin scaffolds as tendon in vitro models and provide evidence that matrix mechanical properties may be crucial factors in cell-matrix interactions during tendinopathy formation.

Correction: Comparison of classical beam theory and finite element modelling of timber from fibre orientation data according to knot position and loading type

Correction: Comparison of classical beam theory and finite element modelling of timber from fibre orientation data according to knot position and loading type

The effects of ply clustering positions and orientations on multi‐directional composite laminates' low velocity impact resistance

AbstractIn this paper, nine different carbon fiber laminates containing clusters are designed using the ant colony ACO algorithm, which have similar equivalent bending stiffnesses and B‐matrices, with the differences being the fiber orientation of the clusters and the position of the clusters in the laminates. The dynamic mechanical characterization of laminates for low velocity impact (LVI) at three different energies was carried out by means of a falling weight impact experiment. The experimental results show that the main form of failure of the laminate is delamination failure at low energy impacts, and shear fracture becomes more and more obvious with the elevation of the impact energy, which was observed in detail by the stereo microscope and electron microscope. The damage area of the laminate and the force and displacement curves after 30 J energy impact were compared by x‐ray scanning to derive the effects of the angle of the ply cluster fibers and the different positions of the ply clusters in the laminate on the impact resistance of the laminate. In conclusion, when designing the laminate, consideration should be given to designing 45° clusters on the impacted side and 90° clusters in the middle layer of the laminate to obtain the best impact resistance.Highlights Designed 9 types of laminates with different laminate structures based on ACO algorithm. Different laminates have similar equivalent bending stiffnesses and the B matrix as close to 0 as possible. LVI tests at three energies were performed on 9 types of laminates. The effects of different orientations of the clusters and the position of the clusters in the laminate on the impact resistance of the laminate were investigated.

Simultaneous influence of strain rate and moisture on the anisotropic mechanical behavior of direct compounded compression molded PA6/Glass LFTs

Fibre-reinforced polymer composites are an increasingly critical long-term solution for lightweighting the transportation sector, therefore, a comprehensive understanding of their mechanical behavior under varying environmental conditions and loading rates is critical. This study investigated the tensile properties and behavior of a direct-compounded compression-molded Polyamide6 (PA6)/glass long fibre thermoplastic (LFT-D) material, specifically examining the influence of moisture content and intermediate tensile loading rates, up to 150 s−1. This range is of significance to the transportation industry and is highly desirable for engineering design since data in the current literature is limited. Dried and undried samples were also examined at four distinct material orientations: 0°, +45°, ˗45°, and 90°. The results confirmed that moisture presence significantly altered the mechanical properties of PA6/Glass LFT material under quasi-static loading rates; in contrast, its effects were negligible under dynamic loadings. Notably, the material exhibited significant strain rate sensitivity within the range of 0.0001 s−1 to 150 s−1. In the 0° material direction, with higher fibre orientation distribution, the undried materials demonstrated a substantial increase of 93% in Young's modulus and 172% in ultimate tensile strength while the complementary dried samples displayed increases of 76% and 97%, respectively. Tensile strength reached 293.8 MPa and 276.7 MPa for undried and dried samples, respectively, in this particular material direction. However, the strain at failure remained consistent at approximately 4% for undried samples and 3% for dried samples, resulting in an increase in tensile toughness by 292% (up to 6.9 MPa) for undried samples and 114% (up to 4.7 MPa) for dried samples.

A highly parallel algorithm for simulating the elastodynamics of a patient-specific human heart with four chambers using a heterogeneous hyperelastic model

