PROCEEDINGS OF THE AMERICAN SOCIETY FOR COMPOSITES-THIRTY-SEVENTH TECHNICAL CONFERENCE
Development of a C-ELS Specimen-Based Numerical Benchmark for Mode II Delamination and Assessment of Two VCCT-Based Propagation Strategies
A finite element (FE) benchmark example inspired by the calibrated end-loaded split (C-ELS) specimen is developed and used to assess the performance of delamination propagation capabilities based on linear elastic fracture mechanics (LEFM). The C-ELS specimen has the advantage of a longer region of stable delamination propagation compared to the existing mode II benchmark case. The new benchmark example may therefore provide a better assessment tool by enabling more stable crack growth in regions further away from the boundary conditions or load application. First, a benchmark result is created manually using two-dimensional finite element models of the C-ELS specimen with different delamination lengths. Second, the performance of the virtual crack closure technique (VCCT) delamination propagation capabilities in the Abaqus/Standard®1 FE code and the recently developed Progressive Release eXplicit-VCCT (PRX-VCCT) method are assessed by comparing the results to the benchmark case. Two examples with different starter delamination lengths are studied. A shorter starter length is chosen to create a scenario with unstable delamination propagation. A longer delamination encourages stable delamination propagation. Detailed results from three-dimensional analyses with aligned and misaligned meshes and two levels of mesh refinement are provided. In general, good agreement can be achieved between the results obtained from the quasi-static propagation analysis and the benchmark analysis. Numerical artifacts including anomalous unreleased nodes in the crack wake and zig-zag crack fronts occur for propagation analyses using Abaqus/Standard VCCT. In comparison, continuous, smooth, delamination fronts are observed for PRX-VCCT. The use of the benchmark case to assess different VCCT-based propagation strategies illustrates the value of establishing benchmark cases.
The Role of Friction in the Strength Size Effect in Fiber Composites Failing by Compression Kink Bands
Prior studies have provided experimental evidence of the size effect on the nominal strength of fiber composites, failing by the formation of a kink band under compression. This size effect is analyzed here computationally with the goal to understand and quantify the role of crack face friction. The mechanism of kink band formation is modeled by the semi-multiscale cylindrical microplane model, recently calibrated and experimentally validated for its predictions of the failure geometry as well as strength size effect. The kink band initiation in the model is driven by damage triggered on cylindrical microplanes. The model embodies a combined damage friction formulation on the microplane level, which assumes a parallel coupling between the two mechanisms. The model is used here to predict the strength size effect with and without friction effects. In the friction-free models, the predicted strength is found to scale in accordance with linear elastic fracture mechanics, suggesting brittle fracture. On the other hand, in the models embodying friction, the fracture process zone size is found to be enlarged, and the predicted strengths are found to not only obey the Bažant size effect law, but also match the test data. The strengths are found to fall in the transitional portion, suggesting quasibrittle fracture. Thus, the inclusion of friction is found to considerably increase the degree of quasibrittleness, and the combined friction/damage based microplane model employed here, is found to be useful to quantify this increase.
A Textile Architecture-Based Discrete Modeling Approach for Fabric Draping Simulations
Adoption of lightweight composites for structural components is transforming the transportation industry in pursuit of improved performance and better fuel economy. In Liquid Composite Molding (LCM), dry fabric deformation in the draping process gains lots of attention as it affects the fiber orientation, leading to variations in fabric permeability and the resulting final quality of the product due to the change in infusion and curing processes. The lack of robust modeling tools makes the composite manufacturers heavily reliant on trial-and-error approaches to minimize part variability, resulting in high manufacturing costs and limiting innovations for new process and part designs. The current study develops a modeling approach to predict the deformation for dry fabric. In the model, fabric is made of interlacing virtual fiber tows which are represented by Timoshenko beams joint by translational and rotational springs. Dashpots at intersections are used to capture energy dissipation. The proposed model features the simplicity and efficiency in the prediction of shear angle when fabric is subject to 3-dimensional loading. Another highlight of this study is the consideration of characterized relaxation behavior of fabric subject to in-plane shear loading. Cantilever beam bending tests and picture frame tests were carried out to characterize material properties, geometric characteristics, spring stiffness, and damping coefficients. The proposed model was applied to a hemisphere draping model implemented in Abaqus to demonstrate the predictive capability.
Evaluation of Composite DCB Delamination Growth by Combining Experimental Data and Numerical Analysis
A study of quasi-static mode I delamination in a laminated unidirectional composite double cantilever beam (DCB) configuration was conducted experimentally and numerically. A two-dimensional (2D) finite element (FE) correction method that consisted of a series of analyses of the DCB compliances at different delamination lengths was conducted to establish an analytical correlation between the delamination length and the DCB opening compliance. This analytical correlation was then used to determine the delamination length provided the experimentally measured compliance. Consequently, the problematic delamination lengths generated from in-situ optical measurement were evaluated and corrected. Also, the fracture resistance curve was updated using the corrected delamination lengths. Good agreement in the loaddisplacement variation was then obtained between the experimental results and the subsequent 2D DCB FE modelling results using cohesive elements. Commentaries on the DCB quasi-static failure analysis and modelling using the cohesive zone modelling technique and the virtual crack closure technique were also provided.
Improved Buckling Resistance in Wind Turbine Blades Through the Production of GFRP Composites with Enhanced Resins
The shear and transverse stiffnesses of unidirectional glass fiber reinforced polymer (GFRP) composites, which constitute a significant portion of wind turbine blades, are dominated by the resin properties. Accurate analysis and therefore optimized usage of such materials are critical in design of super-sized offshore blades, whose macro-structural properties may be improved through use of enhanced resins. In this paper, the properties of GFRP composites made using resins with assumed enhanced properties are accurately predicted using the Continuous Periodic Fiber Model (CPFM) and inserted into macroscopic finite element blade models of 33 and 100 meter lengths. Changes to blade performance in terms of buckling, bending, torsion, and trailing edge shear are quantified. Resins of increasing Young's modulus demonstrated increased blade transverse stiffness and postponed the buckling failure onset. Delayed buckling provides the opportunity to decrease the overall blade mass, reduce the required core foam, and optimize cost/performance for large offshore turbines.
An Efficient Numerical Approach to Evaluate Process-Induced Free-Edge Stresses in Laminated Composites
This paper presents an advanced modeling approach to predict process-induced residual stresses at the free-edge of laminated structures. The numerical model is based on the Carrera Unified Formulation, a numerical tool that allows any kinematic model to be considered without an ad hoc implementation. A layer-wise kinematic model has been adopted to detect the through-the-thickness distributions of transversal stresses. The process's evolution of the material properties is obtained by the RAVEN ® software. A cure hardening instantaneously linear elastic (CHILE) constitutive model was adopted. Peeling and transverse shear stress distributions along free-edges were computed and proved to be very high and localized.
Mechanical Property of Phenolic Resin via Molecular Dynamics Using a Reactive Force Field
During terrestrial atmospheric re-entry, aerospace vehicles can be subjected to temperatures greater than 1800 K which requires thermal insulation to protect the aircraft. Thermal protection systems (TPS) were developed to address this challenge with two goals in mind: (1) provide insulation to inner materials from high temperatures and (2) maintain low weight to reduce payload costs. One class of TPS materials commonly used as ablatives are carbon-carbon composites (CCCs), which consist of a carbon matrix embedded with carbon fillers. Common aerospace materials lose mechanical integrity at high temperatures, while CCCs continue to perform. The manufacturing process of CCCs is cyclic and begins with a net-shape uncured prepreg which is subjected to polymerization and carbonization via pyrolysis. Due to the shrinkage and mass loss associated with these processes, the resulting structure is subjected to several cycles of uncured resin re-impregnation, polymerization, and carbonization until a sufficiently dense structure is achieved. Carbon yield is defined as the mass remaining after carbonization divided by the mass before carbonization and is used as a metric for selecting carbon matrix precursors. A high carbon yield translates into fewer re-impregnation cycles, thus economizing the process. Phenolic resin is a common carbon matrix precursor material due to its relatively high carbon yield of 50-55%. The goal of this project is to establish molecular dynamics (MD) protocols for simulating the manufacturing process of a phenolic-derived carbon matrix. In the present work, an atomistic MD model of the polymerization of phenolic resin was simulated using a reactive force field. By using a well-known material system, resulting MD properties can be compared to experimental values for validation. Since the end goal is a carbonized product, a poly- merized phenolic structure was created using pre-polymerized monomers as the initial structures which are then crosslinked at high temperature (1000 K) via an openvalence approach. A total of 5 replicates were built to account for statistical variation. To keep track of the gelation behavior of the system, the extent of reaction is calculated using Carothers' equation for a trifunctional branching polycondensation reaction, as well as the percent mass of the largest cluster relative to the system mass. After obtaining a gelled structure, the system was equilibrated and subjected to uniaxial tensile simulations. True stress and true strain values from the tensile simulations were plotted to calculate Young's modulus (E) based on the slope of the initial linear portion. The average equilibrated mass density was found to be 1.24 g/cc, while average E was calculated as 3.60 GPa. These properties agree with the experimental values of a mass density of 1.2 – 1.25 g/cc and E of 2.36 – 4.83 GPa.
Investigation of the Multifunctional Carbon Nanotubes-Glass Fiber-Epoxy Composites: Microwave Absorption and Mechanical Properties
With the rapid arising of wireless technology and other microwave applications towards gigahertz frequency in modern communications, microwave absorbing materials (MAM) are playing an increasingly significant role in healthcare, electronic reliability, and defense security. In this work, we aim to explore multifunctional polymer nanocomposites based on carbon nanotubes (CNTs) –epoxy with glass fiber reinforcement, which can be used for microwave absorption and also as structural materials. We fabricated and systematically investigated the mechanical and microwave absorption properties of multi-walled carbon nanotube (MWCNT) - glass fiber (GF) - epoxy composites. Various MWCNT concentrations (1, 3, 5, 7, 9, and 11 wt%) in epoxy resin have been synthesized by shear-mixing method and the reinforcing GF contents (55, 67, and 74 wt%) were controlled by the number of GF plies in the composites. We used low mechanical stirring to avoid introducing air bubbles in MWCNTs - epoxy solution and implemented a press molding (press forces up to 700 Nâˆ™cm-2) during the curing process of the composites to reduce voids in the composites. We studied the mechanical properties, electrical conductivity, and microwave absorption properties of the composites, in addition to the morphology and dispersion properties of MWCNTs and GFs in the composites. The scanning electron microscope (SEM) images indicated a more uniform distribution of MWCNTs in epoxy resin than that in the previous work. The microwave absorption measurements of the composites show excellent electromagnetic (EM) wave absorption performance and high reflection loss (RL) at particular frequency range. The maximum RL of the composites can reach to -48 dB at 24.5 GHz for 3.1 wt% MWCNT loadings and 55 wt% GFs in the composites, with an effective bandwidth (i.e., the frequency range for RL below -10 dB) of about ~6 GHz. The EM wave absorption of the composites strongly depends on MWCNT and GF contents and can reach to ~70% at 26.5 GHz with 4.1 wt% MWCNTs in the composite; further, such dependence is peculiar, contradicting to the conventional wisdom, due to the high density interfaces in the materials, which lead to multiple scatterings and multiple absorptions of EM waves. In addition, the tensile strength of the composites was enhanced to ~427 MPa with ~74 wt% GFs, that is comparable to that of commercial Al alloy 6061 (~300 MPa, but not much EM wave absorption). Our results showed that the tensile strength of the MWCNT-GF-epoxy composites was dominated by the contribution of the GF content, while the EM properties are highly impacted by MWCNTs and the interfaces between MWCNT-epoxy matrices and GFs. The mass densities of the composites were about 1.55, 1.73, 1.88 gâˆ™cm-3 for 55, 67, 74 wt% GF reinforced composites, respectively, which are about 30% ~ 43% lighter than the commercial aluminum alloy 6061 (mass density of 2.7 gâˆ™cm-3). The results suggest that the MWCNT-GF-epoxy composites have the potential as multifunctional microwave absorption and low-weight structural materials without the need of additional coating.
Predicting Stochastic Lightning Mechanical Damage Effects on Carbon Fiber Reinforced Polymer Matrix Composites
Three stochastic air blast models are developed with spatially varying elastic properties and failure strengths for predicting lightning mechanical damage to AS4/3506 carbon/epoxy composites subjected to < 100 kA peak currents: (1) the conventional weapon effects program (CWP) model, (2) the coupled eulerianlagrangian (CEL) model, and (3) the smoothed-particle hydrodynamics (SPH) model. This work is an extension of our previous studies [1–4] that used deterministic air blast models for lightning mechanical damage prediction. Stochastic variations in composite material properties were generated using the Box-Muller transformation algorithm with the mean (i.e., room temperature experimental data) and their standard deviations (i.e., 10% of the mean herein as reference). The predicted dynamic responses and corresponding damage initiation prediction for composites under equivalent air blast loading were comparable for the deterministic and stochastic models. Overall, the domains with displacement, von-Mises stress, and damage initiation contours predicted in the stochastic models were somewhat sporadic and asymmetric along the fiber’s local orientation and varied intermittently. This suggests the significance of local property variations in lightning mechanical damage prediction. Thus, stochastic air blast models may provide a more accurate lightning mechanical damage approximation than traditional (deterministic) air blast models. All stochastic models proposed in this work demonstrated satisfactory accuracy compared to the baseline models, but required substantial computational time due to the random material model generation/assignment process, which needs to be optimized in future work.
Machine Learning for Strength and Damage Prediction of Adhesive Joints
In this study, machine learning (ML), a subdivision of artificial intelligence (AI), is implemented to study the mechanical behavior of adhesive single-lap joints (SLJs) subjected to tensile loading. The experimental data for training and testing the ML models are compiled from peer-reviewed journal papers to eliminate bias and increase the diversity within the data. The dataset is comprised of eight continuous SLJ parameters, which are used to predict the SLJ damage mode and failure strength. To accomplish this, regression and classification models are built using deep neural networks (DNN) and random forests (RF). Finite element (FE) modeling is conducted, and the performance is compared with the accuracy of the regression ML models. Results show ML models were able to predict strength with higher accuracy than FE modeling. Furthermore, both DNN and RF classified damage mode accurately without failure criteria, exposing limitations within FE modeling. As a result, this study introduces the use of ML for strength and damage mode prediction of adhesive SLJ, providing insights into their mechanical behavior, revealing hidden property performance patterns, and enhancing predictability.
Investigating the Influence of Nanoparticle Size and Orientation on Failure in Notched Epoxy Nanocomposites Using the Atomistic J-Integral
The goal of this paper is to (a) investigate the validity of using continuum-based linear elastic fracture mechanics (LEFM) methodology to model fracture processes at the "discrete" atomic scale and (b) investigate the impact of nanographene platelet size on the rupture strength of an edge-cracked polymer block. EPON 862 epoxy polymer with a cross-link density of 85 percent was selected for this study. Furthermore, an atomistic J-integral is used as a nanoscale fracture metric to explore flaw-tolerance at the nanoscale, which several other studies have reported, and to build a methodology to evaluate and predict the material's initiation fracture toughness. For this purpose, five different molecular dynamics (MD) models of edge notched specimens that are similar to Compact Tension (CT) specimens were developed, each with a different size of graphene nanoplatelet (GNP) and different orientations, and they were all embedded in EPON 862 epoxy polymer with 85 percent cross-link density. All simulations in this work are performed using the molecular dynamics software LAMMPS and the bond order based ReaxFF potential available in LAMMPS. Significant deviation of peak Jintegral values from LEFM is detected at crack lengths below a critical threshold crack length. GNP size and orientation significantly affect far-field stress vs. strain plots and near-tip stress-fields. The atomistic J integral plots also revealed that our computational methodology is robust enough to capture weak singularity at the subcritical crack-tip, and that J vs. K data approximately obeys the quadratic relationship predicated by LEFM even at the nanoscale.
Experimental and Numerical Evaluation of Lightning-Induced Degradation of Fastened Composite Systems
Aerospace composite laminate construction is widely used in various airframe components. Composite structures are often joined with other structure and substructure via fasteners that are inevitably exposed to lightning strike currents. The interaction of a lightning strike with a fastener can lead, through complex electrical, mechanical, and thermochemical processes, to the degradation of the strength of the fastened structure. Although degradation can often be seen on the surface as damage via paint discoloration, surface ablation, or surface delamination, a larger subsurface volume of material might be affected by the electrical current and thermo-chemical processes resulting in a heat affected zone and multi-planar delamination. Together, these effects have the potential to degrade the structural performance of the joint. In this work, a series of electro-mechanical tests is performed in order to evaluate the effect of lightning strikes of varying amplitudes on structural composite. The experimental methodology includes subjecting a single-fastener aerospace-composite lap joint to scaled Awaveform electric current pulses to determine the combined electromagnetic and structural effect on the system. Following the electrical test, the tested articles undergo a non-destructive inspection to quantify the extent of the damage, from which the relation between heat-affected zones extents and current levels is given. Finally, electrically-tested articles undergo a bearing test and the structural effect of the lightning strike on the structural properties of the fastened system is determined and implications on composite structural performance is assessed.
The Roles of Interface, Adherend, and Adhesive in Plasma- and Other-Treated Joints of Metals and FRP Materials Under Shear Deformation
This work investigated the role of interface, adherend, and adhesive in adhesivelybonded metal-metal, metal-CFRTP, and CFRTP-CFRTP combinations with plasmatreated surfaces under shear deformation. To this end, aluminum alloys (AA5052 and AA6061) and short-carbon-fiber-reinforced polyamide 66 (CFRPA66) were used as examples and performed through single lap shear testing. The results showed that air plasma surface treatment can improve the shear behavior of adhesively-bonded AA5052-CFRPA66 and CFRPA66-CFRPA66 joints with about 20% enhanced lap shear strength compared to non-treated cases. Failure surface morphology of plasma-treated CFRPA66 adherend confirmed this improvement by showing an increased amount of adhesive failure than interfacial failure between CFRPA66 and adhesive. But this is not true for AA5052-AA6061 joints with plasmatreated surfaces exhibiting almost no enhanced lap shear strength. This study also showed the importance of selecting a proper surface modification method for the enhancement of adhesive-bonded structures under shear deformation through the analysis of the results in this study and in the literature. For fiber- reinforced polymers (FRPs), improving FRP/adhesive interface may be prioritized via different surface modification methods (e.g., plasma, chemical coating, etc.) than adhesive modification methods. However, for surfacecleaned metals, toughening adhesive via different enhancement methods (e.g., nanoparticles, chemical enhancement, etc.) may be more important than improving metal/adhesive interface. These insightful results are valuable in the area of multimaterials joining.
Effective Transverse Reinforcement of Unidirectional Thin Prepreg Composites Using Vertically Aligned Carbon Nanotubes
In this paper, we investigate the use of vertically aligned carbon nano tubes (VACNTs) in laminated composites across nearby plies for developing advanced composites to improve the transverse mechanical properties of the composite. VACNTs introduced into the interlaminar area by manually printing aligned carbon nanotubes onto the surface of the composite prepreg plies. The transverse tensile test is utilized to determine the improvement in transverse mechanical properties. The results shows that the transverse tensile improved by 31.6 %. This approach demonstrates extremely promising outcomes in terms of improving the composite's transverse strength.
