Random Distribution Of Fibers Research Articles

Multiscale simulation and experimental studies on modal damping of ultra‐thick CFRP laminates

AbstractThe vibration characterization of ultra‐thick laminates widely used in aerospace and marine industries was different from that of thin laminates. However, modal testing and simulation methods were generally limited to relatively thin laminates. To explore the vibration behavior of ultra‐thick laminates, a novel multiscale simulation technology based on the representative volume modal strain energy (RVMSE) method is presented for predicting modal damping in this paper. The adaptive Greedy‐Based Generation (GBG) algorithm is used to create a 3D random distribution of fibers for composites. Modal shape information of the structure is obtained according to the Lanczos algorithm, which is used as an input parameter for the microscopic model. This is followed by homogenization based on the volumetric analysis performed on representative volume elements (RVEs) to determine the strain energy in six directions. The calculation of modal damping is performed by using the modal strain energy (MSE) method and the damping properties of the six directions. The fast rate of convergence and high accuracy of the method are demonstrated through different examples. The vibration response predictions produced by novel RVMSE methodology are shown to closely match experimental measurements, providing scope to expand the application of this approach to more complex, ultra‐thick laminate components.Highlights The RVMSE method uses a higher level of homogenization to overcome the limitations of the traditional MSE method for calculating the damping of ultra‐thick CFRP laminates. The modal parameter error is controlled to less than 10%, and the experimental results fill the gap of the damping data of ultra‐thick CFRP structure. The proposed RVMSE model improves the accuracy of dynamic response prediction for ultra‐thick laminates.

Properties of a steel fiber reinforced cementitious composite stool with digitally distributed steel fibers

This study aims to maximize the reinforcement of steel fibers in cementitious composite structural members. A 3D-printing stool was chosen as a case study. The orientation of the steel fibers is designed to be parallel to the direction of the tensile stress, and the volume fraction of steel fibers everywhere meets the tensile requirements, which is defined as digitally distributed steel fiber reinforced cementitious composite (DD-SFRC) stool. The DD-SFRC stool was prepared using magnetic field aligning and 3D-printing, to control the volume fraction and orientation of steel fibers in the stool. The results show that digitally distributed steel fibers reinforce the mechanical properties of the stool more effectively, in terms of ultimate load, energy absorption capacity, joint ductility, and the width of the crack, compared with that of the stool with random and aligned steel fiber distribution. The methodology of design and approach of preparation of DD-stool are presented, which are valid and applicable to other structures in either laboratory or practice.

A micromechanical study on shear performance of unidirectional composites with randomly distributed fibers in the transverse cross‐section

AbstractThe properties of unidirectional (UD) composites has been investigated by analyzing their elastic and strength characteristics under shear loading. The UD fiber‐reinforced polymer (FRP) composites usually consist of fibers randomly dispersed throughout the cross‐section in the transverse direction which is generally not accounted for. A micromechanical model based on finite element analysis (FEA) approach is utilized here to examine these properties. The study begins by identifying micro scale unit cells or repetitive unit cells (RUCs) at the micro scale, as well as representative volume elements (RVEs). The distribution of fiber volume fraction (Vf) varies among various micro scale unit cells positioned in the transverse cross‐section. The elastic properties and strength are estimated by considering the properties of the matrix and fibers, and the configuration of micro scale unit cells, which feature a fiber arrangement which is categorized as hexagonal and varying Vf at different locations (from 0.35 to 0.75). However, the overall Vf for the UD composite remains constant at 0.65. Studies are also carried out with the random distribution of fibers at micro scale unit cells. The findings reveal that the random distribution of fibers significantly impacts the shear behavior of the composite. This investigation provides valuable insights into how the mechanical properties of the UD composite are subjective by the distribution of fiber, thereby contributing to the design and development of this light weight high‐performance material.Highlights Elastic and strength analysis of UD composites is presented. Emphasis is on fiber dispersion in transverse plane. Microscale unit cells, RUCs and RVE are identified. Studies are carried out based on micromechanical model. Influence of fiber distribution on shear behavior is investigated.