In this paper a highly parallel method is developed for simulating the elastodynamics of a four-chamber human heart with patient-specific geometry. The heterogeneous hyperelastic model is discretized by a finite element method in space and a fully implicit adaptive method in time, and the resulting nonlinear algebraic systems are solved by a scalable domain decomposition algorithm. The deformations of the cardiac muscles are quite complex due to the realistic geometry, the heterogeneous hyperelasticity of the cardiac tissue, and the myocardial fibers with active stresses. Moreover, the deformations in different chambers and at different phases of the cardiac cycle are very different. To simulate all the muscle movements including the atrial diastole, the atrial systole, the isovolumic contraction, the ventricular ejection, the isovolumic relaxation, and the ventricular filling, the temporal-spatial mesh needs to be sufficiently fine, but not too fine so that the overall computing time is manageable, we introduce a baseline mesh in space and a two-level time stepping strategy including a uniform baseline time step size to obtain the desired time accuracy and an adaptive time stepping method within a baseline time step to guarantee the convergence of the nonlinear solver. Through numerical experiments, we investigate the performance of the proposed method with respect to the material coefficients, the fiber orientations, as well as the mesh sizes and the time step sizes. For an unstructured tetrahedral mesh with more than 200 million degree of freedoms, the method scales well for up to 16,384 processor cores for all steps of an entire cardiac cycle.

Developing poplar wood into a green structure-decoration integrated material for prefabricated wooden building application

Fast growing poplar wood poses significant challenges including low mechanical strength, poor dimensional stability and weak texture, limiting its direct application in the field of building structures and decoration. We treated poplar wood using compression, digital printing and waterproofing techniques to develop a green structure-decoration integrated material. The compression treatment significantly improved the wood density, fiber orientation and surface smoothness. At a compression ratio of 60 %, poplar veneer demonstrates remarkable improvements in modulus of elasticity (MOE), modulus of rupture (MOR) and surface smoothness, with increases of 222.53 %, 233.53 % and 93.20 %, respectively, compared to uncompressed wood. Notably, this compression treatment reduces the surface roughness of poplar to 0.75 μm, meeting the flatness requirements for digital printing. Consequently, clear textures and vibrant colors are directly printed onto the flat surface of compression-densified poplar wood, eliminating the need for traditional surface sanding pre-treatment process, and accordingly improving the efficiency of the material preparation. Furthermore, a final waterproofing emulsion spraying treatment creates a dense micro/nanoscale hierarchical structure on the surface, enabling the compression-densified poplar wood samples to achieve MOE and MOR of 14.15 GPa and 123.00 MPa respectively, even after water absorption and re-dried processes. These values consistently exceed the standard value of MOE (12.50 GPa) and MOR (35.00 MPa) for the highest grade (TCT40) specified in GB50005-2017, indicating significantly improved structural stability. The structure-decoration integrated materials developed in this study offer high strength and dimensional stability, making them promising candidates for high value utilization in prefabricated wooden buildings.

Growth Dynamics of Flexor Muscle Fibers in Developing Male White Leghorn Chicks

The study examines the relationship between fiber orientation, functional activity, and growth dynamics in the flexor muscle of a male white Leghorn chick. It tests three hypotheses: similar histochemical fiber typing in muscle mass, distribution patterns influenced by species' functional activities, and fiber growth dynamics related to somatic growth rate. The study confirmed the hypothesis that all three basic fiber types (red, pink, and white) grow exclusively through hypertrophy. True hyperplasia was not evident in any age group, possibly in the late embryonic stage. Some cases of pink and white fibers showed splitting into smaller ones. All three basic fiber types grew by hypertrophy, regardless of location or functional activity. Muscle fiber growth in this muscle mass was directly related to the chick's somatic growth rate.

A 3D multi-phase-field model for orientation-dependent complex crack interaction in fiber-reinforced composite laminates

We formulate a 3D multi-phase field model to simulate bulk and interfacial fracture in fiber-reinforced composites. The purpose of this study is to predict the complex crack interaction between the interlaminar and intralaminar fracture in FRPCs. For that, the discrete crack and the sharp interface are both smeared using the phase-field approach. A second-order anisotropic tensor is incorporated in the elastic as well as the fracture surface energy to promote direction-dependent crack growth. The interface constitutive behavior is represented by the uncoupled 3D traction–separation laws—in exponential and bi-linear form. The proposed model captures the complicated failure phenomena in FRPCs such as matrix damage, interfacial delamination, and their interactions for different configurations of lamina with different fiber orientations and fracture energies. This model’s capability is further illustrated to study the three common modes of fracture i.e. modes I, II, and III, in 3D FRPC laminates where the crack impinges on the interface. Finally, the obtained framework is validated by two benchmark problems including the mode I and mode II delamination test, and is compared against experimental data reported in the literature.