Impact Performance Comparison of Fiber Reinforced Composite Sandwich Structures in Arctic Condition
About 40% of sea ice-covered areas have been reduced over the last three decades due to the effect of global warming. The Northern Sea route has been considered as a more effective, quicker, and economical sea route for marine vessels. But it is not safe to operate in such a cold and harsh environment due to the potential risk of collision with ice chunks, resulting in damages in the marine structures. It is therefore important to understand the behavior of marine composites at low temperatures, with the overarching goal that leads to improved design for marine structures and materials that can operate safely and effectively in the Arctic environment. This study investigates the low-velocity impact performance and damage mechanisms of woven carbon fiber reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP), and carbon-glass fiber hybrid face sheets sandwich panel at both room temperature (23 °C) and low temperature (-70 °C) to mimic the Arctic environment. A series of low-velocity impact tests (3.46 m/s and 4.92 m/s) is performed at 15 J and 30 J energy using a drop tower testing machine. A relative comparison of the impact response due to different face sheet materials is presented in terms of force, displacement, and energy. Force-time and force-displacement plots show that GFRP sandwich composites have the highest damage initiation force and peak force values across different temperatures and impact energies. Furthermore, the lowest energy absorption for GFRP composites is found responsible for the least impact-induced damage. X-ray microcomputed tomography reveals severe fiber breakage on the compression side of CFRP sandwich panel and back face spitting at both temperatures for 30 J impacts. By replacing carbon fibers with glass fibers, the damage mechanism switches from fiber breakage to delamination as the dominant failure mode. The findings from this work will aid in a better understanding of the impact failure modes of composite sandwich structures at extremely low-temperature conditions.
Corrugated Core Made by 4D Printing of Composites for Flexible Aircraft Wing
This paper presents a procedure to make composite corrugated core without the need for a mold with corrugated shape. The technique is called 4D printing of composites. The corrugated composite is intended to serve as the core for flexible aircraft wings. A demonstrator sample was manufactured and tested. It was shown that the flexible wing can morph up to 20o and can withstand loads for small unmanned arial vehicles.
Convolutional Neural Network for Predicting Mechanical Behavior of Composites with Fiber Waviness
The fiber waviness is inevitable in non-crimp fabric (NCF) reinforced composites. It is very challenging to accurately and efficiently predict the material behavior with fiber waviness. This work presents a machine learning approach to the prediction of material behavior of NCF composites under a compressive load. The out-of-plane fiber orientations are first extracted from micrographs of NCF laminates. A digital twinning process is followed to create finite element (FE) models with elementwise fiber orientations. Based on the FE models, a physics-based damage model is employed to generate high-fidelity simulation datasets, capturing the kink-band due to the fiber waviness. With the simulation datasets, convolutional neural network (CNN) models are developed to take the images of the fiber orientations and predict the corresponding stiffness, strength, and stress-strain curves of the NCF composites. The results show that the CNN models can capture spatial information of the fiber orientation and efficiently predict the corresponding material behavior with a high accuracy. In addition, the correlations of the fiber orientations and the final material behaviors are investigated based on the developed CNN models.
Investigating the Effects of Cure Pressure on Tool-Part Interaction and Process-Induced Deformations in Composites
The interaction between a tool and part during composites manufacturing may significantly contribute to the formation of residual stresses and process-induced deformations (PIDs). High levels of uncertainty are often associated with tool-part interaction and resulting PIDs due to the complex underlying physics, and variabilities and uncertaintieis in processing. During the assembly of aerospace composite structures, PIDs may create significant geometry mismatches and lead to a loss of mechanical performance. Aerospace manufacturers commonly use costly and timeconsuming techniques such as shimming to compensate for PIDs and meet process specification requirements. Although process simulation tools have evolved significantly in recent years to enable mitigation of PIDs via tool geometry compensation, in practice, they are not implemented often due to challenges associated with the characterization and calibration of numerical models. One such challenge is accurately measuring the degree of tool-part interaction and interfacial stresses during processing cycles. This paper presents a custom-built test fixture to directly measure tool-part interfacial stress development during processing of composites. The experimental setup is installed in a Dynamic Mechanical Analyzer (DMA) for in-situ measurement of tool-part interfacial stresses. The technique allows for the evaluation of the effects of process parameters, including pressure, temperature, lay-up, and tool surface condition. In this study, tool-part stress development was characterized as a function of the applied pressure for Toray T800S/3900-2 laminates cured on steel tools treated with Frekote release agent. The characterized stresses were then validated by measuring warpages of long and symmetric laminates cured on flat steel tools using different pressures similar to DMA tests. Results demonstrated that cure pressure significantly impacts the multi-physics interactions between fibers, resin, interply tougheners, and the tool surface throughout a cure cycle. The results of this paper can be used to expand the current understanding of tool-part interaction and potentially mitigate PIDs in composites processing.
Radical Induced Cationic Frontal Polymerization for Rapid Out-of-Autoclave Processing of Carbon Fiber Reinforced Polymers
Radical induced cationic frontal polymerization (RICFP) is considered as a promising method for processing of fiber reinforced polymers (FRPs). Optimization of the local heat flow is required to pave the way for its adaptation to an industrial processing method. In this work we present an overview on the role of the mold design on the frontal polymerization characteristics and resulting chemical properties. Mold properties were found of significant influence on the front characteristics. Highly insulating molds allowed for the highest front temperatures and velocities while consequent delayed cooling is suggested beneficial for the monomer conversion in neat polymer and FRP systems. An optimized mold configuration was subsequently used for FRP production, allowing for self-sustaining RICFP in FRPs with fiber volume fractions (Vfs) up to 45.8%. A processing window was moreover defined relating the Vf and required heat generation to the potential formation of a self-sustaining or supported front.
On The Representation of Through-the- Thickness Reinforcements in Finite Element Analysis of Stitched, Blade Stiffened Panels
Modern aircraft employ laminated composites for their tailorable in-plane properties, high specific strengths, and high specific stiffnesses. However, laminated composites exhibit relatively poor interlaminar properties without through-the-thickness reinforcements. Quantifying the necessary amount of throughthe- thickness reinforcements is necessary to reduce cost and meet damage tolerance certification requirements. In this study, a discrete superposed cohesive element (DSCE) approach is applied to represent the mixed-mode delamination behavior of stitched stiffened panels subjected to seven-point bending. This approach is compared to a one-dimensional embedded spring element (ESE) method. The DSCE approach uses two superposed bilinear traction-separation laws to obtain a representative load-displacement response determined from interlaminar tensile and shear tests. Additionally, several stitch configurations (unstitched, stitched, and overstitched) are evaluated in terms of their load-displacement response and crack-arrestment capability. Results indicate that the DSCE and ESE approaches show good agreement with respect to the predicted load-displacement response, but the ESE method tends to overpredict the crack growth behavior by approximately 13%. Stitches were not observed to fail during skin-stringer separation. Using an overstitched laminate with stitches near the flange edge provides the greatest crack-arrestment capability. Furthermore, the skin retains 92% of its stiffness after skin-stringer separation occurs.
Mesoscale Analysis of Translaminar Fracture in Thin-Ply Laminates
Translaminar fracture toughness is a key property that determines the notch sensitivity and the damage tolerance of fibre-reinforced composites. By establishing a novel downscaled compact tension specimen configuration, designed for 4D synchrotron radiation computed tomography, a comprehensive perception of developed failure mechanisms can be attained. In this study, first, an initial finite element model, based on limited literature data for a compact tension of a [90/0]8s T300/913 carbon-epoxy laminate [1] is developed. Next, the cohesive law parameters between 0°/0° plies in a [902/0/902/0/902/0/902] thinply HS40/736LT laminate are directly extracted from in-situ synchrotron radiation computed tomograms of miniaturized compact tension specimens. The interlaminar (90°/90°) parameters are obtained from double cantilever beam test results on a similar material system. To accurately predict the ð‘…-curve, the crack extension and crack opening displacements, in both 90° and 0° plies, were captured in a multi-linear cohesive law. Consequently, in the proposed finite element approach, two distinct cohesive surface definitions are assigned to the fracture plane. The numerical results confirm the lagging crack fronts in 0° plies.
Modeling Cold Spray Deposition of Thermoplastic Polymers: Effects of Impact Angle and Temperature
Cold spray additive manufacturing is gaining popularity for polymers due to its low operating temperature and reduced manufacturing time. In the present study, the likeon- like impact of single thermoplastic polymer (polyether ether ketone, PEEK) particles on PEEK substrates is modeled to explore the effects of impact angle, initial particle temperature, and impact velocity on cohesion. The particle impact angle varies from 30o to 90o with 15o intervals for impact velocities ranging from 200 to 1000 m/s. Particle temperature in each case is varied from room temperature to the glass transition temperature of PEEK. Results obtained herein provide an insight into the energy balance and the temperature-velocity conditions likely to lead to bond formation. Modeling results demonstrate that the likelihood of bond formation increases with an increase in impact angle, particle temperature, and velocity, at the cost of bond strength.
Monitoring Void Formation During Liquid Composite Molding by In-Situ X-Ray Computed Tomography
Polymer composites manufactured by liquid molding contain voids, which may have several origins. Porosity patterns in composites are usually characterized ‘postmortem’ via X-ray computed tomography (XCT), which gives only limited information about the void formation mechanisms. In this work, a new lab-based XCT experiment is proposed for the dynamic in-situ monitoring of void formation in thick fiberreinforced polymer composites produced by vacuum infusion. In particular, the method makes it possible to follow the evolution of void volume fraction, size and location during the curing or polymerization of the infused resin within a fibrous preform.
Effect of Manufacturing Defects on Composite Energy Absorbers: Experimental Analysis
Energy absorbers manufactured using reinforced composite materials absorb energy by undergoing a complex combination of failure modes such as matrix cracking, fiber fracture, delamination, sub-laminate bending, and fiber-matrix debonding. The presence of defects could undermine the load-carrying capabilities of these energy absorbers. In the current investigation, the effect of manufacturing defects on energy absorption capabilities and damage evolution of two different geometries, corrugated beams and cchannel stanchions, has been presented. The manufacturing defects investigated, introduced during specimen fabrication, include out-of-plane fiber waviness/wrinkling and delamination. Two different material systems and two different stacking sequences have been evaluated for each energy absorber type. Three-dimensional Digital Image Correlation (DIC) provides a comparison of damage evolution of pristine specimens and specimens with manufacturing defects.
Mechanical Characterization of 8HS S-2 Glass/SC15 Composites for MAT162 Applications
MAT162 is a composite material model, which has been used for simulating ratedependent progressive damage behavior of composite materials under high velocity impact applications such as ballistic penetration and perforation. A limited number of material systems, e.g., (i) unidirectional (UD) S-2 Glass/SC15, (ii) plain weave (PW) S-2 Glass/SC15, (iii) PW S-2 Glass/Phenolic, and (iv) PW E-Glass/Phenolic composites have been characterized for MAT162 material properties and modeling parameters in the literature. This material model needs 37 material properties and parameters to present rate-dependent progressive damage occurred in structure. For this purpose, a series of mechanical characterization tests and model validating experiments and computational simulations need to be performed. In this study, 8HS weave S-2 glass fabric reinforced with SC15 epoxy matrix composites has been characterized for MAT162 applications. Composite laminates of various thickness have been manufactured by hand lay-up method, cured at room temperature (RT) under vacuum and post-cured in an oven under vacuum. In-plane tension, quasistatic punch shear test (QS-PST), quasi-static punch crush test (QS-PCT), three-point bending, short beam shear and model validating low velocity impact (LVI) experiments were performed to determine the material properties and modeling parameters of 8HS S-2 glass/SC15 composites. Experimental damage modes and mechanisms have been quantified and used as input in validating the LS-DYNA computational models.
Reactive Molecular Dynamics Mechanical Properties Prediction of Furan Resin
During the reentry of aerospace vehicles into the earth’s atmosphere, the outer shell surface temperature can reach up to 2700°C, which would melt or degrade most materials. The high temperatures that aerospace vehicles face during reentry mean that these vehicles need a thermal protection system (TPS) to shield the rest of the structure and occupants. There are many categories of thermal protection systems and many materials have been used over the years, but the most notable are carbon-carbon composites (CCC). CCCs are usually manufactured by curing a polymer in a fiber preform and then heat-treating the composite until all non-carbon atoms are burnt out. Due to the complexity, it is desired to model the polymerization and carbonization process to fine-tune composite materials. The first step in modeling a CCC involves the polymerization of precursor material, and an atomistic model is to model the polymerization. Therefore, reactive molecular dynamics (MD) has been used to model the polymerization of precursor material. The precursor material selected for benchmarking and validation is furan resin (polyfurfuryl alcohol – PFA). Furan resin has been of interest for CCC ablatives since the 1950s due to its ability to achieve relatively high carbon yields, which reduces the number of carbonization cycles. Furan resin has also found uses in adhesives, corrosion protection, fuel propellants, and foundry molds. In this paper, you will find experimental curing of furan resin and an MD modeling approach for polymerization of furan resin.
Punch Crush of Unidirectional Composites at Sub-Millimeter Length Scale: Experiments and Simulations
An experimental methodology has been developed to fabricate unidirectional (UD) S-2 glass/epoxy composite films at sub-millimeter length scale, and to study the micromechanical punch crush damage mechanisms of UD ribbons of width 1mm (machined from sub-millimeter UD composite films) under transverse compression loading. Quasi-static micro-mechanical crush damage mechanisms includes: (i) fiber-matrix debonding, (ii) non-linear large-deformation of matrix resins, (iii) punch-shear of fibers, (iv) crush of fibers under diametric compression and (v) crush of matrix resins. Modeling these micro-mechanical damage mechanisms are challenging. Finite element (FE) models of UD composite ribbons of sub-millimeter thickness have been developed by modeling individual fibers through the thickness, fiber-matrix interface debonding with zero-thickness rate-dependent cohesive elements, transverse fibers fracture with stochastic zero-thickness cohesive elements, and fiber crush is modeled by erosion of elements. Micro punch crush experiments on UD S-2 glass composites show formation of a sheared plug which undergo through-thickness crush damage yielding about 1.4 GPa crush strength. Micromechanical 3D FE model can predict this crush damage mode at a matrix erosion strain of 0.99.
Dynamic Behavior of Fiber-Reinforced Composites Under Triaxial Compression
Fiber-reinforced composites (FRCs) under transverse impact by bullets are demonstrated to be subjected to the multi-axial stress state. This study presents the dynamic behavior of unidirectional composites at confining pressure. An S-2 glass/SC- 15 composite laminate was manufactured by using a resin injection method and then sectioned into small cylindrical specimens. Optical microscopy was utilized for specimen characterization and the fiber volume fraction was measured. Dynamic experiments were conducted by using a conventional Kolsky compression bar modified by adding a radial and axial confining chamber. Prior to the dynamic loading, hydraulic pressure up to 50 MPa was applied to the two chambers simultaneously. The radial chamber enclosed the cylindrical composite specimen and applied the radial confining pressure. On the other hand, the axial chamber was added at the free end of the transmission bar, providing the axial portion of the hydrostatic pressure to the specimen. Once the triaxial confinement was achieved, a striker impacted the incident bar to apply a dynamic compressive load to the specimen. The specimens’ dynamic responses were compared with that without confining pressure. It is found that the peak strength of the composite increased as the confining pressure increased.
Low Velocity Impact on Plain Weave S-2 Glass/DER353 Composites with the Corner of a Cube and a Hemi-Cylinder: Experiments and Simulations
An experimental methodology has been developed to investigate the low velocity impact (LVI) damage behavior of plain weave (PW) S-2 Glass/DER353 composite laminate using a hemi-cylinder (HC) and the corner of a cube impactor. Ultrasonic Cscan images of the LVI specimens have been used to determine the extent of interlaminar delamination. LS-DYNA finite element (FE) models of the LVI experiments have been developed and simulated for different impact scenarios in conjunction with rate dependent progressive composite damage model MAT162. A Python code has been developed to reduce the experimental data and automatic determination of different LVI parameters to validate the FE models. In addition, another Python code has been developed to automate the processing of layer-by-layer damage modes and LVI simulation parameters to validate with experimental data. Computational models have been validated with LVI experimental force-time data which shows a good correlation. The relationship between computational damage prediction and LVI experimental damage has been established.
Effect of Sub-Laminate Stacking Sequence on the Transverse Impact and Perforation Behavior of Multi-Layer Soft-Ballistic Armor Pack
LS-DYNA computational simulations have been carried out to study the effect of sub-laminate stacking sequences on the transverse impact and perforation behavior of multi-layer soft ballistic armor packs (SBAP). A previously validated finite element model has been used to study the effect of transvers impact as a function of stacking sequence on the minimum perforation velocity and deformation cone. In this study, multiple stacking sequences have been assembled for an 8L-SBAP. Denoting the single layer [0/90] soft-ballistic sub-laminate as [β]SBSL (where β is the material angle of [0/90] SBSL with respect to reference material direction 1 or [0]), the stacking sequences considered are (i) Baseline Layup 1 – [0]8 SBSL, (ii) Layup 2 – [0]4 SBSL [45]4 SBSL, (iii) Layup 3 – [0]2 SBSL [45]2 SBSL 2, (iv) Layup 4 –[0]1 SBSL [45]4, SBSL, (v) Layup 5 – [0â„13â„26â„39â„51â„64â„77â„90]SBSL. Dynamic as the lowest minimum perforation velocity range. At the impact layer, the deformation cone initially has a diamond shape and becomes near circular over time for all stacking sequences. On the other hand, at the rear/back layer, there are 4 spokes for the baseline Layup 1 [[0]8 SBSL, and 8 spokes for the zero-forty five Layups 2, 3, and 4 while the helicoidal Layup 5 has 28 spokes.
Optimum Conversion of Design Optimized Fiber Paths to 3D Printable G-Codes
Topology and fiber path optimizations result in the ideal design of the shape and fiber placement, respectively, in composite structures subjected to certain loads and constraints. Advancements in additive manufacturing (AM) can enable such designs to be manufactured. Specifically, the use of continuous carbon fiber-reinforced plastics (CFRPs) in AM or automated fiber placement (AFP) allows for 3D printing of such topology and fiber path optimized designs. However, fiber path optimization methods generally result in a collection of fibers in loops (closed loops) that are impossible to print, and lines (open loops), which may be too short to print depending on the system. Additionally, placement of discontinuities, i.e., where a fiber path ends inside a part, can result in stress concentrations that degrade the part performance. This paper introduces an approach to automatically convert the collection of closed and open loops into printable set(s) of fibers. An additional optional consideration of stress concenterations can be provided to the algorithm, which is demonstrated using finite element analysis (FEA) for enhanced structural performance.