Dynamic compressive properties of 2D-aligned steel fiber reinforced cement-based composites

Dynamic compression may happen in some protective cement-based composite structures. Cement-based composites are compressed at loading direction when subjected to dynamic compression, however expansion occurs in the direction perpendicular to the loading. As a quasi-brittle material, the expansion of the cement-based composites may result in the disintegration and hence the failure of the material. Incorporating steel fibers is a valid solution of reinforce the composites to resist dynamic compression. Usually, steel fibers are randomly dispersed throughout the composites. Actually, steel fibers with the same direction of the dynamic loading are ineffective. Only steel fibers perpendicular to the orientation of the dynamic compression load can they effectively restrict the expansion of the composites and enhance its dynamic compressive properties. So, cylindrical specimens using two-dimensionally aligned steel fiber reinforced cement-based composites (2D-SFRC) were prepared and tested. In specimens all steel fibers are perpendicular to the dynamic compression load, which limits the circumferential expansion and deformation of the specimens when subjected to dynamic compression and significantly enhances its performance resisting dynamic compression. When preparing 2D-SFRC specimens, the magnetic field was used to align steel fibers to achieve the two-dimensionally aligned steel fiber in specimens. Then, 2D-SFRC specimens were tested for their dynamic compressive properties. The results indicate that the dynamic compressive strength and toughness of 2D-SFRC specimens are significantly increased compared with unidirectional and random steel fiber distribution specimens. By analyzing the stress distribution and tensile force of steel fibers, the reinforcing mechanism of two-dimensionally aligned steel fibers was revealed. The two-dimensional alignment of steel fibers increased the number and the tensile force of fibers, which effectively restrained the circumferential expansion of the cylinder specimens.

Nonbinary 2D Distribution Tool Maps Autonomic Nerve Fiber Clustering in Lumbosacral Ventral Roots of Rhesus Macaques.

Neuromodulation of the peripheral nervous system (PNS) by electrical stimulation may augment autonomic function after injury or in neurodegenerative disorders. Nerve fiber size, myelination, and distance between individual fibers and the stimulation electrode may influence response thresholds to electrical stimulation. However, information on the spatial distribution of nerve fibers within the PNS is sparse. We developed a new two-dimensional (2D) morphological mapping tool to assess spatial heterogeneity and clustering of nerve fibers. The L6-S3 ventral roots (VRs) in rhesus macaques were used as a model system to map preganglionic parasympathetic, γ-motor, and α-motor fibers. Random and ground truth distributions of nerve fiber centroids were determined for each VR by light microscopy. The proposed tool allows for nonbinary determinations of fiber heterogeneity by defining the minimum distance between nerve fibers for cluster inclusion and comparisons with random fiber distributions for each VR. There was extensive variability in the relative composition of nerve fiber types and degree of 2D fiber heterogeneity between different L6-S3 VR levels within and across different animals. There was a positive correlation between the proportion of autonomic fibers and the degree of nerve fiber clustering. Nerve fiber cluster heterogeneity between VRs may contribute to varied functional outcomes from neuromodulation.

Experimental study and numerical simulation of transverse tensile behavior for thermoplastic glass fiber reinforced plastics

In order to predict the mechanical behavior of thermoplastic composites, the phases of glass fiber reinforced plastics (GFRP) were discretized within the computational micromechanics framework. This approach incorporated the random distribution of fibers, nonlinear matrix behavior, and interface damage behavior in a synergistic manner. Subsequently, a three-dimensional representative volume element (RVE) model was established. To verify the accuracy of the numerical model, macroscopic transverse tensile experiments on GFRP were designed. Building upon this foundation, a detailed study on the damage failure of GFRP under transverse tensile loads was conducted to reveal the damage evolution mechanisms. Furthermore, the influence of the random distribution of fibers, nonlinear characteristics of the matrix, and interfacial parameters on the transverse damage mechanical behavior of GFRP was elucidated. The results demonstrate that the random distribution of fibers significantly affects the damage initiation point and crack evolution path. Moreover, GFRP with higher interfacial performance exhibits substantially improved transverse tensile strength compared to those with lower interfacial performance.