Automatic reconstruction of closely packed fabric composite RVEs using yarn-level micro-CT images processed by convolutional neural networks (CNNs) and based on physical characteristics

Micro-CT scanning is an advanced technique to reconstruct inner architectures for RVEs of fabric composites. Currently, however, there exist few automatic approaches to separate closely packed yarns in the micro-CT images with economical resolution that can only identify yarns but not individual fibers. To tackle this issue, an innovative method has been developed in this work to identify cross-section area of the yarns via deep-learning-based image segmentation, and then reconstruct 3D geometry model of the composites containing local fiber orientations. The image segmentation was achieved through semantic segmentation by U-Net with validation accuracy of 87 % counted by mIOU and object detection by YOLO v8 with validation accuracy of 99.5 % counted by mAP50. Micro-CT slices with different morphological characteristics were divided into three groups via a ResNet50-based image classification network and selected in ratio to form the training datasets for U-Net and YOLO v8 with high representativity and efficiency. Extraction of individual cross-sections of weft and warp yarns were conducted only using the micro-CT scanning from one angle of view to reduce scanning cost and yarn-to-yarn penetration error. An algorithm considering physical constraints of the yarns was also completed to estimate local fiber orientations with maximum error of 18.065°, nearly 50 % smaller than the existing method.

Axial compression behavior of concrete-filled prefabricated aligned steel fiber UHPC tubes

This study presents an innovative composite column system featuring exceptional ductility and versatility, suitable for replacing traditional concrete columns or UHPC composite columns. The composite column, comprised of concrete-filled aligned steel fiber ultra-high performance concrete (UHPC) tubes (ASFUTs), offers superior mechanical properties. Apart from its function as a formwork, the ASFUT provides exceptional rigidity and lateral confinement capabilities, enabling it to withstand substantial axial forces directly. Initially, steel fibers were aligned using an electromagnetic field. Computed Tomography (CT) imaging elucidated an average inclination angle of 16.36° between the fibers and the circumference of ASFUT sections. Compared to conventional UHPC, aligned steel fiber UHPC demonstrates an average 9.1 % increase in compressive strength and an average 129.67 % increase in maximum equivalent tensile. This enhancement can be attributed to the improved fiber bridging effect resulting from the orientation of fibers. Then, the mechanical properties of the concrete-filled ASFUT columns were evaluated by axial compression testing of eight specimens with different fiber contents, shapes, and orientations. The findings indicate that the ASFUTs outperform conventional concrete-filled UHPC tubes, exhibiting notable enhancements across various performance metrics. Specifically, at a fiber volume fraction of 1 %, the concrete-filled ASFUT exhibits a compressive strength, elastic modulus, ductility, and energy dissipation capacity that are 1.12 times, 1.03 times, 1.25 times, and 1.54 times respectively, in comparison to conventional concrete-filled UHPC tubes. Finally, an advanced predictive model for estimating the axial bearing capacity of ASFUT concrete columns was proposed, offering valuable insights for structural design optimization and widespread implementation.

Predicting the fiber orientation of injection molded components and the geometry influence with neural networks

The injection molding simulation of short fiber reinforced plastics (SFRP) is time consuming. However, until now it is necessary for predicting the local fiber orientation, to optimize the molding process and to predict the mechanical behavior of the material. This research presents the capabilities of artificial neural networks (NN) in predicting fiber orientation tensor (FOT) during injection molding processes, with a focus on enhancing computational efficiency compared to traditional simulation methods. Three NN architectures are compared based on simulated injection molded plates, with the goal of predicting the effect of the plate geometry on the local fiber orientation. Results indicate that NN outperform the baseline assumption of aligned fibers and demonstrate significant potential for accurate FOT prediction. The computational efficiency of NN, especially during the prediction phase, showcases a reduction in processing time by a factor of 104 compared to traditional simulation methods. This research lays a foundation for further exploration into the feasibility of NN in partly replacing time-consuming simulations for practical applications in injection molding processes.