Out-of-Plane Displacements of Composite DCB Specimens Using Embedded Optical Fiber Strains
The use of polymer matrix composite materials in primary load-bearing structures has increased in the aerospace industry primarily due to their high strength-to-weight ratios and stiffnesses. However, composites are susceptible to delamination due to their low interlaminar fracture resistance, which can result in stiffness degradation, thereby decreasing the structural integrity of the part. Strains obtained from embedded optical fibers can be used to detect and monitor damages. Optical fiber strain sensors are lightweight, easy to embed, and offer higher resolution and data acquisition rates. In this study, double cantilever beam (DCB) specimens fabricated from Hexcel IM7/8552 carbon/epoxy prepreg are embedded with optical fibers. Outof- plane displacements of the DCB specimens were calculated using optical fiber strains and show excellent agreement with deflections measured using the DIC system.
A Technique for Real-Time Defect Detection of Composite Material Using Machine Learning and Transfer Learning
In this study, the aim is to develop a method that is capable of locating the defects in composite plates by using a minimum number of wires and contact points. The reason is that previously there was not a method that can be used to detect defects with a reasonable number of wires and connections. To do so, measurements are restricted to be done only on the edges of the composite plates to predict the location of the defect within the plate. In this work, Single-walled carbon nanotubes (SWNT) were mixed with epoxy resin. By doing so, electrical conductivity was introduced to the resin. The prepared resin is then incorporated with woven fiberglass fabrics to make nanocomposite plates. Probes to measure the electric resistances were placed on the edges of the plates. The 4-probe method was used to measure the electrical resistance between the probes. Due to the complexity of the electrical behavior of composites and having multiple numbers of inputs, Machine Learning (ML) and Deep Learning (DL) methods were used. Data Augmentation (DA) was used to increase the number of labeled data examples that are needed to train the Neural Network (NN) model. Coupled with DA, Transfer Learning (TL) was used. A simulation model of the grid of resistors was developed in LTspice software. In the simulation, the defect was represented by increasing the resistors’ value of the defected cell. The data from the simulation was used for the initial training of the NN and then the experimental data is used in the second stage of Transfer Learning to train and test the final NN. The model's performance in locating the defects is 78.57% while the precision is 2â€x2â€.
Integrated Flow and Stress Modeling for Infusion and Curing Process in Liquid Composite Molding
Liquid composite molding, such as resin transfer molding and vacuum-assisted resin transfer molding, is an economical composite manufacturing technique for largescale parts. Modeling of the flow phenomena during the infusion process and the stress build-up in the subsequent curing process is imperative to improve part quality and reduce the number of trial tests. Despite the abundance of literature in both flow and stress modeling, an integrated model that couples the flow and stress physics is lacking. In this work, we combined the state-of-the-art flow and stress models to establish such an integrated framework. An infusion flow model is developed with the commercial computational fluid dynamics software STAR-CCM+, which incorporates the submodels to account for flow front evolution, compaction, and resin reaction. Several stress-based models are implemented in ABAQUS to account for fabric draping, compaction, and curing-induced thermal and chemical deformation. To demonstrate the importance of modeling the coupled physics, we conducted three case studies to show (1) effects of draping on the flow front evolution, (2) effects of degree of cure advection during infusion on the curing-induced stress build-up, and (3) effects of flowcompaction coupling on the flow front and dry spot formation in vacuum infusion.
Phase Field Based Cohesive Zone Fracture Approach to Model Anisotropic Effect and Interface Fracture in Fiber Reinforced Polymer Composites
Among multiple damage mechanisms in fiber reinforced polymer composites (FRPCs), delamination is the major failure mode that occurs very often due to low interlaminar strength of these materials. Prediction of this failure mode through computational modeling is not straight forward. In this work we aim to use the phase field fracture method (PFF) to model interfacial fracture in FRPCs. In PFF, the crack is assumed as a diffused entity rather than discrete discontinuities. In the present work, a unified phase field based cohesive zone model (PF-CZM) has been utilized to characterize the interlaminar fracture of carbon fiber reinforced epoxy composite. A Double cantilever beam (DCB) geometry has been simulated for 0â—¦ fiber orientation to determine mode I interfacial fracture toughness. To meet the requirement, two laminas of unidirectional FRP were bonded together using an adhesive (resin rich region) for different adhesive layer thicknesses and the corresponding energy release rates are computed. The area method suggested by Whitney [1982] was used to measure the energy release rate (R-curve). The results show different GI values for different thickness of adhesive layer and remains within a specified limit. The peak load is also different for different thicknesses of adhesive. Prior to the DCB simulations, open hole tension (OHT) simulations for different fiber orientations (0â—¦, 45â—¦ and 90â—¦) were also performed for carbon-fiber reinforced epoxy composite to validate the PF-CZM model prediction with the experimental data available in literature.
Carbon Nanotube Reinforced-Epoxy Based Adhesives: Correlations Between Fracture Morphology and Chemical Functional Changes
This paper addresses the experimental correlations between failure mode morphologies and the chemical changes inside an epoxy-based adhesive nanomodified by carbon nanotubes. This “specialâ€ nanocomposite is under a combined loading. i.e., shear and peel stresses, commonly encountered into single lap joints under tension. An increase in intensity on FTIR spectra on chemical functional at wavenumbers ranges 750-835 cm-1, 1170-1250 cm-1 and 1450-1610 cm-1 are related to the ductile-like fracture morphology due to more molecular mobility. At meanwhile, the increase in intensity at 2950-3350 cm-1 wavenumber range is linked to brittle-like morphology fracture. The cohesive failure is associated to the ductile-like failure morphology, while the adhesive failure is related to brittle-like morphology fracture.
Novel Flexible-Matrix-Composite Pump with High Energy Efficiency
The paper introduces a novel efficient compliant-body pump: flexible-matrixcomposite pump. The proposed pump enjoys a very high pumping potential (relative ejected volume per stroke) and a high-energy efficiency at low frequency. The high pumping potential is attributed to the negative high Poisson’s ratio of the flexible composite material that comprises the pumping chamber’s wall of the pump. Two fluidstructure- interaction analyses have been conducted for the simulation of the pumping action of the chamber and for the evaluation of the pump’s efficiency: a novel lumped system, which takes into consideration the negative Poisson’s ratio and the coefficient of mutual influence effects, and a finite element (ANSYS Workbench 2021 R2) analysis. The work concludes that the proposed pump has a promising potential at low frequency applications: it enjoys a very high pumping potential (volumetric-ejection ability) as well as a high-energy efficiency.
Multifunctional Energy Storage Integration into Electrospun Epoxy-CNT Nanofiber Enhanced CFRP Composite Structure
This work presents and assesses a structural integrity concept for a multifunctional carbon fiber reinforced composite with an embedded lithium-ion battery. In order to find a better packaging strategy for embedding lithium-ion batteries at its core, we compared adaptable composite structures made of traditional carbon fiber reinforced polymer (CFRPs), air-sprayed, and electrospun epoxy-multiwalled carbon nanotubes (epoxy-CNT) enhanced CFRPs. The electrospinning technique is well recognized across the world as a versatile and cost-effective way of producing continuous nanofilaments. It was precisely applied to the prepreg surface to provide efficient interfacial bonding and adhesion between the layers. The mechanical and physical characteristics of CFRPs reinforced with electrospun epoxy-carbon nanotubes have been demonstrated to be superior to those of conventional CFRP prepreg composites. Simultaneously, the air sprayed epoxy-carbon nanotube enhanced CFRP provides more mechanical strength than conventional CFRP prepreg but less than electrospun fiber-enhanced composites. The new multifunctional energy storage composite (MESC) might be a design factor in terms of economic feasibility. These components also help to the battery's structural load-bearing implementation and effective load transmission without damaging the battery's chemical composition. MESC design validation, manufacturing procedures, and experimental characterization (mechano-electrical) are all investigated in this paper. The electrochemical characterization findings demonstrate that the MESCs function similarly to ordinary lithium-ion pouch cells without any external packaging and under all loading circumstances. The mechanical strength and stiffness of the MESC cells, especially the electrospun epoxy-CNT enhanced MESC, are tested in three-point bending tests. The results show that the electrospun epoxy-CNT enhanced MESC has a lot more strength and stiffness than traditional pouch cells and air-sprayed CFRP at a lower weight and thickness. This mechanical robustness of the MESCs enables them to be manufactured as energy-storage devices for electric vehicles.
Multi-Nozzle Electrospinning of Carbon Nanotube/Epoxy Submicron Filaments for Composite Reinforcement Applications
Nanocomposites are gaining tremendous attention in structural applications from the automotive to aerospace industries. In this research, we used multi-nozzle electrospinning using Lateral Belt Driven (LBD) approach to fabricate mass production of submicron thermoset epoxy filaments with carbon nanotubes (CNT) to enhance the mechanical properties of Carbon fiber reinforced polymer (CFRP). Electrospinning is one of the most versatile, low-cost, and well-recognized technologies for producing continuous filaments with diameters ranging from submicron. These Nanofilaments were precisely incorporated into the prepreg layers to improve adhesion and interfacial bonding. In this study, the deposition characteristics of the multi-nozzles were observed and analyzed to understand the fiber formation of each nozzle on the multi-nozzle (10 nozzles in 50 mm apart) platform, as shown in Figure 1. Figure 2 represents the summarized fiber diameters of the SEM images at 6,000× magnification from each nozzle while the electrospinning parameters were kept constant; Voltage: 17kv; nozzle gauge: 25G, working distance: 12 cm, and time of spinning: 5min. ImageJ software was used to analyze the SEM images and was plotted using Origin Pro software. CNT/Epoxy Fiber mean diameter was 128.3 nm ±35.4 nm resulting in a 29% improvement in Interlaminar Shear Strength (ILSS) of the multi-nozzle electrospun CNT/Epoxy enhanced CFRP laminates.
Cellulose Nanofibers (CNF) Reinforced Carbon Fiber/Epoxy Matrix Composite with Higher Mechanical Properties
The effect of the Cellulose Nanofibers (CNF) compositions, their morphology on carbon fiber, and subsequent mechanical properties have been explored in this work. The CNF composite nanofiber networks were introduced as interleave layers to improve the interlaminar shear strength (ILSS) of an epoxy/carbon fiber laminate composite. Dry carbon fiber was coated by different volume fractions of CNF (0.6wt%, 0.8wt%, 1wt%) through the sonication process. The CNFs volume fraction and delamination properties of enhanced carbon fiber reinforced polymer (CFRP) laminates have been studied. It is shown that when the dry carbon fiber was treated with CNF, the laminate shows greater mechanical strength in certain cases. The application of CNF composite nanofiber networks as an interleaved layer in an epoxy/carbon laminate increased the delamination resistance of the ILSS in both 0.8wt% and 1wt% CNF by 27.2% and 12.4% respectively, while compared to the neat control sample. This result suggests that CNF could enhance the delamination resistance of an epoxy/carbon laminate undergoing stress and deformation. This result is attributed to crack path modification, and load energy absorption by higher modulus CNFs reinforced nanofibers interleave in the laminate resulting in a higher shear modulus to the networks.
Substructure Damage Tolerancing in Carbon Fiber Composites Under Impact Fatigue
The service life of aircraft structural components often experience sub-catastrophic impact events, such as during launch and landing cycles or blunt impacts from ground service equipment. These occurrences lead to impact fatigue that can result in damage of the carbon fiber-reinforced composite structural components (CFRCs). Due to their stacked lay-up structure, internal damage may not manifest visibly on the surface as it could for a solid isotropic material. Consequently, it is critical to quantify subsurface damage accurately, including the link between impact energy, loading cycles and reduction in elastic stiffness parameters of composite structures for more rigorous service life predictions. A unique identification method to quantify impact fatigue substructure damage in the form of stiffness degradation is considered here. The method leverages deflectometry, a full-field optical method with high sensitivity to surface defects not visible to the naked eye. Coupled with the use of the Virtual Fields Method (VFM), this approach is demonstrated numerically through finite element ABAQUS simulations.
Experimental Validation of the Dynamic Molecular State of Water in Damaged Polymer Composites Using Near Infrared Spectroscopy
Safety has long been a key factor in the design, manufacturing and maintenance of products that are made from composite materials. The exceptional properties these materials exhibit compared to their metal counterparts is enabling widespread adoption across civil infrastructure, oil & gas, marine, automotive, and aerospace industries. But the lack of a definitive and accurate technique to predict damage progression in a polymer-matrix composite (PMC) during their service life continues to pose a major risk and creates a gap in the long-term integrity of the structures produced. Although there is widespread consensus regarding the deleterious effects of the ingressed moisture on the overall properties of a composite, recent studies have revealed that the inevitable presence of moisture in a PMC can be leveraged for damage characterization. This work aims to employ Near-Infrared spectroscopy for quantifying molecular moisture in polymer composites for submicron scale damage detection. Prior to moisture absorption, a drop tower was used to induce a barely visible impact damage (BVID) in the center of dry E-glass/epoxy specimens. Three different specimens were subjected to 1J, 1.5J, and 2J of damage, respectively. The NIR Nano EVM Spectrophotometer was used to obtain spectral scans between wavelengths of 900-1700 nm for each of the three damaged samples, as well as an undamaged sample, in their dry state. The samples were then exposed to moisture contamination via water bath, and subsequent spectral scans were acquired at consistent intervals of gravimetric moisture gain. The spatial variation of the moisture content was evaluated from the characteristic peak for water in the damaged samples at various levels of absorbed moisture. The absorbance area obtained from the NIR spectral shows quantitative values to represent increasing damage and spatial maps indicating different states of absorbed moisture in each sample.
Performance Impacts of 3D Slicers on Additively Manufactured Composite Joints
Topology optimization (TO) combined with composites additive manufacturing (AM) enables design of skeletal structures that present opportunities for weight savings in aerospace structures. Of critical importance in these structures are intersecting elements, or joints, that, if improperly designed, can be origin points for structural failure. This study simplifies TO joints to 4-member AM x-joints and investigates the performance impact of the slicing software and infill pattern on the joint. A mechanical test method was developed to evaluate x-joints in a two phase study. Phase I leveraged fused filament fabrication (FFF) of neat PLA in a screening study that sampled the available design space. Using the data collected in phase I, phase II produced additively manufactured composites via direct ink writing (DIW). Ultimately, slicer and infill patterns were recommended for the creation of AM composite joints that demonstrate high stiffness, repeatable maximum stress, and progressive damage. Preliminary mosaic style numerical simulations which accurately predict damage and material response were also completed.
Design of Composite Double-Slab Radar Absorbing Structures Using Forward, Inverse, and Tandem Neural Networks
The survivability and mission of a military aircraft is often designed with minimum radar cross section (RCS) to ensure its long-term operation and maintainability. To reduce aircraft’s RCS, a specially formulated Radar Absorbing Structures (RAS) is primarily applied to its external skins. A Ni-coated glass/epoxy composite is a recent RAS material system designed for decreasing the RCS for the X-band (8.2 – 12.4 GHz), while maintaining efficient and reliable structural performance to function as the skin of an aircraft. Experimentally measured and computationally predicted radar responses (i.e., return loss responses in specific frequency ranges) of multi-layered RASs are expensive and labor-intensive. Solving their inverse problems for optimal RAS design is also challenging due to their complex configuration and physical phenomena. An artificial neural network (ANN) is a machine learning method that uses existing data from experimental results and validated models (i.e., transfer learning) to predict complex behavior. Training an ANN can be computationally expensive; however, training is a one-time cost. In this work, three different Three ANN models are presented for designing dual slab Ni-coated glass/epoxy composite RASs: (1) the feedforward neural network (FNN) model, (2) the inverse neural network (INN) model – an inverse network, which maintains a parallel structure to the FNN model, and (3) the tandem neural network (TNN) model – an alternative to the INN model which uses a pre-trained FNN in the training process. The FNN model takes the thicknesses of dual slab RASs to predict their returns loss in the X-band range. The INN model solves the inverse problem for the FNN model. The TNN model is established with a pretrained FNN to train an INN that exactly reverses the operation done in the FNN rather than solving the inverse problem independently. These ANN models will assist in reducing the time and cost for designing dual slab (and further extension to multi-layered) RASs.
Proper Tensile Testing of Unidirectional Composites
Tensile tests are a basic characterization method for composite materials, but the specimens often do not fail properly. Obtaining reliable results in tensile testing requires avoiding stress concentrations near the grips. The material near the tabbed section is under longitudinal, transverse and shear stress concentrations, which leads to underestimated results and conservative design. This study therefore examines different geometries to find the best testing method that yields the maximum failure strain. The experimental results show that the novel arrow shape end tabs and continuous tab specimens allow reaching the highest failure strain value.
Reinforcement of Natural Fibers via Supercritical Fluid Infiltration of Nanoparticles
In recent years, consumer products have been increasingly utilizing sustainable materials to attempt to reduce the product’s carbon footprint. For example, the automotive industry has incorporated a variety of natural fiber polymer composites on vehicles in the last 20 years, including wheat straw in the Ford Flex and flax fibers on the Polestar Precept and the Porsche Cayman GT4 Clubsport. However, natural fibers exhibit lower strength and stiffness in comparison to synthetic reinforcing agents, such as glass fiber. In this work, the authors are developing a technique to improve the mechanical performance of flax fibers for use in structural composites. Supercritical fluids, including supercritical-carbon dioxide (scCO2), have been shown to swell and plasticize amorphous polymers, resulting in increased mass transport and absorption of additives. The weak intercellular region within flax fibers, commonly called the middle lamella, consists mainly of amorphous pectin. In this work, the authors hypothesize that scCO2 could be used to swell amorphous polymers in a fiber’s structure (e.g. pectin) and enable reinforcement with nanoparticles, resulting in fiber performance enhancement. Pectin films were created for proof-of-concept experiments and treated with scCO2 at pressures ranging from 1200-4000psi in the presence of titanium dioxide nanoparticles (TiO2). TiO2 nanoparticles were shown to be able to enter pectin films upon treatment with scCO2 for 24 hours. The same treatment process was used on dew retted, mechanically extracted flax fibers and after treatment for 24 hours, the average tensile strength of the fibers was improved by over 40%. Overall, this method of incorporation of nanoparticles within natural fibers could enable development of low-density, low-carbon footprint polymeric composites for use in structural industrial applications.
A Machine Learning Approach for Impact Damage Quantification in Polymer Matrix Composites
Largely due to superior properties compared to traditional materials, the use of polymer matrix composites (PMC) has been expanding in several industries such as aerospace, transportation, defense, and marine. However, the anisotropy and nonhomogeneity of these structures contribute to the difficulty in evaluating structural integrity; damage sites can occur at multiple locations and length scales and are hard to track over time. This can lead to unpredictable and expensive failure of a safety-critical structure, thus creating a need for non-destructive evaluation (NDE) techniques which can detect and quantify small-scale damage sites and track their progression. Our research group has improved upon classical microwave techniques to address these needs; utilizing a custom device to move a sample within a resonant cavity and create a spatial map of relative permittivity. We capitalize on the inevitable presence of moisture within the polymer network to detect damage. The differing migration inclinations of absorbed water molecules in a pristine versus a damaged composite alters the respective concentrations of the two chemical states of moisture. The greater concentration of free water molecules residing in the damage sites exhibit highly different relative permittivity when compared to the higher ratio of polymer-bound water molecules in the undamaged areas. Currently, the technique has shown the ability to detect impact damage across a range of damage levels and gravimetric moisture contents but is not able to specifically quantify damage extent with regards to impact energy level. The applicability of machine learning (ML) to composite materials is substantial, with uses in areas like manufacturing and design, prediction of structural properties, and damage detection. Using traditional NDE techniques in conjunction with supervised or unsupervised ML has been shown to improve the accuracy, reliability, or efficiency of the existing methods. In this work, we explore the use of a combined unsupervised/supervised ML approach to determine a damage boundary and quantification of single-impact specimens. Dry composite specimens were damaged via drop tower to induce one central impact site of 0, 2, or 3 Joules. After moisture exposure, Entrepreneur Dr, Raleigh, North Carolina 27695, U.S.A. 553 each specimen underwent dielectric mapping, and spatial permittivity maps were created at a variety of gravimetric moisture contents. An unsupervised K-means clustering algorithm was applied to the dielectric data to segment the levels of damage and define a damage boundary. Subsequently, supervised learning was used to quantify damage using features including but not limited to thickness, moisture content, permittivity values of each cluster, and average distance between points in each cluster. A regression model was trained on several samples with impact energy as the predicted variable. Evaluation was then performed based on prediction accuracy for samples in which the impact energies are not known to the model.