A materials informatics framework based on reduced‐order models for extracting structure–property linkages of additively manufactured continuous fiber‐reinforced polymer composites

AbstractThe innovative combination of additive manufacturing (AM) and continuous fiber‐reinforced polymer composites (CFRPCs) confers products with the dual advantages of integrated manufacturing and designability of properties, but lack an efficient and reliable method for property prediction. This study presents a materials informatics framework using reduced‐order models and machine learning (ML) to extract the structure–property (SP) linkages between microstructures and macroscopic elastic properties of AM‐CFRPCs. The initial step involves generating microstructural 2D cross‐sections and representative volume elements (RVEs) with random fiber and pore distributions based on the minimum potential method. Then, finite element (FE) calculations are performed on RVEs to obtain nine macroscopic elastic properties. Following that, the quantification and dimensionality reduction of the 2D cross‐sectional dataset are conducted separately using two‐point spatial correlations and principal component analysis (PCA). Finally, a Bayesian optimized composite kernel support vector regression (CK‐SVR) algorithm is used to effectively establish complex mapping relationships between the reduced‐order representations of the microstructures and the mechanical properties. Despite the reduced‐order dataset containing only 3–6 variables, the framework generates an interpretable model exhibiting excellent accuracy with all predicted R2 values surpassing 0.91. Therefore, this framework presents a prospective solution for expediting the design and optimization of AM‐CFRPCs.Highlights A materials informatics scheme is proposed to predict the 9 elastic properties of AM‐CFRPCs. Microstructures are quantified and dimensionally reduced by two‐point statistics and PCA. SP linkages are established between 2D cross‐sections and 3D macromechanical properties. Modified CK‐SVR exhibits higher prediction accuracy compared to conventional models.

Prediction of thermal behavior of Earthen-Straw composite material with 3D numerical modeling of a random geometry without overlapping

Nowadays, stabilizing raw soil with straw fibers represents a sustainable eco-building practice. Moreover, the rebirth of the earth’s construction is primarily driven by the material’s thermal properties. In the present work, a 3D study of the earthen-straw composite material’s thermal behavior has been carried out to promote its use in construction and ensure satisfactory living conditions for the building. To consider the most possible influencing factors, the effect of fibers concentration on thermal conductivity was investigated for the straw contents of 5%, 10% and 15% by volume of earthen. Thus, a 3D model with a random distribution of straw fibers considered as cylinders without overlapping was designed under Catia V5. The distribution uses datasets from a hybrid algorithm developed for this purpose, which is then imported to Ansys Software to carry out the simulation allowing the computation of the thermal conductivity of the homogeneous material. It can be concluded that the proposed hybrid algorithm was efficient since the 3D numerical results based on the geometry generated by the algorithm’s output were satisfactory in comparison with those deducted from the 2D study and the existing theoretical models. On the other hand, adding straw fibers in the raw earth matrix with thermal conductivity equal to 0.75 W/(m.K) has enhanced its thermal insulation. Indeed, for 15% of straw fiber’s contents, we have found 0.633 W/(m.K) for the thermal conductivity of the earthen-straw composite material, which is equivalent to a decrease of 15.6% in this intrinsic parameter.

Effective mechanisms responsible for increased strength and fracture strain of carbon fiber-reinforced plastic/steel hybrid laminates

The tensile properties of carbon fiber-reinforced plastic (CFRP)/steel laminates have been observed to exceed the expected values predicted by the rule of mixture. While the CFRP/steel laminate is expected to fail at the failure strain of the CFRP lamina, it was observed that hybridization with a steel lamina improves the failure strain. This study investigates numerically and analytically the roles of each influential mechanism responsible for this enhancement, including the thermal residual strain, bridging effect, effect of compressive transverse stress on CFRP layers, and effect of tensile transverse stress on steel layers. To assess these mechanisms, multiple finite-element and analytical models were developed. A mesoscale finite-element model was proposed, which uses novel random fiber distribution algorithm capable of reproducing random fibers with high fiber volume fractions exceeding 65%. Rather than the meso-scale model, macro finite-element models and analytical relationships were developed to assess each hybrid mechanism. Analysis showed 6% increase of the failure strain due to thermal effect and up to 11% increase of strength due to multiaxial stress in steel layer. The results of this study contribute to a deeper understanding of the role of each phenomenon that contributes to improved tensile properties in hybrid CFRP/metal laminates.