Effect of Negative Poisson’s Ratio on the Tensile Properties of Auxetic CFRP Composites
Carbon fiber reinforced polymer (CFRP) matrix composites have become increasingly popular across industries such as aerospace and automotive industries due to its outstanding mechanical properties and significant weight saving capability. CFRP composites are also widely known to be highly tailorable. For instance, different laminate-level mechanical properties for CFRP composites can be achieved by varying the individual carbon fiber laminar arrangements, among one of them is the Poisson’s ratio. Conventional materials have a positive Poisson’s ratio (PPR), visualize any conventional materials in a 2D block shape, when stretching that material in longitudinal direction, contraction follows on the transverse direction, whereas for materials with a negative Poisson’s ratio (NPR), stretching in the longitudinal direction leads to expansion in the transverse direction. Materials with NPRs have been shown to improve the indentation and impact resistances, when compared to equivalent materials with PPRs. However, producing NPRs could potentially compromise other properties, such as tensile properties, which has not been reported. The current work investigates the effects of NPR on the tensile properties of CFRP composites. Specifically, a laminatelevel NPR of -0.4094 in the in-plane direction is achieved through ply arrangement of CFRP composites using classical lamination theory (CLT). The non-auxetic counterpart CFRP composites are designed to produce an PPR of 0.1598 in the in-plane direction while simultaneously match their elastic moduli in three directions with those of the auxetic composites. Results show that the predicted tensile modulus and in-plane Poisson’s ratio were in excellent agreement with the experiment results. It was found that the ultimate tensile strength and failure strain or ductility of auxetic specimens were on average 40% lower than those of the conventional CFRP composites.
Rapid Curing of Epoxy Resin Using Self- Sustained Frontal Polymerization Towards the Additive Manufacturing of Thermoset Fiber Composites
The demand for lightweight and high-performance thermoset fiber composites, such as the carbon fiber reinforced epoxy resin composites, has been rapidly increasing in a wide variety of industries. However, thermoset composites require cross linking for curing and consolidation, which is time consuming and can often take several hours. Additionally, the associated capital, operation, and maintenance costs are immense. The major challenge in the additive manufacturing and repair of thermoset-matrix fiber composites is an issue with the in-situ curing. To address this challenge, one of the promising solutions is to use the frontal polymerization technique to significantly reduce the curing time, from several hours to only a few seconds, while simultaneously obviating the need for external heating sources. In this work, the frontal polymerization of the epoxy resin, i.e., one of the most used thermoset resins for fiber composites, is investigated. Specifically, the frontal polymerization is initiated by the ultraviolet LED light. Then, with the help of a thermal co-initiator, the exothermic heating released due to the photopolymerization triggers the thermal polymerization, leading to a selfsustained polymerization front to form and propagate through the epoxy resin. Preliminary experimental results on the effect of weight fraction of the thermal coinitiator on the performance of the frontal polymerization of epoxy resin are presented and discussed. Results include the temperature measurements, SEM images showing the surface morphology of the cured epoxy resin specimens, and the tensile properties of the cured epoxy resin. The tensile properties of the epoxy resin specimens cured using the frontal polymerization technique are also compared with those of a conventional thermoset epoxy resin.
Deep Learning Framework for Woven Composite Design and Optimization
Woven composites are produced by interlacing warp and weft fibers in a pattern or weave style. By changing the pattern or material, the mechanical properties of woven composites can be significantly changed. However, how a woven composite’s architecture (pattern, material) is related to its mechanical properties is still unclear. Thus, in this paper, we utilize Deep Neural Network to explore the relationship between 2D woven composite architectures and their corresponding mechanical properties. We propose Deep Convolutional Neural Network to predict in-plane modulus from a given weave pattern and material sequence. More importantly, we propose a Physics-Constrained Neural Network to predict woven composite architecture from in-plane modulus, which is an extremely complex problem. The results demonstrate that our proposed Deep Neural Network frameworks can effectively represent the relationships between woven composite architecture and corresponding in-plane modulus with much higher accuracy compared to existing frameworks. We anticipate our proposed frameworks will not only facilitate woven composite analysis and optimization process but also be a starting point to introduce Physics knowledge guided Neural Networks into woven composite analysis.
Gas Permeability of 3D Printed Thermoplastic Composites for Cryogenic Applications
Thermoplastics have shown promise as a choice of material for production of lightweight structures for cryogenic storage. To fully utilize thermoplastics for such applications, cryogenic fuel leakage through transverse cracks in these structures must be studied. Thermoplastic composites (carbon fiber reinforced PEEK and Nylon) were 3D printed using fused deposition modeling. Test specimens were thermally cycled from ambient (23ºC) to cryogenic (-196ºC) temperatures and gas permeability measurements were conducted at selected cryogenic cycles. Results show that carbon fiber/PEEK specimens had the lowest gas permeability after 50 cryogenic cycles with no through-thickness crack networks. The gas permeability of 3D printed thermoplastic composites was several magnitudes lower than the leak rate allowables for different launch vehicles. Tensile tests, post cryogenic cycling, revealed a reduction in the tensile strength and modulus of the 3D printed specimens with CF/PEEK having the best mechanical and permeability performance.
Lightweight Approach to SMC Composites: Nanocellulose Coated Glass Fiber Fabric
The focus of this study is to investigate how to lightweight SMC composites for automotive applications without compromising their performance. This is accomplished by replacing, at least partially, the heaviest materials such as the glass fibers (GF) or calcium carbonate (CaCO3) with nanocellulose or nanoclays. In addition, the chopped glass fibers are replaced by glass fabric in order to better control the location and orientation of the glass fiber reinforcement and thus engineer the mechanical properties. Unsaturated polyester resin (UPR) is used as the resin, and a pilot scale sheet molding compounds (SMC) is used to make the SMC. The composites are made by stacking plies of SMC layers in a mold, after appropriate conditioning of the SMC, and compression molding. The properties of interest are the tensile and flexural modulus and strength according to the corresponding ASTM standards and the density of the composites. The void content is also determined using acid digestion and scanning electron microscopy. The main goal is to replace traditional chopped glass fibers (GF) used in SMC with unidirectional glass fabric coated with cellulose nanocrystals (CNC). The reasoning is to enhance properties with a better UPR/GF interface and controlled fiber orientation while reducing density. The glass fiber fabric is coated with nanocellulose using a scalable spraying technique that leads to homogeneous coatings. The four different glass fiber fabrics that were used in this study vary in CNC coating amount. To understand the effect of the nanocellulose, the glass fiber content of all composite formulations was kept constant at about 30 vol%. In addition, to determine the mechanical properties of the composites, the viscosity was verified for all formulations to ensure processability using the SMC pilot line. SEM micrographs show the quality of the CNC coating on the glass fiber fabric. Water uptake of all composites was also determined. The expected results address design, processing, and testing challenges, and successes and failures. The question to be addressed is whether CNC coated fabric is significantly advantageous for SMC compared to randomly oriented, chopped GF.
Effects of Magnetic Alignment and CNT Agglomeration on Reinforcing Fracture Toughness of Polymers
Reinforcing composite materials with carbon nanotubes (CNTs) has the potential to improve mechanical and/or multifunctional properties due to their nano-size. Research has been done on using CNTs to reinforce the interlaminar strength of carbon fiber reinforced composites (CFRPs), but most of the previous work is about randomly oriented carbon nanotubes. Currently, one of the main challenges regarding CNT integration into polymers is mitigating their agglomeration and controlling their dispersion in the polymer matrix. By aligning CNTs with an external field, more tailored structure control can be achieved, and a better understanding of how CNT agglomeration and dispersion relate to external field application and CNT concentration is needed. In this work, we studied the effects of magnetic field magnitude, CNT concentration, and matrix viscosity on CNT agglomeration and morphology. We measured the fracture toughness reinforcement of epoxy-CNT nanocomposites at various CNT concentrations (0.1 vol.% and 0.5 vol.%), magnetic field magnitudes (no field, 180 G, and 300 G), and matrix viscosities (older epoxy-hardener system with higher viscosity and newer epoxy-hardener system with lower viscosity). Our results demonstrated that aligning CNTs with a magnetic field can lead to extra reinforcement when compared to using randomly oriented CNTs if the field magnitude, CNT concentration, and matrix viscosity are selected accordingly. The maximum fracture toughness reinforcement achieved with the higher viscosity epoxy-hardener system (~72%) was with 0.5 vol.% of CNTs with a 180 G field, whereas the maximum reinforcement with the lower viscosity epoxy-hardener system (~62%) was observed for the samples fabricated with 0.1 vol.% of randomly oriented CNTs. COMSOL simulations were also conducted to understand the behavior of CNT agglomeration and alignment at different field magnitudes and CNT concentrations, and were compared with the experimental results. To maximize CNT reinforcement, more work needs to be conducted to address the challenge of CNT agglomeration and dispersion control in a polymer matrix, such as a more in-depth study of how different field magnitudes affect fracture toughness improvement and new methods to improve CNT dispersion.
The Effect of Two-Way Shape Memory on the Healing of Poly (Ethylene-Co-Methacrylic Acid) and Polybutadiene Blend
Development in self-healing materials and smart composites has continuously improved for many decades and has given rise to many real-life applications with implications for engineering materials, structures, and human beings who rely on these technological innovations to further human endeavor. This study involves the use of intrinsic selfhealing ability of poly (ethylene-co-methacrylic acid) thermoplastic, known by its commercial name as Surlyn 9520©, and combined two-way shape memory effect with Di cumyl-peroxide (DCP) cross-linked polybutadiene elastomer to achieve crack narrowing and closure with subsequent healing of the polymer blend surface. The simple batch mixing process resulted in an immiscible yet compatible blend, determined by two distinct melting peaks from DSC characterization and FTIR spectroscopy analysis. Different blends ratios of 80/20, 70/30, 60/40, 50/50 were investigated and characterized. However, the 80/20 blend was chosen to demonstrate the significance of the two-way shape memory effect, where a material experiences elongation upon cooling and contraction upon heating to achieve crack closure and effectual healing. Two sets of samples were studied; control Sample known as 2A and 2B samples were one time programmed to about 300% strain. Self-healing, which is a function of the poly(ethylene-co-methacrylic) acid component of the blend, was established for both sets of specimens. The flexural properties from three-point bending test indicate that although both sets of samples achieved good healing efficiencies, the 2B programmed samples displayed better healing efficiencies than the control by 30%.
Design and Testing of an Additively Manufactured Self-Sensing Composite Material
The growing trend towards limited-life aircraft brings a host of new challenges for nondestructive evaluation of their condition. One approach is to use materials with integrated sensing which provide low-to-medium fidelity information for rapid decision-making. In this work, electrical impedance tomography is applied to additively manufactured polymer-matrix composite materials with leads and electrodes directly printed into the material volume. A computational study is presented that shows volumetric resolution of surface and sub-surface damage with embedded electrodes.
Effects of Transverse Compression on the Structure and Axial Properties of Polyethylene: A Molecular Simulation Study
In this paper, the effects of transverse pressure on the structure and axial tensile properties of polyethylene (PE) crystals have been studied using all-atom molecular dynamics (MD) simulations. In the MD simulations, the inter-atomic interaction is modeled by the modified adaptive intermolecular reactive bond order (AIREBO-M) force field. Hugoniot equation of state of the PE crystal is developed using isotropic compression simulations. To investigate the transverse pressure effects, both the pristine and defective crystals (i.e., crystal with chain ends, equivalent to fibril) are subjected to axial tensile loading at different levels of transverse pressure from 0.0 to 20 GPa, and the tensile properties are predicted as functions of transverse pressure. Simulation results show that the transverse pressure significantly affects the tensile properties of PE especially for the fibril models by intensifying the inter-molecular interactions and changing the damage modes from chain end slippage to chain scission. At the highest level of transverse pressure, the improvement in modulus is predicted to increase by 50% for both pristine and defective crystal. Tensile strength is predicted to increase by 44% and 290% for the pristine and defective crystals, respectively These predictions provide insight into the response of UHMWPE subjected to high velocity impact where strain rates and transverse pressure loading are orders of magnitude greater than quasi-static loading at ambient pressure conditions.
Low Velocity Impact Experiments of S-2 Glass-Epoxy Composites Under Different Environmental Conditions
S-2 glass-epoxy composites are used in damage tolerant structural applications such as military ground vehicles due to their high specific strength, stiffness, and energy-absorbing capabilities. Composites can be susceptible to delamination failure caused due to high interlaminar shear stresses when subjected to transverse impact loading. While fiber fracture, fiber pullout, matrix cracking, and delaminations are the major damage mechanisms, delamination is a significant energy absorbing failure mode in low-velocity impacts (LVI). LVI leads to a reduction of stiffness and residual strength, which is critical for structural integrity. To improve the delamination resistance, researchers have used various types of interlayers for composites subjected to impacts. In this research, LVI experiments are conducted on composites made using plain weave S-2 glass and SC-15 epoxy resin. Two types of specimens are tested, 'baseline' (without interlayer) and 'interlayer' (with thermoplastic interlayer UAF 472). A Dynatup 9200 drop tower with a hemi-cylindrical 12.7 mm impactor is used. The specimens are impacted (40J) at three temperatures, -55C, RT, and 76C. The stiffness before and after the LVI test is evaluated, and the influence of temperature and impacts on stiffness change is discussed, along with the mechanisms that cause the change in stiffness. The interlayer specimens have significantly smaller delamination areas, and the stiffness loss due to impact is also reduced (compared to baseline) at each temperature. However, since the properties of the resin and the TPU deteriorate at elevated temperatures, there is a drastic stiffness loss in interlayer specimens at elevated temperatures in the pristine, non-impacted samples.
Effects of Extrusion Rate and Post-Annealing on Mechanical Properties and Printing Quality of Additively Manufactured Carbon Fiber Reinforced Polyetherketoneketone (PEEK) Parts
The development of high-temperature fused filament fabrication (FFF) 3D printers has enabled the additive manufacturing (AM) of polymers and composites with relatively high thermomechanical properties. Among them is polyetherketoneketone (PEKK) reinforced with short carbon fibers (CF-PEKK). PEKK is a high-performance thermoplastic that belongs to the polyaryletherketone (PAEK) polymer family with excellent mechanical properties. In particular, it offers a glass transition temperature of ~140°C, a relatively high modulus that can be readily enhanced by carbon fiber addition, and specific strength comparable to aluminum alloys. Therefore, there is a growing interest in using CF-PEKK to replace metal parts. Low dimensional accuracy and resolution, high porosity, and poor inter-layer strength [1-3] have limited FFF parts to rapid prototyping and non-structural applications. This paper aims to investigate extrusion rate, a printing parameter, and post-annealing as a potential solution to reducing porosity and enhancing inter-layer strength in CF-PEKK printed parts. A 5% increase in the theoretical extrusion multiplier (EM) resulted in a 1.6% reduction of void content accompanied by a 30% improvement in the inter-layer tensile strength of CFPEKK coupons. The impacts of extrusion rate and post-annealing (in a salt-packed container) on the printing quality of CF-PEKK parts are also determined. No significant structural or dimensional changes were detected with the higher extrusion rate or annealing in salt. This paper provides a new understanding of mechanical properties, processing, printability of CF-PEKK, and their AM challenges.
The Effect of Process Parameters on First Ply Deposition in Automated Fibre Placement
Automated Fibre Placement (AFP) is widely recognised as one of the most advanced processes for manufacturing structural composite components. Understanding the process remains at the forefront of academic/industrial investigation due to the myriad of parameters that affect the quality of the deposited tape. A novel AFP testbench, which included a heated glass tool, was developed to aid in the investigation of the material behaviour underneath the roller during compaction. The material behaviour was captured by using a camera directed at the compaction region, where the data was subsequently analysed using a vision analysis technique during a post-processing step. The results indicate that the use of a glass tool can help in quantifying the tape spreading when subjected to varying process temperatures as well as identifying various defects and features that can arise in a typical AFP manufacturing cycle.
FEA-Based Failure Analysis of Post-Buckled Composite Multi-Hat Stiffened Panel Under Static Compression
The aerospace industry uses composite multi-hat stiffened panels for skins because of their high strength-to-weight and stiffness-to-weight ratios. However, laminated composites with initial flaws are susceptible to delamination under buckling loads. The goal is to ensure damage initiation occurs past the buckled state, only stable damage progression at loads below the ultimate compressive load, and debonding failure past the ultimate compressive load. This approach reduces weight and addresses a potential design review for future aircraft repairs. The need exists to better understand damage initiation and growth mechanisms in composite structures while assisting in the design, analysis, and sustainment methods. Teflon inserts simulate damage defects during manufacturing, while barely visible impact helps capture human error during manufacturing. This work shows the interaction between the skin-stringer and ply-ply separations at the post-buckled state for both defect events using Abaqus Virtual Crack Closure Technique (VCCT). The initial configuration for the Teflon case was to leave the Teflon region unbonded, and the initial impact damage region approximation came from the experimental data and was considered the initial configuration. When compared against the experimental data produced through the NASA Advanced Composites Project (ACP), the present model captured damage transition from skin-hat to ply1-ply2. The model validations were within ~5% of the experimental data.
A Partitioned—Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing
The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces the user to implement macro solver specific changes to the platform. In this work, a partitioned-task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and playâ€ capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.
Challenges in Additively Manufactured Thermoset Continuously Reinforced Composites
Continuously-reinforced composite additive manufacturing (CC-AM) is set to revolutionize the manufacturing and design of high-strength, low-weight structures. Longitudinal tensile strengths of CC-AM have been reported exceeding 1500 MPa with minimal porosity, making this system a candidate for scale-up and structural applications. However, there remain a number of morphological non-idealities that are unique to the CC-AM process that limit the performance of a complex AM build. These can be categorized into material non-idealities (fiber clustering, resin-rich zones, matrix quality) and topological constraint non-idealities (joint design constraints, minimum path radius, tow cuts). Furthermore, for UV snap-cured carbon fiber CC-AM, limited penetration of the UV radiation through the carbon fiber tow presents a challenge to achieving optimal in-situ curing. The present work lays out these challenges both in a general sense, with specific case examples for material built with the CF3D system (Continuous Composites Inc.) using T-1100 12K carbon fiber tows and a UV snap curing acrylate resin. Most of the issues highlighted are inherent to CC-AM, and so most of the recommendations for future development to mitigate the various non-idealities are expected to translate to other CC-AM technologies, such as those employing a thermoplastic polymer matrix.
Effect of Low Velocity Impact on the Compressive Load Carrying Capability of Thick Composites
The use of carbon fiber reinforced polymer (CFRP) composites in modern aircraft has become common as a result of the advantage in the strength to weight ratio the material provides. A limitation to using CFRPs on aircraft stem from their low resistance to low velocity impact (LVI) damage. In these instances, LVI causes barely visible impact damage (BVID) such that the indication of impact on the structure is barely noticeable. These impacts have the potential to generate fiber and matrix failure and cause delamination between lamina which ultimately reduces the compressive load carrying capability of the composite. This study performs an experimental analysis on the knockdown in compressive load carrying capability over a range of impact energies that produce BVID on thick composite panels of 40, 48, and 56 plies.
Damage and Failure Analysis of Ultra-High Temperature Ceramics (UHTCs) Subjected to Thermal Shock
In this study, the finite element analysis (FEA) software ABAQUS 2020 and the eXtended Finite Element Method (XFEM) were used to predict the crack initiation and propagation within a UHTC subjected to cold thermal shock from 2000°C to 20°C. Within the XFEM enriched region, the maximum principal stress damage criterion was implemented to capture the crack initiation, and an energy-based damage criterion was used for crack propagation. Two simulations were developed, one for zirconia diboride (ZrB2) and one for hafnium diboride (HfB2). Temperature-dependent thermomechanical and fracture material properties were used for both simulations. A convective heat transfer condition was applied to the models' exposed surface. The multiple crack initiation and propagation were captured by using several XFEM enriched regions. The results for both UHTCs showed that crack initiation began at the exposed surface of the geometry and propagated into the material in a fast and brittle manner. The study found that defining the UHTCs' material temperature-dependent properties for the cold thermal shock models produced faster cracking due to the embrittlement of the materials' elastic properties and the degradation of the fracture properties at high temperatures. The properties of the materials can be seen to degrade as the temperature increases.
Assessment on the Capabilities of ABAQUS and Ls-Dyna to Predict the Behavior of Laminated Composites Subjected to Low-Velocity Impacts
Composite materials have excellent in-plane mechanical properties. However, they have a low resistance to impact damage. Low-velocity impacts (LVI) produce barely visible impact damage (BVID) on the surface of the laminate but with the potential to produce significant internal damage, such as delamination and matrix cracking. Composite materials' impact damage evaluation still largely relies on experimental results rather than numerical simulations because of the material's multiple damage mechanisms. In an attempt to mitigate cost and time requirements for large-scale experimental studies, there have been significant strides toward enhancing computational simulations to incorporate and predict damage mechanisms observed in composite structures. However, current computational models have limitations in how they capture the impact response and damage spread in laminated composites. The present study compares the predictive capabilities of two commercially available software, ABAQUS and LS-Dyna, to assess their feasibility in capturing the impact response and damage spread on laminated composites. The computational responses will also be compared with the responses obtained experimentally. To the authors' best knowledge, there has not been any report in the literature that compares the predicting capabilities of these two softwares. IM7/977-3 graphite epoxy unidirectional laminates with a 32-ply layup [-45/0/45/90]4S were manufactured according to the ASTM D7136/D7136M-12. Drop weight impact tests were performed in an Instron CEAST 9350. The samples were subjected to LVI energies of 30 J. From each test, the contact force, displacement, velocity, energy and impact duration time were recorded to compare with the predicted responses from the computational models. To evaluate the internal damage area, nondestructive inspection (NDI) was performed on all the samples with X-ray. The objective is to compare the internal damage per layer of each experiment with the internal damage obtained from the ABAQUS and LS-Dyna computational models. For the ABAQUS model, the intralaminar damage (ply failure) model consisted of a continuum damage model, Hashin failure criterion, and a damage evolution model based on equivalent displacement. The interlaminar damage (delamination) was incorporated through a cohesive surface interaction with a bilinear traction-separation law. In the LS-Dyna model, MAT261 Laminated Fracture Daimler-Pinho material card was used as the intralaminar damage model. MAT261 is a continuum damage model with linear softening evolution based on fracture toughness. The interlaminar damage was incorporated through a Tiebreak contact algorithm with a bilinear traction-separation behavior. Preliminary studies have shown that the ABAQUS/Explicit model showed a good correlation with the experimental results in terms of contact force, impact duration time, and displacement. On the other hand, the LS-Dyna MAT261 material model underpredicted the contact force, impact duration time, and displacement. The extreme differences in the LS-Dyna simulation are attributed to MAT261’s algorithm requiring element deletion during the simulation to maintain stability. Therefore, the striker never rebounded and continued penetrating the laminate. Further impact energies will be explored with the ABAQUS computational model. For LS-Dyna, different venues need to be explored in calibration for MAT261’s material model to account for the element deletion’s energy loss or use a different material model.
Impact of Nonuniform Fiber Arrangements on Simulated Composite Transverse-Tensile Strength
Micromechanical models of fiber reinforced composites are becoming a main area of research because damage and failure often initiates at small scales. Microscale features such as fiber clusters and matrix pockets are thought to impact failure because they introduce localized stress concentrations and low stiffness regions where cracks propagate easily. The challenge in modelling these features is due to the fidelity required to capture local fiber to fiber interactions. In this study, a generator was used which can tailor microstructures to create fiber clusters and matrix pockets, while still maintaining a degree of randomness. Fiber clusters and matrix pockets were identified by using an algorithm which sorted and filtered neighboring fiber triads. Descriptors were calculated for each microstructure based on the area and number of clusters, as well as local volume fraction distribution. Microstructures were loaded using a reducedorder model which calculated strength and stiffness. Results show the relationship between generator inputs and descriptor outputs, as well as strength and stiffness.
Hyper-Velocity Impact Performance of Foldcore Sandwich Composites
A foldcore is a novel core made from a flat sheet of any material folded into a desired pattern. A foldcore sandwich composite (FSC) provides highly tailorable structural performance over conventional sandwich composites made with honeycomb or synthetic polymer foam cores. Foldcore design can be optimized to accommodate complex shapes and unit cell geometries suitable for protective shielding structures This work aims to characterize hypervelocity impact (> 2000 m/s, HVI) response and corresponding damage morphologies of carbon fiber reinforced polymer (CFRP) FSCs. A series of normal (0° impact angle) and oblique (45° impact angle) HVI (~3km/s nominal projectile velocity) impact tests were performed on CFRP FSC targets to understand the effects of projectile impact on redirected debris formation, and variable debris cloud expansion. HVI damage in FSC targets were assessed using visual inspection and high-speed imaging analysis. The results from the present study indicate that debris cloud propagation and expansion are strongly influenced by foldcore impact location/angle and open-channel direction. This work serves as a baseline study to understand HVI response of FSC targets and to identify critical FSC design parameters to optimize HVI mitigation performance.
Development of Single Case Studies for Micromechanics Damage Evolution in Unidirectional Composites
This study continues to further expand the methods utilized by the Air Force Research Laboratory (AFRL) to understand microscale damage evolution. The microscale test data collected here will be used to validate many multiscale modeling frameworks’ ability to accurately predict damage evolution in complex, heterogeneous microscale structures. Previous work has conducted testing of transverse compression (TC) pillars in scanning electron microscope (SEM) load stages allowing for the measurement of surface level strains while being loaded. The limitation of this approach is a lack of understanding how damage develops through the thickness of the pillar during loading. This work involved the fabrication of a transverse compression micropillar and the experimental test of this sample that visualized through thickness damage evolution in-situ. A post mortem tomography was conducted to fully analyze damage evolution in the micro-pillar to validate the planned framework would be viable for additional microstructural geometries. A complete examination of the pillar, a postmortem Nano-CT, and a preliminary methodology for evaluating multiscale models are presented within this work.
Characterization and Improvisation of Direct- Ink-Writing (DIW) Technique with In-Situ Electric Field to Print Highly Aligned Carbon Fiber/Epoxy Composite
An investigation is presented on direct-ink-writing (DIW) of carbon fiber epoxy composite with and without an electric field. Initial emphasis is focused on the importance of DIW and a common notion that DIW/3D printing aids in better alignment across a printed specimen. For this purpose, the DIW technique is utilized in printing a single filament dog bone specimen, and uniaxial tensile tests were performed on all printed specimens. Furthermore, the microstructure of the printed sample and the fracture surface of the specimens was performed using a high-resolution scanning electron microscope (SEM). It was found that the fibers adjacent to the surface of the printed specimens were highly aligned along the printing direction, whereas the fibers at the core remain mostly misaligned. This could be due to the high shear stress and higher change in velocity gradient of the ink at the inner nozzle wall, which leads to better alignment of the fibers along the print direction. However, very little or negligible change in shear stress and velocity gradient at the core of the ink filament at the nozzle leads to poor alignment of the fibers during extrusion. Thus, integrating DIW and the electric field was conceived, which could effectively be used to align fibers at the surface and the core of the ink filament during the extrusion of the ink. The in-situ electric field, in association with the direct ink writing fabrication (iEF-DIW) technique, effectively aids in controlling both in-plane and through-thickness properties of the composite by controlling the alignment of the carbon fibers. This fabrication technique could effectively replace most of the conventional as well as cumbersome methods that are used to orient/align fibers/fillers in the desired direction.
Flexural Performance of Hybrid Discontinuous Fiber Composites Made of Repurposed Aerospace Prepreg
The flexure properties of Discontinuous Fiber Composites (DFCs) made from repurposed aerospace prepreg are investigated. In this study, two platelet sizes with varying length and the same width are used. Three thicknesses are investigated along with hybrid laminates, which combine DFCs and unidirectional (UD) and textile tapes. The study showed that by increasing platelet length, the flexure properties increased by, on average, 37%, but the Coefficient of Variation (CoV) also increased by, on average, 47%. However, as the thickness increased the CoV decreased by, on average, 25% while the flexure properties did not change. By adding continuous fiber plies, the average flexure properties increased by 29-67%. However, there were cases where adding these plies increased the CoV of the modulus. This is due to fiber waviness caused by platelet motion during cure. This was mitigated by a precure routine and using a textile ply between the UD and DFC core. The precured and textile hybrids resulted in a lower CoV of the flexure modulus. On the other hand, the CoV of the flexure strength was always lowered by the addition of continuous fiber plies by 36-67%. A finite element model was developed which could match and predict the flexure modulus of DFC and hybrid specimen. The development of this model is of utmost importance to mitigate the need of extensive physical tests to validate parts made using DFCs. The experiments and computations showcase the excellent tunability of DFCs, and the immense potential this repurposing method has to reduce thermoset prepreg waste.
Effect of Shear-Tension Coupling on the Deformation Characteristics of Woven Fabrics
In this study, the deformation characteristics of plain-woven fabrics under shear and tensile stresses are studied numerically using a biaxial bias-extension test with a square fabric specimen and a cruciform fabric specimen. The fabric orientation is ±45o with respect to the loading directions. For both specimens, the tensile force FT in the vertical direction of the specimen is increased at a constant rate while maintaining a constant tensile force FC in the transverse direction. Both the shear angle in the central zone of pure shear and the shear stiffness of the fabric depends on the transverse tensile force. Numerical simulations are performed with different transverse forces and the shear strain in the central zone of the specimen is determined. The deformation patterns of the fabric under biaxial tensile loading are mapped. Various ratios of load application area to specimen size and different fabric sizes are considered with the goal of designing the test conditions that produce consistent deformation patterns.
Simulation of Debulking in Resin-Saturated Composite Prepregs Using a Pore-Pressure Cohesive Zone Model
Aircraft composite parts are commonly manufactured from resin-saturated thermoset pre-impregnated plies laid-up over a rigid tool and consolidated and cured in an autoclave. In many applications, autoclave consolidation alone is not sufficient to remove the air, or bulk, that has been entrapped within the laminate during layup and may lead to the formation of voids in the final part. Entrapped air at ply interface can also participate in the formation of ply wrinkles, especially in curved laminates. High bulk content in curved sections is associated with an excess of ply length material that builds up during the layup. During compaction, this excess ply length may be squeezed into a tighter radius, which might lead to ply buckling and formation of wrinkles. Wrinkles and voids may significantly affect structural integrity of composite structures and increase rejection rates in the production cycle. Debulking, or vacuum consolidation, has been a common practice extensively used by aircraft manufacturers to reduce the amount of air entrapped during the layup of composite parts prior to curing. Yet, the underlying physical principles governing formation of defects during debulking are not well understood. This work is part of the Office of Naval Research (ONR) project “Physics-Based Composite Process Simulationâ€ that seeks to fill the gaps in understanding the physical principles governing the formation and evolution of manufacturing defects. Recently, the authors of this work have introduced an approach for modeling debulking in resinsaturated prepregs where cohesive elements enriched with pore-pressure degree of freedom are inserted at ply interfaces, using simulation concepts originally developed for the analysis of hydraulic fracturing in geomechanics problems. Further improvement of the methodology combined the pore-pressure cohesive zone model with cohesive contact to capture the tacky behavior of the interface. This work presents a verification of the ability of the method to capture the physics involved during debulking at the coupon scale using a two-ply carbon/epoxy IM7/8552 debulk test specimen with a seeded wrinkle. The methodology is then further extended and verified at the element scale for the first time for simulation of debulking in a rotor blade grip test element.
Finite Element-Based Evaluation of Residual Stresses in Carbon Fiber-Reinforced Polymer (CFRP) at Microscale Using Fiber Push-Out Experiment
Residual Stresses that develop during manufacturing process of Carbon Fiberreinforced Polymer (CFRP) composites can have negative effects on material strength and fatigue properties. The ability to reliably represent residual stresses in the material microstructure may be essential for accurate prediction of composite material properties using numerical micromodels. In this work, a methodology that uses Finite Element Model Updating (FEMU) and experimental data from Fiber Push-Out experiments is presented for evaluation of microscale residual stress in CFRPs. Recently, Fiber Push-Out experiments with in-situ scanning electron microscope (SEM) imaging conducted by the authors on CFRP specimens revealed significant through-thickness matrix deformation/sink-in in the matrix-rich region after nearby fibers are pushed out, a phenomenon attributed to the release of residual stress after the fiber-interface is broken. To characterize and reproduce residual stress in the Push-Out test samples, a two-step approach is proposed. First, a microscale Finite Element Method (FEM) model is built based on the geometry of the Push-Out area. Second, an FEMU procedure determines effective matrix properties associated with stress build-up that will reproduce the matrix Sink-in value as measured experimentally. In this preliminary work, residual stresses are attributed to the development of thermal strains in the matrix during cool down, and an effective Coefficient of Thermal Expansion (CTE) property for the epoxy material is obtained from the FEMU methodology. FEMU results suggest that epoxy matrix’s common CTE (on the order of 50ppm/oC) is too small to explain the observed matrix Sink-in. Preliminary evaluations suggest high level of residual stress in matrix which might initiate and aggravate microstructure defects, and potentially interfere with fiber-matrix interface properties measurements using the Fiber Push-Out Experiment.
Two-Way Global-Local Coupled Failure Modeling with Rx-FEM
Fiber-reinforced composites are widely used in aerospace structures because of their high specific strength. However, the failure prediction in these heterogeneous engineered materials presents significant challenges due to the multiscale nature and interaction of the damage modes. The computational cost increases dramatically moving from coupon to element to subcomponent and higher levels of the building block ladder. Fine meshes and high-fidelity numerical models are necessary in order to achieve local accuracy but at the same time make the computations prohibitively expensive. The present work focuses on a practical approach, two-way global-local tight coupling, to allow users to setup the modeling easily and reduce the computational cost. This method can capture the global failure. Penalty connection method is used for tight coupling of the local and global regions. Multiple discrete damage modes are allowed in the local region. Two numerical examples are provided to illustrate that the two-way global-local tight coupling can effectively predict the local damage and the global response.
Effect of Controlled Local Microstructural Modification of Glass Fiber Epoxy Composites on Progressive Damage Propagation Under Tensile Loading
Advanced composite materials are defined by hierarchical, heterogeneous, and anisotropic behavior, resulting in complex, multi-scale progressive damage mechanisms, making failure predictions even under simple loading a challenging task. With the widespread usage of polymer composites for structural applications, holes, notches, and other geometric features are often needed for assembly and other functional requirements necessitating improvements to the local architecture around the holes to alleviate associated stress concentration effects. Multiwalled carbon nanotubes (MW-CNTs) when incorporated with epoxy matrix have shown to increase the open-hole tensile (OHT) strength of unidirectional glass fiber reinforced plastic (UD-GFRP) laminates by altering the inherent damage mechanisms. To assess the incipience of damage in MW-CNT modified UD-GFRP laminates, X-ray microcomputed tomography (CT) of the specimen before and after failure have been carried out in the current work. Future work is ongoing to perform in situ tensile testing assisted with X-ray micro-CT to have a better understanding of damage evolution in the specimens.
Generating Woven Textile Models with Induced Fiber Entanglement for Achieving Realistic Tow Fiber Volume Fraction
Meso-scale modeling can be an effective way to predict textile-reinforced composite performance when the geometry of the textile is known. Digital element fiber models can be used to obtain the textile reinforcement by allowing for the simulation of the manufacturing process of the textile to be replicated. While helpful, these textiles frequently become over compacted to a smaller than desired thickness due to the lower resistance an ideal unentangled fiber bundle provides to compaction. A bundle that contains entangled fibers as found in manufactured textiles provides greater resistance to compaction. A novel entanglement generation procedure was created to obtain textile geometry with higher resistance to compaction. To introduce fiber entanglement into a tow, select fibers are swapped with each other in the tow at a cross-section. This allows entanglement to be introduced after the basic textile structure is already made and prevents individual fibers from leaving the tow and getting entangled into neighboring tows. By combining artificial fiber entanglement with manufacturing process simulation, a method was developed to create fiber bundle models using entanglement to control the compaction behavior. This fiber entanglement process was controlled by three parameters, which dictate how many, how often, and how far away from each other fibers are swapped. The method was applied to a woven textile model, where it was found that increasing the amount of entanglement within the tows increased the compacted thickness of the textile under the same load. This method for artificial fiber entanglement and manufacturing process simulation shows the potential to control the compaction response of a textile by controlling the amount of entanglement introduced to the textile.
The Role of Semi-Curing in Liquid Composite Moulding
This study investigates how Semi-Cured interfaces form and preform in Liquid Composite Moulding processes in order to support the drive towards low cost and high rate manufacture of complex composites. A two-step program was devised. Firstly, the effect on neat resin toughness properties arising from additional thermal cycling needed for Semi-Curing was explored. This confirmed that the Semi-Curing process had little effect on plane-strain fracture toughness values. Secondly, Semi-Cured laminates with elements initially cured to varying degrees of cure were manufactured and tested in Mode I and Mode II. The results of these tests indicated interfacial properties are fully retained in Mode II and a reduction in Mode I is seen after the resin enters the post-gel stage. These initial results demonstrate the usefulness of Semi-Curing to integrate preforms up until the gel point of the material.