Optimization of Electrospun Bilayer Vascular Grafts through Assessment of the Mechanical Properties of Monolayers.

Small-diameter vascular grafts must be obtained with the most appropriate materials and design selection to harmoniously display a variety of features, including adequate tensile strength, compliance, burst strength, biocompatibility, and biodegradability against challenging physiological and hemodynamic conditions. In this study, monolayer vascular grafts with randomly distributed or radially oriented fibers are produced using neat, blended, and copolymer forms of polycaprolactone (PCL) and poly(lactic acid) (PLA) via the electrospinning technique. The blending ratio is varied by increasing 10 in the range of 50-100%. Bilayer graft designs are realized by determining the layers with a random fiber distribution for the inner layer and radial fiber orientation for the outer layer. SEM analysis, wall thickness and fiber diameter measurements, tensile strength, elongation, burst strength, and compliance tests are done for both mono- and bilayer scaffolds. The findings revealed that the scaffolds made of neat PCL show more flexibility than the neat PLA samples, which possess higher tensile strength values than neat PCL scaffolds. Also, in blended samples, the tensile strength values do not show a significant improvement, whereas the elongation values are enhanced in tubular samples, depending on the blending ratio. Also, neat poly(l-lactide-co-caprolactone) (PLCL) samples have both higher elongation and strength values than neat and blended scaffolds, with some exceptions. The blended specimens comprising a combination of PCL and PLA, with blending ratios of 80/20 and 70/30, exhibited the most elevated burst pressures. Conversely, the PLCL scaffolds demonstrated superior compliance levels. These findings suggest that the blending approach and fiber orientation offer enhanced burst strength, while copolymer utilization in PLCL scaffolds without fiber alignment enhances their compliance properties. Thus, it is evident that using a copolymer instead of blending PCL and PLA and combining the PLCL layer with PCL and PLA monolayers in bilayer vascular graft design is promising in terms of mechanical and biological properties.

High Speed Milling Specific Cutting Energy Model of CFRP and Its Surface Quality Optimization Based on Random Fiber Distribution

High Speed Milling Specific Cutting Energy Model of CFRP and Its Surface Quality Optimization Based on Random Fiber Distribution

The spectral properties and dispersion parameters of electrospun nanofibers Poly(vinyl alcohol/ Poly(acrylamide)

Electrospun nanofibers based on polyvinyl alcohol (PVA), polyacrylamide (PAAm), and a PVA-PAAm blend (50/50 wt.%) were effectively made a room temperature(RT) and a voltage of (12kV). The products were studied using Field Emission Scanning Electron Microscope (FESEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy(FT-IR) and Ultraviolet-visible (UV–Vis) spectroscopy. The result of FESEM analysis showed that the polymer PVA, PAAm, and blend samples produced a random distribution of fine fibres at an average diameter of (214.12, 317.1, 157.65) nm with a smooth surface. In addition, the FESEM images demonstrate the fibres' suitability for use in gas sensing applications due to their branching fibres and porosity surface. XRD showed that the film polymeric of PVA, PAAm polymeric blend PVA-PAAm was seen to have a semicrystalline nature. According to the FTIR analysis, the PVA and PAAm networks in the PVA-PAAm polymer nanofibers were entangled due to the powerful hydrogen bond contact between the PAAm and PVA chains. Observed around (3473.79 and 3414) cm-1 were attributed to the N–H vibration and overlapped to O–H stretching. The spectra of the prepared films exhibit prominent absorption peaks, which are at the wavelength range (200-320) nm. PVA-PAAm polymer nanofibers decrease the energy gap from 3.70eV to 3.40eV. The Wemple-DiDomenico model was used to derive dispersion parameters such as dispersion energy, single oscillator energy, Urbach energy, the static refractive index and the moments of optical spectra the result of calculating by this model was compatible with that value calculated by the Tauc relation. While increased which qualifies them to be used in the electronic devices.