Moisture Influence on Viscoelastic and Thermal Properties of Additively Manufactured Syntactic Foams
Syntactic foams are lightweight structures extensively used in marine and aerospace applications as core materials due to their inherent buoyant nature and energy absorption capability. In addition to structural applications, syntactic foams find applications in microelectronics. However, exposure to moisture for a prolonged period will mediate moisture ingression into syntactic foams that will eventually degrade the structure and cause catastrophic failure. Despite its importance, most of the past research has focused primarily on experimental studies of mechanical property degradation of syntactic foams. In contrast, time-dependent property degradation due to moisture exposure is lacking. Such behavior of additively manufactured syntactic foams is not known. To address this knowledge gap, this paper focuses on elucidating the impact of moisture absorption on the viscoelastic and thermal properties of syntactic foams, particularly Thermoplastic Polyurethane (TPU) based syntactic foams. In this paper TPU based syntactic foams with 20% and 40% reinforced glass micro balloons (GMBs) are additively manufactured using selective laser sintering. To that end, the viscoelastic and thermal properties are measured in both pristine and water-aged syntactic foams. Dynamic mechanical analysis is performed at temperatures from -50 oC to 100 oC at 0.1% strain and 1 Hz. It was found that glass transition temperature increases with an increase in GMB volume fraction due to the effect of reinforcement, which hinders the polymer chain movement at the interface. The peak damping factor, which is representative of ???, is reduced by 5% in neat TPU and TPU + 20% GMB after the exposure due to plasticizing effect in TPU whereas no change is found in TPU+40% GMB foams. This is attributed to the majority of the moisture absorption occurring at the interface between GMB and matrix. The thermal conductivity of the neat TPU and TPU+20% GMB is increased by 8% after the samples are exposed to moisture due to the formation of thermal bridges when water molecule reacts with TPU matrix, however, it slightly decreased in TPU+40% GMB due to insufficient formation of thermal bridges as a result of insufficient matrix and hindrance from the reinforcement. Our results demonstrate that the thermal properties of the syntactic foams can be tailored based on our knowledge of their response to moisture and exposure time.
Force Field Parameterization and Molecular Dynamics Simulation of Epoxy Interaction with Boron Nitride Nanotube Surfaces
Wettability is a key phenomenon in understanding solid-liquid interface behavior in composite materials and is important in the manufacturing of boron nitride nanotube (BNNT)-based composite materials. Wettability is often quantified by calculating the contact angle values of liquid resin droplets on reinforcement surfaces. Determining contact angle values using experimental techniques for nanomaterials like BNNT is challenging and costly. Computational simulations with interface calculation capabilities offer an easier approach to solve this problem. In this study, a molecular dynamics framework is used to determine the contact angle values of various epoxy systems on the BNNT surface. The Interface Force-Field (IFF) was used for this study. Forcefield parameters were developed to describe the interaction of boron (B) atoms, nitrogen (N) atoms, and the pi electrons that dominate the out-of-plane behavior of two-dimensional B-N materials. A single layer BNNT surface was modelled as shown in “Figure 1â€. For wetting simulations, the selection of resin system is based on a combination of EPON 862 and EPON 828 monomers with aromatic amine hardeners and aliphatic amine hardeners. The results are dependent on the chemical groups present in the resin system, temperature, and the charges on the atoms in the functional groups. The EPON 828 systems show overall better wettability than EPON 862 systems irrespective of choice of hardener.
Correlating Structure to Damping and Stiffness in Graphene Oxide Films
Graphene oxide (GO) films have a great potential for aerospace, electronics, and renewable energy applications due to their low cost and unique properties. For structural applications, they can achieve an exceptional combination of damping and stiffness. This study investigates the effect of packing density, reduction, and water removal on stiffness and damping of graphene oxide films. GO sheets dispersed in water are passed through a filter and deposited on a removable substrate. Through variations of the film fabrication process, films of both GO and reduced GO (rGO) are produced with varying levels of packing. Heat treatment is also used to remove the water in half of the films. The degree of packing is assessed through film density calculations. Microscopy as well as Raman and X-ray spectroscopy are used to measure the degree of packing while Dynamic Mechanical Analysis (DMA) is used to quantity mechanical damping and storage modulus of specimens in tension. Correlating mechanical properties to structure of films revealed new understanding of damping and stress transfer mechanisms in these materials. Optimal structures resulted in superior combinations of stiffness (18 GPa) and damping (0.14), potentially paving the way for using GO based films in advanced structural applications.
The Determination of a 3D Length Scale Using Long Reconstructed Fiber Paths
Carbon fiber reinforced composites often exhibit large amounts of property scatter. Attempts at understanding composite property scatter have led researchers to generate many 2D models which ignore the 3D phenomenon of entanglement. Previous studies of entanglement have suggested it is correlated to a length scale, but have not had large enough samples to determine its size. In this study, fiber paths of long, entangled, continuous fibers were extracted from CT data of an automotive grade, heavy tow composite. Descriptive metrics of these fiber paths were used to quantify the entanglement as a function of position along the fiber direction. Using this data, several minimum length scales for capturing the behavior of multiple descriptors were determined. These length scales revealed where statistical representation of 3D fiber models provides superior information to that of 2D models.
Efficacy of Cellulose Fiber as Bacteria Carrier for Self-Healing Concrete and 3D Polymer Microstructure
Microcracks are known to occur at an early stage in constructions utilizing concrete thereby affecting its serviceability and increasing the cost of repair and maintenance. As a result, there is a growing need to use a microbiological crack-healing strategy to arrest and mitigate the impact of the microcracks. The microbial system's distinguishing characteristic is that it allows concrete to self-heal. This study addresses the efficiency of microbiologically induced calcite precipitation in increasing the durability and selfhealing of cementitious construction materials. The primary focus has been on developing a carrier to protect the bacteria from being crushed during casting and from the harsh environment. The results of the SEM examination demonstrated that cellulose fiber bacteria can live at temperatures as high as 160 degrees Celsius, as opposed to direct bacteria, which can only survive at temperatures as high as 60 degrees Celsius. On the 28th day of curing, the cellulose fiber bacteria exhibited a 25% improvement in split tensile and compressive strength over the control concrete. Furthermore, after 28 days, the Cellulose fiber bacteria self-healed up to 1.5 mm fracture concretes via wetdry technique and 2.5 mm crack concretes by induced method after 40 days. Fiber-Sphaericus bacteria capable of producing spores and 3D printed materials to grow bionic mineralized composites with ordered microstructure was utilized. Bionic composites outperformed the control microstructure by 50% in terms of specific compressive strength and fracture toughness, and they also self-healed a larger percentage of the lattice beam within 12 days. This study contributes towards the development of 3D-architectural hybrid synthetic living materials with live ordered microstructures.
Analysis of Progressive Damage in 3D Woven Composites Using Overheight Compact Tension and Compact Compression
The objective of the ongoing research is to understand the progressive damage and propagation of cracks in a 3D woven composite. This is part of a larger scale effort to understand the progressive damage response of notched tensile and compressive composites. The current effort has gone extensively into studying the response with unidirectional (UD) and traditional textile composites. This project specifically dives into a 3D orthogonal woven composite and is meant to bolster the ongoing effort with information on how binder fibers can change the dynamic crack path as it progresses from the notch throughout the specimen. A 3D orthogonal preform is infused with resin and tested using compact compression (CC) and over-height compact tension (OCT). 7 Samples of each are tested using a custom load fixture and loaded to varying values to capture damage at different stages of failure. Each sample is studied with digital image correlation (DIC) and X-ray Computed Tomography (CT). It is found that even with existing thermal cracks due to increased temperature cure, that the samples retain toughness and strength and show extensive plasticity.
Micro-Scale Process Modeling and Evaluation of Curing-Induced Residual Stresses in Fiber-Reinforced Polymers Using Higher-Order FE Models
This manuscript presents the analysis of the curing process of thermoset polymers to predict the cure-induced residual stresses at the micro-scale level. A phenomenological cure kinetics model is used to describe the polymerization process, while an instantaneous linear-elastic constitutive law is used to predict residual stress. The computational model leverages higher-order structural theories derived from the Carrera Unified Formulation. A ten-fiber randomly packed repeating unit cell is virtually cured using the proposed higher-order method. The predicted stress state is shown to agree with reference results based on 3D finite element analysis while achieving a multi-fold reduction in the computational effort.
Understanding the Strengthening Effect of Aramid Pulp as an Interlaminar Reinforcement for CFRP Composites Subjected to Low-Velocity Impact
Composite materials are used widely in aerospace and naval sectors due to fatigue resistance, corrosive resistance, tailorability, lightweight, and high bending-tostiffness ratios. However, one of their major drawbacks is their low resistance to impact damage due to their poor through-thickness properties. Low-velocity impacts (LVI) produce barely visible impact damage (BVID) on the surface of the laminates but can carry the potential of significant internal damage such as delamination, fiber breakage, and matrix cracking. This is extremely dangerous as the structure can fail catastrophically without any previous warning. The region between the layers of fibers is the interlaminar region, and it is a resin-rich region very susceptible to damage. Therefore, different interlaminar reinforcements have been proposed to increase the through-thickness mechanical properties of laminated composites. Interlaminar reinforcements exist primarily in two forms, 3D and 2D. 3D reinforcements look to enhance the through-thickness properties by penetrating through the fiber layers, such as stitching and Z-pinning. 2D reinforcements only strengthen the interlaminar region, without any perforation through the layers, such as nanotubes or nanowires. While there have been great strides in research of these interlaminar reinforcements, previous studies have suggested significant drawbacks. For example, the 3D reinforcements tend to decrease the in-plane mechanical properties of the laminate by changing the fiber volume fraction or breaking the fibers. In the case of 2D reinforcements, they could damage the fibers when the reinforcements are synthesized on them. In order to increase the through-thickness properties of laminated composites while mitigating the potential of previously mentioned detriments, Aramid (Kevlar®) pulp has been proposed as a potential interlaminar reinforcement. The objective of this project is to investigate the optimum quantity of Kevlar® pulp needed in carbon fiber reinforced polymer (CFRP) composites subjected to LVI to mitigate the damage during a LVI event. Varying degrees of reinforcement were examined through the pulp to resin mixture ratios. Specimens were categorized as 1x, 2x, and 4x, where 1x is the recommended ratio of Kevlar® pulp to resin, 1:15 by volume, specified by the manufacturer (FibreGlast), 2x corresponds to the ratio 2:15, and 4x corresponds to 4:15. Drop weight impact tests were be performed using an Instron CEAST 9340, with an impact energy of 5J following ASTM D7136/D7136M-20 standards. The impact responses were evaluated based on recorded data including time, energy, contact force, and displacement. Experimental results illustrated a correlation between increased reinforcement ratios and decreased stiffness observed in the specimen. Specimens with greater ratios than 1x experienced higher degrees of damage, lower peak forces, longer impact durations, higher displacements, and reduced bending stiffness. The decrease in stiffness is attributed to an increase in air presence during manufacturing caused by air being trapped within the microfibers during the mechanical opening.
Dielectric Analysis to Predict Moisture Absorption in Structural Composites: A Data-Driven Approach
Due to continual exposure to moist environment, environmental degradation is a major threat to structural composites throughout their service life. Impedance Spectroscopy (IS)/Broadband Dielectric Spectroscopy (BbDS) is a reliable nondestructive method that has been used in polymer industries for dielectric characterization of material. While moisture absorption causes irreversible changes in the polymer matrix composites, it also alters the electrical properties of the system which is detectable using BbDS. Since the physics that drives the change in electrical characteristics is driven by the modifications imposed by water molecules (whether free or bound), both events can be linked. A dielectric spectrum over a broad frequency range can give an accurate estimation of moisture absorption in structural composites. In this work, machine learning (ML) models (Discriminant Analysis (DA) and Support Vector Machine (SVM) with Principal Component Analysis (PCA)) were developed that incorporate the dielectric data from BbDS to predict the current material state due to hygrothermal ageing. The models not only can detect the presence of moisture in composites, but also can predict the current saturation state of the material based on their dielectric properties. It uses the dielectric spectra and composite’s geometry as features to train supervised learning classification algorithms. The ML models developed in this study shows high accuracy and efficiency in predicting the current moisture state of the composite test samples due to hygrothermal ageing.
Additive Manufacturing and Mechanics of Multiscale Architected Flexible Syntactic Foams
Polymer syntactic foam is a lightweight composite consisting of hollow particles, like Glass Micro-Balloons (GMBs) or cenospheres, reinforced in a continuous polymer matrix. Due to their inherent weight-saving characteristics and enhanced mechanical properties, these foams are attractive for use in aerospace and marine industries. Recent advances in additive manufacturing (AM) techniques have enabled the development of complex-shaped parts of syntactic foams and circumvents the need for advanced highcost equipment to produce these parts. Selective Laser Sintering (SLS) is a widely adopted powder-based AM technique used to manufacture 3D parts by sintering polymer powder, and unlike other 3D printing methods, SLS does not require support structures. SLS has been reported to generate a segregated matrix system when used with Thermoplastic Urethane (TPU) in a standalone manner. However, the introduction of GMBs to this manufacturing method has thus far not been extensively studied. Consequently, the influence of GMB parameters on the mechanical response of syntactic foam with a segregated matrix is not fully understood. In this work, we use SLS to fabricate and further investigate the mechanical performance of segregated TPU matrix syntactic foam with different grades and volume fractions of (GMBs). We show for the first time that GMB size drives internal microscale architecture within syntactic foams that manifest as counterintuitive macroscale mechanical responses. That is, GMBs with a diameter larger than gaps between the cell walls of the segregated matrix get lodged between the cell walls while those smaller tend to get lodged inside the cell walls of the segregated matrix. Because of this, larger particles increase the stiffness of the syntactic foams while smaller ones do not contribute to this significantly. On the other hand, larger particles with their lower crushing strength reduce the densification stress of the foam, whereas the foam with smaller particles with higher crushing strength behaved similar to pure TPU but with significantly reduced weight. Overall, we show that coupling hollow particle parameters with print parameters can enable the fabrication of 3D printed syntactic foams with hierarchical tailored architectures and functional properties. These findings can be adapted to the development and design of cores for lightweight sandwich structures in the marine and aerospace industries.
Experimental Calibration of Randomness in Additively Manufactured Continuously Reinforced Composites
This paper presents an experimental analysis of the uncertainty in physical and mechanical properties of fused filament fabrication (FFF) parts that are reinforced with continuous carbon fibers (CCF). The goal of this work is to quantify modulus uncertainty in composites specimens printed on a commercially available continuous carbon filament 3D printer. The specimens that are analyzed in this paper are fabricated of a nylon-based material as the thermoplastic matrix and CCF as the reinforcing material. The test specimens are designed with four unique set of stacking sequences, which are categorized as SS #1, a combination of symmetric 0°and 90°layers, SS #2, a combination of symmetric ±45°layers, SS #3, a combination of symmetric 0°, ±45 °, and 90°and SS #4, a combination of non-symmetric ±45°layers. In each category, a total of 15 specimens are manufactured through FFF. A load-unload tensile test is performed for each specimen using an extensometer and digital image correlation (DIC) for strain analysis. Elastic Modulus (Exx) values of the specimens are determined and compared within each specimen to analyze the uncertainty. Also, strain variability is analyzed among the specimens using the DIC results.
Effective Thermal Conductivity for Functionally Graded Materials
In this paper, an analytical approach is presented to derive the effective thermal conductivity of a composite reinforced by FGM (Functionally Graded Materials) inclusions of spherical shape. The composite consists of spherical inclusions made of FGM embedded in an infinitely-extended matrix phase subject to uniform heat flux at infinity. The thermal conductivity of the FGM inclusion is assumed to vary linearly inside the FGM. The varying thermal conductivity inside the FGM inclusions results in a temperature distribution in the composite. The effective thermal conductivity is derived based on the exact temperature solution for a single FGM inclusion and by employing the self-consistent approximation. The derived values are found to be within the upper and lower bounds of the rule-ofmixtures.
Investigation of Interfacial Properties of Flattened Carbon Nanotubes and Amorphous Carbon
In this work, Molecular Dynamics (MD) simulations are used to study the interfacial properties (interaction energy, frictional sliding resistance and transverse tension) of flattened carbon nanotubes (flCNTs) – amorphous carbon (AC) as a function of density of AC and flCNT-AC crosslinks. The ReaxFF reactive force field was used to develop the models and predict the interfacial properties.
A Multiscale Approach to Investigate the Effect of Temperature and Crystallinity on the Development of Residual Stresses in Semicrystalline PEEK
Thermoplastic Matrix Composites (TMC) are shown to have a considerable commercial interest in cutting-edge industries due to their superior mechanical and chemical properties and the resistance to high temperatures. During the processing, TMCs are subjected to a wide range of elevated temperatures involving different cooling and heating cycles which result in the development of internal residual stresses in the matrix. In semicrystalline polymers such as PEEK, formation of crystalline regions during the processing causes shrinkage in the matrix leading to generation of additional residual stresses. Optimization of materials, manufacturing and design of components reduces development cycle time and cost for future hightechnology applications of TMCs. It has been shown that manufacturing of TMCs has a huge impact on the microstructure of these material, which in turn control the in-service performance. Since the thermo-mechanical properties of composite materials are defined by phenomena at multiple length scales, to have precise estimation of these residual stresses, a computational approach is required to combine simulation tools at multiple length scale. In this study, a multiscale approach has been introduced based on the Integrated Computational Material Engineering (ICME) which integrates Molecular Dynamics (MD) and Finite Element Analysis (FEA) to predict the induced residual stresses during processing. In the first step, thermoelastic properties of semicrystalline PEEK are determined as function of crystallinity content at different processing temperature at nanoscale using MD and micromechanics modeling. In the next step, the evolution of thermo-elastic properties during the crystallization is achieved using computational and experimental data. These results will be used to estimate the induced residual stresses of composites at higher length scales. This two-scale approach will allow us to virtually characterize material properties and predict the residual stress state of composites during manufacturing as a function of processing parameters and investigate the effect of temperature and temperature history on semi-crystalline PEEK thermal-mechanical properties.
Rapid and Scalable Additive Manufacturing of Thermoset Polymer Composites
Additive manufacturing (AM) has recently been transformed into a robust manufacturing paradigm for rapid, cost-effective, and reliable manufacturing of fiberreinforced thermoset polymer composites. Among various AM techniques, direct ink writing (DIW) technique offers exceptional ability for constructing scalable 3D composite structures with a high resolution and rapid production rates. In the conventional DIW technique, composite parts are created by thermal post-curing of a thermoset resin ink in an oven at elevated temperatures to obtain a highly crosslinked polymer network. The long and energy-intensive curing processes often required for curing the monomer limits the applications of this approach to layer-by-layer printing of simple 2D geometries. In addition, the conventional approach is not suited to creating large structures, as the uncured material in the earliest deposited layers reaches a flow state, resulting in loss of print fidelity or even the collapse of printed parts. Alternative in-situ curing approaches during the printing process are promising for highrate and scalable AM of thermoset polymer composites. To date, a handful of AM techniques based on in-situ curing have been developed using UV-curable thermoset resins. However, these techniques are not yet applicable for creating structural components due to the poor mechanical performance of the matrix, as well as incomplete curing of the resin in the presence of light absorbing reinforcements. In this work, we present a novel technique that can realize fast and energy-efficient fabrication of high-performance polymer composites using a thermoresponsive thermoset resin system. Our technique involves feeding resinous inks filled with discontinuous carbon fiber (CF) reinforcements from the nozzle of a printing robot and directing thermal stimulus toward the extruded material. The thermal stimulus is configured to rapidly and locally heat the composite material and instantaneously rigidize the extruded material. Using our novel printing technique, we demonstrate AM of tall composite structures using conventional layer-by-layer printing, which is difficult to achieve using existing techniques. In addition, instantaneous and localized curing of the thermoset matrix resin allows for the manufacturing of freeform structures (in-air printing), eliminating the need for support materials and tooling. We have shown that we can manufacture fully cured, void-free, and high-performance composites with printing speeds up to 1.5 m/min without requiring postâ€treatment or postâ€curing steps.
Designing an Improved Interface in Graphene/Polymer Composites Through Machine Learning
The matrix-reinforcement interface has been studied extensively to enhance the performance of polymer matrix composites (PMCs). One commonly practiced approach is functionalization of the reinforcement, which significantly improves the interfacial interaction. A molecular dynamics (MD) and machine learning (ML) workflow is proposed to identify the optimal functionalization parameters that result in improved mechanical performance of a 3-layer graphene nanoplatelet (GNP)/ bismaleimide (BMI) nanocomposite. MD is used to generate the training set for a graph convolutional neural network (GCN). This article reports the MD methodology and an example mechanical response from a pull-out simulation. Upcoming work in the proposed MD-ML workflow for designing a nanocomposite with improved mechanical performance is also discussed.
A Data-Driven Mechanical Property Prediction in Epoxy/Glass Fiber Composite
Fiber reinforced epoxy based composite materials are widely used in aircraft, marine, and automotive structures to minimize weight and increase performance. Typically, the mechanical performance of a composite part has so far been inspected using destructive testing, which is both expensive and time consuming. The mechanical properties of a composite are influenced by the curing process and its parameters, particularly the mechanical tensile modulus of the polymer, which rises as crosslink density rises and is influenced by curing temperature and holding time. It is, however, critical to manufacture epoxy-based composites with a higher crosslinking density by using the proper and uniform curing temperature. After fabricating the composite part, the most important step is to inspect the mechanical strength. In this study, we have presented a non-destructive quality inspection technique by merging Broadband Dielectric Spectroscopy data with supervised learning algorithms to predict the tensile strength of the cured composite sample based on the sample’s dielectric state variables. Different samples were made using different curing temperature to ensure variability in tensile strength data. A total of 15 features based on the Dielectric characteristics of the sample has been used in the algorithm. In this case, a classifier algorithm has been utilized, which predicts tensile strength based on which subset it belongs to. Overall, an estimation of the mechanical strength can be obtained by measuring the dielectric characteristic using an AC current frequency sweep which is a time-saving and nondestructive procedure and fitting the data in a supervised learning algorithm.
Estimation of 3D Woven Design Sensitivities Using a Rapid Multiscale Analysis Technique
Highly-refined finite element models of three-dimension (3D) woven composite systems currently require excessive computational demands that limit their use in sensitivity analysis, uncertainty quantification, and optimization. An alternative analysis methodology was developed using the NASA Multiscale Analysis Tool (NASMAT) where multiscale models of a 3D woven composite (including inter-tow matrix voids and constituent failure) can be completed on a single central processing unit (CPU) on the order of ~30 s. To develop inputs and validation data for the NASMAT model, coupon and acid-digesting testing and x-ray computed tomography were performed. The NASMAT inputs were parameterized using a set of 25 input variables and distributions. These inputs were randomly sampled to generate a total of 100,000 NASMAT analyses that could be used to understand the influence of different material and geometric properties on the warp and weft-direction stiffness and strength. These analyses (including pre/post-processing) were performed in less than eight hours on a 120 CPU cluster. The computational efficiency of the NASMAT model enabled a sensitivity analysis to be performed, and dominant input variables were able to be identified. Key results were consistent with theoretical and experimental observations for the specific 3D woven system studied in this work.
Building and Breaking Carbon Composites with REACTER
Carbon-based composites have become indispensable materials in aerospace and other high-performance applications, yet obtaining a detailed, nanoscale understanding of their morphology and failure mechanisms using only experimental methods remains a difficult challenge. REACTER is a versatile computational modeling tool for atomistic molecular dynamics simulations designed to model chemical reactions at the speed and length scales of classical force fields. In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites: carbon nanotube (CNT) composites and carbon fiber reinforced polymers (CFRP). A network of CNTs was grown dynamically using the new ‘create atoms’ feature of REACTER. The CNT filler was embedded into a polyarylacetylene (PAA) matrix by simulated in situ polymerization to obtain the final composite model. To generate the second class of carbon composite, fully carbonized (graphitic) carbon fiber morphologies were created by the method of Desai et al. [1], but using the advanced reaction constraints framework of REACTER. Two fiber models were created, representing a circular carbon fiber core and a flat surface, and similarly infiltrated with resin to obtain the final CFRP structure. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third order DFT-based tight-binding simulations, via a reaction constraint on the total potential energy of the involved atoms.
Mechanical and Dielectric Modeling of Adhesive Bonded Fiber Reinforced Composite Single Lap Joints
Fiber Reinforced Polymer (FRP) composites have long since been dominating the structural materials industry due to its superior specific strength and its ability to be designed for desirable mechanical and electrical properties. Using this formidable class of materials as structural components lead to the need of joining and bonding them. Adhesive bonding of composite materials are preferred over conventional mechanical fasteners, rivets, welding etc. as these tend to weaken the structure by introducing additional sources of stress concentrations. However, the complexity from the anisotropy of FRPs and the added convolution of anisotropic (composite adherend) and isotropic (adhesive) interfaces poses significant challenge to properly evaluate and model the adhesive bonded joints of composites. Significant experimental investigations have revealed correlations of material state degradation with the dielectric state variable defined as Dielectric Relaxation Strength (DRS). Due to the lack of appropriately defined physics in commercial simulation software packages, modeling such behaviors were challenging. In this paper a phenomenological modeling approach is taken to simulate the evolution of dielectric properties with the degradation of materials state. Broadband Dielectric Spectroscopy (BbDS) tests were carried out while applying tension on the specimen. The experiment allowed for an in-situ measurement of dielectric property evolution with material state degradation. The experimental data obtained were used to formulate equations relating material’s mechanical properties with dielectric variables such as real and imaginary permittivity. These equations were inserted into the material model as constitutive equations and the evolution of dielectric properties with material degradation were simulated using an 1D Finite Element Analysis (FEA) model.
Investigation of Mechanical Properties of Composites-Based Sheet Lamination Additive Manufacturing Process
The Composites-Based Additive Manufacturing (CBAM) system is a novel sheet lamination process combining mats of randomly oriented carbon fiber (CF) reinforcement with thermoplastic matrix materials to fabricate composite objects. This study investigated the suitability of three ASTM test standards for tensile, inplane shear, and interlaminar fracture properties of two CBAM material systems: CF reinforced Nylon-12 (CF/PA12) and CF reinforced polyether ether ketone (CF/PEEK). The tensile, in-plane shear, and interlaminar fracture tests were well suited for the CF/PEEK material, though high variability was found in the interlaminar fracture response. The CF/PA12 material system exhibited high plasticity and evidence of a poor fiber-matrix interface. This was shown by fiber pullout in the tensile tests and the presence of voids observed on the in-plane shear surfaces. The interlaminar fracture test method was invalid for the CF/PA12 material due to a large process zone invalidating. These results show CF/PEEK to be a promising material system for the CBAM process while CF/PA12 requires further development.
Near Zero-Waste Manufacturing of Carbon Fiber-Reinforced Thermoplastic Composites
Organosheet composite scrap made from polyphenylene sulfide reinforced with long recycled carbon fibers was reprocessed to produce compression molding compounds. No additional polymer was added to the process, making this a demonstration of closed-loop recyclability in composites manufacturing. The recyclate, produced by hammer-milling organosheet trimmings, was sieved and the resulting particulate geometry was measured to predict the fiber length in the molded composites. Tensile testing of the composites revealed that high stiffness parts (tensile modulus greater than 13 GPa) can be achieved using particulate molding compounds, but that tensile strength was significantly degraded. Still, the isotropic molded composites exhibited a greater than 18.8% increase in tensile strength over the neat polymer. Evaluation of the composite microstructure via optical microscopy revealed that fiber packing played a significant role in the tensile strength of the particulate composites, indicating that microstructural heterogeneity should be avoided to maximize the properties of composites made of recycled organosheet waste.
Response of Microvascular Composites to In-Plane Shear Loading
Microvascular composites were manufactured with precise channel spacing aligned to and transverse to the fiber direction using a custom tool. Stainless-steel tubes and sacrificial polylactic acid were used to produce microchannels following the standard curing schedule with modification to the post-cure step. Optical and radiographic evaluation showed that the microchannels were well-aligned. Transverse microchannels yielded large resin “eyesâ€ and voids near the channels, as well as deformed the sacrificial PLA filament, while microchannels aligned to the fibers yielded undisturbed microstructures with circular cross-section channels. In-plane shear testing revealed that transverse microchannels cause a disturbance in the stress state of the composites when subjected to shear loading. Channels aligned to the fibers failed at the microchannels, though their penalty to the shear properties was small. This study shows that the shear properties of microvascular composites are comparable to those of neat composites, allowing for the addition of multifunctionality with little penalty.
Numerical Investigation of Shape-Memory Zirconia-Reinforced Metal-Matrix Composite for Energy Dissipation and High Temperature Applications
This paper aims to exploit the shape-memory behavior of zirconia in order to design a composite with enhanced strength, energy dissipation, and strain recovery upon heating. Zirconia is characterized by two properties: superelasticity and the shapememory effect. These unique features are achieved through the reversible phase transformation from a high-temperature tetragonal phase to a low-temperature monoclinic phase. This study examines the response of shape-memory zirconia-reinforced aluminum-matrix composite under mechanical and thermal loadings. Microstructural finite element simulations are conducted to investigate the impact of the yield stress of the matrix, as well as the volume fraction and the diameter of zirconia particles on the response of the composite. The results of this study show that shape-memory zirconia reinforcing particles contributed effectively to the strength enhancement. In fact, it is found that 50% zirconia volume fraction can improve the maximum stress and the energy dissipation by 76% and 38%, respectively, at 4% tensile strain. Furthermore, 23% recoverable strain can be achieved upon heating up to 700◦K. This work provides insights into the potential application of shape-memory zirconia as reinforcing particles for damping systems and high temperature actuation.
Micro Scale and Bulk-Level (Polycrystalline) Simulations of Boron Carbide for Ceramic Matrix Composite Applications
This study applied computational molecular dynamics (MD) to model crystalline boron carbide (B4C) using the Large-scale Atomic/Molecular Parallel Simulator software package. The Reax Potential Force Field was utilized at a strain rate of 107/s to evaluate micro-scaled mechanical behaviors of the material system. Then, the bulk– level (polycrystalline) behavior was evaluated using the relation between single crystal elasticity and the effective elastic behavior of polycrystalline materials. The simulations and analysis provide the link between the microscale and bulk-level performances of boron carbide, and the results at both length scales agree with the experimental data in the literature. The computational method can also be used to further develop strong and light-weight materials for aerospace, automotive, and military applications at relatively low costs of high-performance computational tools and higher throughput.
Effects of Graphene on Twisting of High Density Polyethylene
High density polyethylene (HDPE) is known to form banded spherulites when crystallized from the melt. In such spherulites, concentric bands of alternating light and dark colors emanating from the spherulite nucleation center are observable between cross polarizers and appear as a function of the anisotropy of the dielectric susceptibility as crystal orientations continuously rotate about the growth direction. Recently, we identified PE to be a promising compound to induce twisting in conjugated carbonaceous systems, such as triisopropylsilylethynyl anthradithiophene (TIPS ADT). When blended together in ratios between 10 – 70 wt.% PE, TIPS ADT and PE crystals twist in concert with one another to form composite films of intertwined helicoidal fibrils. In this work, we investigate crystal twisting in HDPE-graphene oxide composites. In addition to its unique multifunctionality, graphene has also recently demonstrated peculiar twisting capabilities that strongly alter its physical properties. Here, we first produce graphene sheets through the chemical oxidation of natural graphite, and then investigate the influence of graphene on the twisting of HDPE composites under various processing parameters (graphene concentration, polymer cooling rate, etc). HDPE-graphene composites have been prepared using melt extrusion in the form of microfibers and films. We measured the influence of twisting on the mechanical and electrical properties of the composites, as well as the crystallographic structure using optical and electron microscopy, and X-Ray diffraction spectroscopy.
Heated Additively Manufactured Molds for Thermoplastic Composite Automated Fiber Placement
Thermoplastic composite (TPC) tapes can be consolidated in situ via automated fiber placement (AFP) at relatively high temperatures (>250°C) and local pressures (up to a few MPa). In situ consolidation of TPC parts requires special tooling and heated molds to prevent warping. Creating complex three-dimensional (3D) molds at a low cost and in a short time frame can facilitate TPC AFP adoption and entry into new markets requiring customized parts. The industry standard for mold manufacturing is milling or bending metal stock (typically invar, steel, or aluminum). This process can be costly and have lead times upwards of two months. Additive manufacturing can shorten the lead times significantly. Additively manufactured molds, to be used by TPC AFP, should withstand high temperatures and roller pressures. Current mold generation practices do not have a method of heating the mold surface necessary for dimensional accuracy of TPC tape-based parts. This paper investigates a process to create 3D molds via fused filament fabrication (FFF), a form of material extrusion additive manufacturing (AM), and high-performance materials that can withstand the temperatures and pressures of thermoplastic AFP application. FFF offers customized parts quickly and at a low cost. A laser-assisted AFP robot performed a layup over two heated FFF molds made of short carbon fiber reinforced polyetherketoneketone (CFPEKK), a flat plate and one with a one-axis curvature. These specimens performed well with no noticeable permanent deformation of the mold caused by either the roller or the laser demonstrating the viability of this mold generation process to create 3D molds usable with TPC AFP.
Coupled Structural Thermal Analysis of the Defect Formation Process During CFRP Tape Layup
The Automated Fiber Placement (AFP) is the technology for automated layup of multiple narrow prepreg tapes in CFRP (Carbon Fiber Reinforced Plastics) manufacturing of structural components for aircraft. Because most AFP devices cut the material perpendicular to the feed direction, geometrically complex layup can result in localized gaps and overlaps that can affect the mechanical properties of the molded product. The bending modulus of prepreg tapes is the dominant factor for defect formation in the layup process. For the layup using CFRTP (Carbon Fiber Reinforced Thermoplastics) tapes, the material is heated during the tape layup and thus the temperature variation and distribution during forming have a large effect on the bending modulus of prepreg tapes [1]. In this study, we modeled the laminate with internal defects made by the AFP process, and we performed a coupled structural thermal analysis for the gap elimination when the out-of-plane pressure was applied, considering the temperature-dependent material properties of CFRTP. We showed a relationship between the bending stiffness of the layer above the gap and defect formation in CFRTP.
A 3D Thermo-Mechanical Analysis of Additively Manufactured Aligned Discontinuous Fiber-Reinforced Composites
This work investigates the effects of thermal residual stresses due to curing processes on the mechanical and failure responses of additively manufactured aligned discontinuous fiber-reinforced composites (DFRCs). A micro-mechanical framework is used for finite element simulation of damage and failure in the three-dimensional (3-D) representation of the DFRCs under both mechanical and thermal loadings. In this numerical framework, accurate constitutive equations are utilized to explicitly simulate the fibers, matrix, and fiber/matrix interfaces within the composite’s microstructure. All parameters of the micro-mechanical model are defined based on a recently developed 3-D printed aligned discontinuous fiber-reinforced thermoset. The coupled thermo-mechanical model on the commercially available nonlinear finite element software ABAQUS is used to accurately model the response of the studied DFRC when exposed to different curing temperatures and to mechanical loading. Intermediate fibers’ aspect ratios (FARs) and low fibers’ volume fraction are used, which are suitable for 3-D printed aligned DFRCs. The curing-induced residual stresses are then studied, and the effects of different curing processes on the onset of different damage types and on the stress-strain response up to final failure are predicted. Also, the effect of the perfect versus cohesive interfacial bonding on the DFRC’s performance is examined. This work reveals that the DFRCs’ responses are significantly affected when thermal residual stresses due to curing are considered, and therefore, provides guidance for better design, manufacturing, and analysis of such composites.
Evaluations of Shell and Solid Formulations for Progressive Damage and Impact Analysis Methods in Low Velocity Impact Applications
Progressive Damage and Failure Analysis (PDFA) has been shown to effectively predict damage initiation and propagation of composite materials at the lamina length scale when subjected to various forms of structural loading. The MAT299 composite damage model was developed by Boeing and LST/ANSYS and implemented as a native capability within the LS-DYNA explicit FEA suite under the Impact Damage Analysis Tools for Composite Structures (IDAT) program through the Air Force Research Laboratory in 2020. The material model was thoroughly verified and validated for low velocity impact events under the IDAT program using high fidelity ply-by-ply models. This work addresses the scalability of the MAT299 material model by investigating the effectiveness of thick shell elements implemented in an equivalent single layer scheme for low velocity impact of composite structures. Demonstrating the predictive capability of MAT299 with the thick shell implementation is a significant step toward applying PDFA methods at structurally relevant length scales.
A Novel Discrete, Mesoscale Modeling Framework for the Simulation of the Damaging and Fracturing Behavior of Composites
Unidirectional (UD) and 2D/3D textile composites are increasingly being employed in systems acrossed many industrial sectors including aerospace, automotive, and wind energy. This is due to the excellent specific mechanical properties and tailorability of composites, paving new avenues for structural optimization and weight savings. One of the challenges with the simulation of the mechanical response of composite materials is that their damage mechanisms depend strongly on the material micro- and mesostructures. Phenomena such as fiber micro-buckling and kinking in compression or fiber scissoring and matrix microcracking in shear in UD composites are only a few examples. Homogenized continuum models that describe these mechanisms are extremely mathematically complex, lack generality, and can only be used to fit experimental data. In fact, the constitutive equations compensate for not modeling fibers and matrix explicitly by introducing several complex equations and fitting parameters of unclear physical meaning. This makes model calibration extremely cumbersome and limits the predictive capability of the model. In reality, the modeling of damage and fracture in composite materials does not have to be complex if the physics of the micro-and mesostructures is simulated explicitly. This is the goal of the Discrete Model for Composites (DM4C), a novel discrete mesoscale modeling framework that simulates the mechanical behavior of UD and textile composites. Specifically, this framework is only based on physical laws and does not depend on element erosion to simulate fracture. As it will be shown in this presentation, in DM4C, fibers, groups of fibers, and tows are simulated explicitly as Timoshenko beam elements while the matrix is described by vectorial constitutive laws defined on the facets of a tetrahedral mesh anchored to the nodes of the beam elements. These vectorial laws describe both the elastic and inelastic behavior of the matrix, including the traction-separation laws governing the fracture process and the friction between facets governing the compressive behavior. Thanks to the facet-based formulation, fracture is modeled in a discrete way and the need for element erosion can be avoided. Furthermore, since fibers and matrix are now simulated explicitly, the constitutive laws of each material can be physics-based, simple, and with clearly defined material parameters. To demonstrate the predictive capability of the proposed framework, simulations of several typical damage mechanisms in composites will be compared to experimental data such as shear band formation in transverse compression, fiber micro-buckling and kinking in longitudinal compression, and sub-critical matrix microcraking in off-axis layers.