Analysing the impact of paper grammage and pulp blend on electrophotographic printing systems

AbstractThe effect of fibre length and grammage on the electrophotographic digital printing process was investigated in this study. While integral optical density values on handsheets have shown no significant change, unprinted handsheets have shown an increasing change as short fibre content has increased. Because of structural changes in the paper surface, the measured results for print chroma, brightness, contrast, and delta gloss differed between paper groups. This research confirmed that these changes have nothing to do with grammage or fibre length content. Regardless of the fibre length ratios, significant increases in tone values of ink, were accompanied by a decrease in the grammage of the handsheets among the grammage groups provided. The specimen grammage affected the universal colour diagrams, but not the fibre length. The discrepancies in all of these printing outcomes were thought to be caused by the random distribution of fibres and the distances between them on the paper's surface.

Micropatterned Nanofiber Scaffolds of Salmon Gelatin, Chitosan, and Poly(vinyl alcohol) for Muscle Tissue Engineering.

The development of scaffolds that mimic the aligned fibrous texture of the extracellular matrix has become an important requirement in muscle tissue engineering. Electrospinning is a widely used technique to fabricate biomimetic scaffolds. Therefore, a biopolymer blend composed of salmon gelatin (SG), chitosan (Ch), and poly(vinyl alcohol) (PVA) was developed by electrospinning onto a micropatterned (MP) collector, resulting in a biomimetic scaffold for seeding muscle cells. Rheology and surface tension studies were performed to determine the optimum solution concentration and viscosity for electrospinning. The scaffold microstructure was analyzed using SEM to determine the nanofiber's diameter and orientation. Blends of SG/Ch/PVA exhibited better electrospinnability and handling properties than pure PVA. The resulting scaffolds consist of a porous surface (∼46%), composed of a random fiber distribution, for a flat collector and scaffolds with regions of aligned nanofibers for the MP collector. The nanofiber diameters are 141 ± 2 and 151 ± 2 nm for the flat and MP collector, respectively. In vitro studies showed that myoblasts cultured on scaffold SG/Ch/PVA presented a high rate of cell growth. Furthermore, the aligned nanofibers on the SG/Ch/PVA scaffold provide a suitable platform for myoblast alignment.

Simulation Analysis of Composite Axial Tensile Failure Considering Fiber Strength Dispersion

The axial strength limit of composites exhibits obvious dispersed characteristics. Based on the finite element simulation, using the Weibull distribution to describe the fiber strength, and considering the random distribution of fibers within the matrix, a representative volume element of composites was established in this article. The axial tensile failure of T300/BSL914C composites was studied and the effects of fiber tensile strength and volume fraction on the axial tensile strength of composites were analyzed. Results show that considering the influence of fiber strength dispersion, the fracture of fiber bundles exhibits a progressive failure during the composite tensile failure process, and before the fiber fracture, the interface is not subjected to stress. Axial tensile strength increases linearly with the increase of fiber tensile strength and volume fraction. The composite axial tensile strength could be improved by selecting high-strength fibers or increasing fiber volume fraction.

Efficient generation of random fiber distribution by combining random sequential expansion and particle swarm optimization algorithms

Representative volume elements (RVEs) with random fiber distribution are widely used in micro-mechanics for determining the properties of unidirectional fiber-reinforced composites from their microstructure. In this paper, the random sequential expansion (RSE) and particle swarm optimization (PSO) algorithms are combined to develop an efficient methodology for generating such RVEs. This methodology can successfully eliminate the biased regions of dense fiber population and unreal matrix-rich corners that usually appear in created RVEs and resolve the complications in selection of the input parameters in the RSE algorithm. Statistical analysis of the generated microstructures and two- and three-dimensional finite element analyses are performed to validate the capability of the proposed algorithms.

An accurate analytical model for stress overload around multiple fiber breakpoints in unidirectional fiber reinforced plastic

Efficient and accurate calculation of stress overload and stress redistribution near the fiber breakpoint is the basis for simulating the tensile damage evolution of unidirectional fiber reinforced plastic (FRP), and it is also the premise for predicting the tensile-tensile fatigue life. In this study, an efficient finite element (FE) model with a large number of fibers was developed based on the FE method to calculate stress concentration factor (SCF) near multiple breakpoints, and the calculation time only takes 3 min on average. The FE model is used to efficiently calculate multiple breakpoints and the stress distribution near the breakpoint considering the interface debonding. Based on the efficient FE model, an analytical model is developed to calculate the stress overload superposition around multiple breakpoints. In this analytical model, the shear stress distribution near the broken fiber elements is established based on the experiment, and the stress redistribution mechanism near the breakpoint in FRP with random distribution of fibers is established. Moreover, the calculation method of stress overload near multiple break points is established, and the FE method is verified.

Optimizing the buckling resistance of injection molding composite plates by manipulating gate locations

In contrast to continuous-fiber-reinforced polymer (cFRP), the random distribution of fibers in short-fiber-reinforced polymer (sFRP), which depends on the manufacturing process, has a significant impact on the mechanical properties of sFRP components. In this study, an automatic joint injection-buckling analysis framework was developed that can simulate the injection process and predict the mechanical performance in sequence. This automatic analysis framework can be directly utilized to optimize the manufacturing process to improve mechanical properties. Based on this method, it is demonstrated that an sFRP plate (consisting of carbon fiber-reinforced polyphenylene sulfide) has better buckling resistance than an aluminum alloy plate with the same design weight. The buckling resistance can be further improved by manipulating the gate location in the injection molds. The optimization scheme was verified using the conventional analysis framework. Moreover, the optimization method was improved by utilizing a tensor-similarity-based algorithm, which can substantially decrease the time required to locate the optimal solution.

Experimental Investigation on the Impact of Micro-Steel Fibers on the Flat Slabs' Punching Shear Resistance

This research examined the effects of micro-straight steel fiber percentage and column form on the punching shear of SFRC slabs. Fibers made of micro steel with a diameter of 0.2 mm and a length of 13mm with an aspect ratio equal to 65 were used. The fiber content varied between 0.5%, 1%, and 1.5% by volume. Four different types of concrete mixes were adopted and tested. Experimental results showed that when the percentage of steel fibers in SFRC increased, its compressive strength, flexural strength, splitting tensile strength, and direct tensile strength improved. This investigation applied a monotonic load to eight cast slabs (two each of conventional concrete of square and circular column sections of the equivalent area while the other six slabs were made with steel fiber concrete. The dimensions of each slab were (920 x 920 x 80 ) mm. Each slab specimen had essential, edge-based support with square and round column sections. It has been demonstrated that slabs with square column sections endured a relatively higher ultimate load than slabs with circular column segments when the steel fiber dosage was 0.5% or 1.0%. Still, at a steel fiber dosage of 1.5%, circular column segment slabs approached the ultimate load of square column segment slabs. The heterogeneous behavior in concrete can be attributed to the random and unequal distribution of steel fibers throughout the material. There were only flexural fractures visible on the tensile face of the slab. New fractures emerged in the center of the slab as the load increased.

Effect of random fiber distribution on the performance of counter-flow hollow fiber membrane-based direct evaporative coolers

The counter-flow hollow fiber membrane-based direct evaporative cooler (MDEC) was proposed as an energy-efficient and hygienic air cooling solution. The random sequential addition algorithm was used to simulate the randomness of fiber distribution within the MDEC in engineering practice. 3D numerical models were developed with a computational domain determined as a hexagonal prism containing multiple fibers. The experimentally validated model depicted the air state variation along the path under regular and random fiber distributions. The differences in wet-bulb effectiveness (εwb) and coefficient of performance (COP) of MDEC with two configurations, regular and random fiber distributions, were compared for different packing fractions and air flow rates. Furthermore, dimensionless correlations for the shell-side friction factor (f), Nusselt number (Nu), and Sherwood number (Sh) were derived to generalize the results to other hollow fiber membrane modules employed in liquid/gas systems. The results showed that the channel flow effect and dead zone under the random configuration worsened the heat and moisture handling performance of MDEC. Compared with the regular configuration, both Nu and Sh were degraded by 11.6–55.6%, but f was desirably reduced by 28.8–49.8%. Balancing cooling capability and energy efficiency, a regular configuration with moderate packing fraction was more beneficial for engineering practice.