Discrete, Meso-Scale Modeling of Fiber- Reinforced Composites (DM4C): Application to Additive Manufacturing of Continuous Fiber Composites
This study presents the application of a novel, discrete modeling framework for composite materials made via 3-D printing of continuous fibers. Fiber tows are explicitly modeled as Timoshenko beam elements, and the matrix is represented via tetrahedral elements derived from the set of beam nodes. The constitutive law of the matrix is defined at facets which are generated from the tessellation process in the mesh. Vectoral representation of stress and strain on facets provides clear and physics-based material descriptions. A computationally efficient, robust, and highly parallelized scheme is provided to generate the 3-D printed composite parts, which can attain the fiber volume fractions higher than 60 %. The calibration result of the model applied to the 3-D printing composite materials is presented, which demonstrates the capability of the model in capturing the main damage mechanisms of 3D printed composites.
Discrete Modeling and Machine Learning Assisted Calibration of 3D Printed Carbon Fiber Reinforced Plastics (CFRP) Structural Joints
Over the past few decades, Additive Manufacturing (AM) has rapidly grown and has been very quickly adopted across a wide variety of industrial and academic fields. Although materials and structures manufactured using this technique are generally inferior in strength than those manufactured using traditional techniques, the many inherent advantages of AM still make it a great alternative to conventional composites. Fused Deposition Modeling (FDM) is by far the most widely used AM technique due to its capability to create complex parts by melting and extruding filaments of many different materials according to a specific and a-priori optimized pattern. With improvements in controls and robotics technologies, it is nowadays possible to deposit long continuous bundles of carbon fibers embedded in a snap-cure resin, allowing to greatly increase the strength-to-weight ratio of a complex structural joint where different layers of materials are thoughtfully and methodically placed to better react the loading conditions. The Discrete Model for Composites (DM4C), currently under development, is used to generate both simple and more complex joint structures, which will be calibrated using machine learning algorithms after computational results are gathered by a massively parallelized HPC code and stored in a Structured Query Language (SQL) database.
High-Speed Nanoscale to Macroscale Composite Prediction Tool Using Neural Networks
Material properties of carbon fiber composites were linked from the nanoscale to the macroscale via molecular dynamics simulations and finite element analysis. In particular, the study focused on predicting the properties of PAN-based and pitchbased carbon fiber composite specimen. The atomistic features that develop throughout the manufacturing process were captured within the molecular dynamics simulations, while the microstructural features and composite layup information were captured within the finite element analysis model. However, in order to obtain the desired material property values, a significant amount of modeling experience is required. Therefore, the purpose of this research was to remove the finite element analysis models by training sets of neural networks to quickly and accurately predict properties from the nanoscale to the macroscale. When compared to experimental data, the errors of the high-speed composite prediction tool were all less than 10%. Ultimately, this tool can provide a rapid analysis of different fiber manufacturing techniques and composite layups to provide insight and understanding on how to better tailor the properties of carbon fiber composites for various applications.
Deflection-Time Characterization on High- Pressure Impacted Thermoplastic-Metal Hybrid Panels
High strain rate events pose high levels of complexity when analyzing a materials deformation characteristics. In high strain rate events like blast and impact, understanding the damage progression within the tested material is crucial when optimizing material design to give a desired performance. Under extreme loading cases inertial effects play a large role on how a material system performs. When a structure is blast loaded and begins deformation, inertial effects cause the structure to continue to deform past its stressed equilibrium point even after the main front of the shock wave has passed until it stabilizes its inertial effects with the material’s strength. At the point of momentary rest, the inertial effects are zero, and the structure begins to rebound causing the structure to elastically “snap backâ€. This behavior may repeat and oscillate to release the energy that was transferred into it until remaining at rest at its plastically deformed state. In this work, high-pressure impact loading was implemented on a thermoplastic-metal hybrid panel via free piston shock tube. Finite element models, and pressure-time and deflection-time histories, were used to correlate the deformation characteristics to an applied blast loading. Deformation characteristics are obtained in real time during the blast test using fringe projection methods. To correlate and better describe experimental observations, finite element models were developed in LS Dyna for the blast apparatus and hybrid composite panel, and the results are compared to the experimental blast tests. The results show a lag in the deformation response within the material structure from peak loading to peak deflection of 0.5ms in both the model and fringe projection analysis. Furthermore, the deflection-time history between the model and fringe projection data show similar correlations behaviorally for the duration of valid testing.
Effect of Enzymatic Retting Conditions on the Diameter and Mechanical Properties of Flax Fibers
The current industrial method of extracting natural plant fibers, originally intended for their textile use, can degrade the inherent mechanical properties, making them difficult to replace e-glass fibers for reinforcement in polymer composites. Microorganisms during the initial dew/field retting step of fiber extraction process not only degrades the fiber-stem interphase bond constituting primarily pectin and lignin, but also degrades the structural components of the fiber such as cellulose, resulting in non-uniform technical fibers with poor mechanical properties. Also, current single fiber testing standards used for mechanical properties characterization of these fibers are suitable for assessing homogenous and uniform fiber properties correctly, which is not the case in natural fibers. In this study, the flax stems were treated with Pectinase Ultra SPL enzyme targeted to degrade the pectin bonds between the fibers and plant stem, without affecting the structural component cellulose. In this study, the size of technical fibers hand extracted from dew and enzyme retted flax are compared. The hand extracted enzyme retted stem fibers showed more uniform, finer diameters resulting in better tensile properties when compared with dew/field retted stem fibers. The improved properties are related to the diameter effect in which as the area of these fibers is reduced, the reduction of defects during the fiber extraction.
A General Dehomogenization Method for Beam Analyses
Traditional multiscale methods homogenize a beam-like structure into a material point in 1D continuum with effective properties computed over a structure gene (SG) in terms of a 2D cross-section or a 3D segment with spanwise periodicity. Such methods lose accuracy when dealing with real beam-like structures usually not uniform or periodic along the spanwise direction. Thus, traditional multiscale methods cannot be rigorously applied to these cases and some refined methods have been proposed to analysis beam structure featuring spanwise heterogeneity. However, those methods usually require specific geometries assumption, assume material to be isotropic and homogeneous, or only predict macroscopic behavior without detailed dehomogenization analysis for local stresses recovery. In our previous work, we proposed Heterogeneous Beam Element (HBE) based on Mechanics of Structure Genome (MSG) to analyze beam-like structures featuring spanwise heterogeneity. Despite more accurate in predicting both macroscopic behavior and local stresses than traditional methods, errors in local stresses predictions on the SG boundary are inevitable due to the invoked assumptions of boundary conditions. In this paper, we propose a general dehomogenization methods for beam modeling (GDMB) based on HBE to better predict local stresses when the macroscopic behavior from other beam models are available. The results show that GDMB improves accuracy of the HBE dehomogenization and provides accurate stresses predictions based on a beam analysis.
Design of Composites for Additive Manufacturing: Tailoring of Individual Lamina
The research and development of polymer composite materials for additive manufacturing (AM) is critical for potential applications in the aerospace, automotive, and construction industries. The properties of the additive manufactured composite component are highly dependent on factors such as slicing thickness, infill pattern, infill direction, infill density, and fiber volume fraction. An additive manufactured composite part fabricated with different infill directions can have the same density but an immense effect on the resulting mechanical response of the components. This study is focused on exploring the possibility of developing composite material parts with different material layering pattern within each lamina to obtain highly tailored mechanical properties that cannot be obtained in traditional laminated composites. The results show that additive manufacturing provides a versatile method for developing composites that cannot be developed by the traditional methods by tailoring the properties of individual lamina in multiple directions.
Deep-Learning Detection of Cracks in In-Situ Computed Tomograms of Nano-Engineered Composites
The deformation and damage development of nano-engineered composites have not yet been investigated in 3D, although it can provide a deeper insight into their damage behavior. To fill this gap, we perform a tensile test on a nano-engineered composite with in-situ X-ray micro-Computed Tomography (micro-CT). The composite is made from woven alumina fibers with grafted carbon nanotubes (CNTs) and epoxy. More diffuse damage seems to exist for the materials with CNTs compared to the baseline material. However, at such resolution where individual fibers are vaguely visible, grayscale thresholding does not accurately characterize the matrix cracks due to their small opening and low contrast with the material itself. Thus, we employ a deep-learning tool, called RootPainter, for segmentation of cracks with small opening in relation to the voxel size, in the 3D images. The results show that RootPainter can reliably identify these small cracks. In addition to the investigation of the mechanical performance of the nano-engineered composite, this study provides a novel and reliable method for the characterization of micro-cracks in in-situ tomograms of these composites.
Interlaminar Shear Behavior of UHMWPE Tensylon® Composites in Quasi-Static Mode II Loading
Ultrahigh molecular weight polyethylene (UHMWPE) film composite materials such as Tensylon® HSBD30A are useful for ballistic applications, but quantification of their interlaminar shear behavior is necessary to inform design considerations. This study investigates a double lap shear specimen to determine mode II interlaminar shear properties. Average shear stresses calculated from measured loads and relative displacements calculated from full-field displacement data obtained via digital image correlation are used to produce an approximate traction-separation law. For a representative specimen, interfacial shear strength is calculated to be 3.18 MPa, mode II critical energy release rate is 465 J/m2, and interfacial stiffness is 36.8 MPa/mm. The double lap shear specimen is found to be appropriate for approximating these values, but the potential for complex loading states caused by non-simultaneous crack growth necessitates further investigation into alternative specimen configurations.
Transverse Tensile Strength Prediction of Thermosetting Composites
The transverse tensile strength of composites is susceptible to size effects. Therefore, it is paramount to develop length-scale specific physical test procedures to validate computational models that estimate the transverse composite response using micromechanics. To this end, a computational process modeling and virtual mechanical testing framework are presented in this study to predict the transverse response of composite microstructures subjected to processing conditions. Informed by a comprehensive material dataset, the numerical model is shown to reliably predict the process-induced residual stress generation in composite microstructures and accurately evaluate its influence on their transverse strength prediction. A novel procedure to fabricate thin composite laminates from a single ply of carbon fibers and characterize their transverse tensile response is presented to validate the numerical model. The results show excellent agreement with the virtual test predictions. This study highlights the importance of length-scale specific testing to minimize the influence of size effect on the transverse composite strength.
Discontinuities in Aligned Discontinuous Fibers Composites: Microstructure Orientation Effect on Local Stress Concentration Factors
The complexity of the microstructure in composites has led to major generalizations when predicting the strength of composites. In recent years composite strength predictions have progressed by improving the fidelity of randomly packed unidirectional models. Taking it one step, further we created digital twin models of real microstructures for discontinuous aligned composites. In these models we evaluated the impact of the mean fiber direction on the local stress concentration factors. We found that the local stress concentration factors can vary 71% within a 20 ° range of rotation. Nonetheless, this variation is load dependent and will be reduced with load progression.
Remaining Challenges in the Application of High-Performance Computing to a Process-to- Performance Pipeline for Textile Composites
Predicting the performance of a textile composite based on a description of the mesostructure and parameters related to the processing that the textile experiences would provide many advantages. Multiple groups have made significant progress towards robust process-to-performance predictions and developed a pipeline of computational tools to perform the analyses. As more complex components and materials are considered, high-performance computing systems have been used to meet the increasing computational costs, but most tools do not effectively leverage modern HPC systems. This paper assesses a particular process-to-performance pipeline by measuring the computational cost at every step for increasingly large problem sizes. Critical limitations of each tool are discussed, and a perspective on how the pipeline may be improved to efficiently use HPC resources to perform more complex analyses is provided.
New Failure Criteria for Composite Materials and Structures
The paper presents new failure criteria which can be applied to brittle polymer composites. The criteria can be applied to specimens regardless of whether they have cracks, cutout, or none of them. The new criteria consist of two failure conditions, both of which must be satisfied if failure occurs at any critical location. The first condition is the stress-based failure criterion. This condition of failure determines potential failure locations. For failure to occur, not only a location but also its neighbor should possess criteria favorable to failure. The second condition is related to the neighbor condition, and it is the stress gradient-based failure criterion. This condition states that failure may occur when the cubic power of the effective stress divided by its stress gradient is equal to or greater than the critical failure value of the selected material. The second condition determines the failure path from the failure location. Laminated fibrous composites have different stiffnesses and strengths depending on the orientation of the layers. This paper proposes a way to predict failure strengths of laminates with different layer orientations containing holes if the failure strength is known for a laminate.
Quantitative Assessment of Imperfection Inclusion Techniques in Bistable Composites
This work aims at quantifying the effect of geometric imperfection on cured shapes and the postbuckling behavior of bistable composites. For this purpose, the effects of two different sources of imperfections on predicted cured shapes and postbuckling behavior are assessed. Comparisons are held against Koiter’s asymptotic theory and test results. These comparisons reveal the respective effects of imperfection sources on buckling and postbuckling behavior of bistable composites.
Optimization of FE Crashworthiness Model for Sheet Molding Compound (SMC) with Extended Strength Distribution Model and Machine Learning
Sheet Molding Compound (SMC) possesses good mechanical properties and manufacturing flexibility. Nevertheless, SMC exhibits large scatter in mechanical properties and large difference in strengths under different stress distribution or loading conditions. As a result, the classical modeling techniques based on the mean tensile strength tend to significantly under-predict the flexural responses in finite element (FE) simulations. Probabilistic simulations with a unimodal tensile strength distribution had limited success in improving the predictions. In this work, the statistical distributions of the elastic modulus, tensile strength and compressive strength were considered with bimodal Weibull strength distributions. An optimization procedure for probabilistic FE models using artificial neural network (ANN)-based machine learning (ML) algorithm has been proposed. This procedure was examined through correlating simulations with experimental results for the 3-pt bending case. A set of optimum parameters was determined and subsequently examined in probabilistic simulations of tension, compression, 3-pt, and 4-pt bending cases. Simulations with this approach yielded low errors for all 4 cases and the results reached the steady-state within 20-30 iterations.
Experimental Characterization of the In-Plane Shear Response of Woven Polymer Matrix Composites Under Intermediate Strain Rates
The need for advanced material models to simulate the process of deformation, damage and failure of polymer matrix composites (PMCs) under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. Experimental stress vs. strain curves are needed at different strain rates for progressive damage modeling of dynamic failure. Matrix-dominated deformation modes are particularly challenging as they exhibit nonlinear behavior and rate dependence. In particular, in-plane shear is known to exhibit significant nonlinear response due its matrix dominant deformation leading up to failure. The purpose of this work is to experimentally characterize the in-plane shear deformation response of woven carbon/epoxy fabrics under intermediate strain rates (10-1 to 100 s-1). For this work, plain weave carbon fabrics with 3k and 12k tows are manufactured by VARTM. Testing is done using a servo-hydraulic load frame and 2D digital image correlation (DIC) is used to obtain experimental stress vs. strain curves following ASTM D7078M. Comparison between quasi-static (10-3 s-1) and intermediate experimental stress strain curves show an increase in ultimate strength and no significant change in modulus with increased loading rate. Investigations into the development of areas of localized high strain are observed which are attributed to the growth of meso-scale fiber tows damage. Surface level measurements from DIC and qualitative observations from high speed camera imaging reveal that cracks initiate and develop in the matrix gap between tows and at fiber undulation regions of the plain weave. These then develop into bulk cracks that grow parallel to the load. Higher loading rates have shown increased strength under in-plane. In conclusion, 2D DIC and the v-notched shear test method was able to characterize rate effects under intermediate shear loading of woven polymer matrix composites deformation response. High resolution DIC reveals localized mesoscale strain inhomogeneity that plays a key role in the initiation and evolution of bulk fracture in woven composite architecture which was captured for well for the 12k tow material.
Investigating Effects of Fiber Layers in 3D Printed Carbon Fiber Reinforced Polymer Composites
The prominence of carbon fiber reinforced polymers (CFRP) has made advancements in many industries including aerospace, automotive, and sporting goods. Using additive manufacturing to produce the CFRPs allows prototyping complex geometries while keeping the structure lightweight and producing a high strength material. This work studies the printing parameters and flexural strength of 3D printed onyx based CFRP samples, looking at the effect of variable parameters affecting the carbon fiber layers. A Markforged Mark 2 3D printer, which utilizes a dual head print head, is used to print nine different configurations of the CFRP composite. Each sample consists of 24 layers of material with an infill of 50%, two wall layers, as well as four roof and floor layers. The configurations examine the extreme of three parameters with reference to the carbon fiber, being the fiber angle, number of fiber layers, and the position of the fiber layers. The carbon fiber print angle is printed with layers at 0Ëš, 0Ëš/45Ëš, and 0Ëš/90Ëš with the latter two switching between the respective angles for every layer of carbon fiber printed. The number of fiber layers are set to be either 4 or 16. The position of fiber layers includes all layers (excluding roof/floor); the two outer most layers (which are directly below/above the roof/floor layers); and the four middle layers of the sample. The 3D printed CFRP specimens are subjected to three-point bend test, and three samples are tested for each configuration. One sample is chosen from each configuration to undergo pre-test and post-test inspection using X-ray micro-computed tomography to examine any internal damages.
Novel Enclosed Delamination Injection Repair Process for Strength Restoration
Delaminations are a common damage mechanism that occurs on composite structures due to in-service impacts. Enclosed damages less than 50 mm in diameter are of particular interest for repair. Current practices for repair of delaminations include: cut out of the damage and applying a patch or doubler to the cutout site, or injection using a repair resin. The use of a bonded doubler repair is more invasive and requires a cutout that acts as a stress concentration in the area of the repair. Injection repairs have traditionally been a faster, less expensive way to repair composite delaminations. However, the aerospace industry has not accepted injection repair as a strength restorative process. Questions about quantifying delamination internal contamination and ensuring percentage of repair resin fill within a delamination have been primary reasons why injection repairs have not been credited with strength restoration. Development of a new quantitative internal surface cleaning, preparation and repair process for delaminated composite materials is required to provide justification for strength restoration using injection repair. Fabricating representative local delaminations was performed with a modified end-notch flexure (ENF) test. A unidirectional 24-ply panel was fabricated to simulate damage to laminates. Intentional contamination was introduced into the induced delamination of each panel type. Contamination removal and surface preparation using solvent and atmospheric plasma cleaning were completed on the modified ENF coupon and verified utilizing in-line monitoring with Quantitative Gas Analysis (QGA) and post processing inspection with Fourier Transform Infrared Spectroscopy (FTIR). A modified low-viscosity injection resin was developed and utilized to repair the post-tested ENF coupons. The modified epoxy exhibited comparable shear strength characteristics to un-modified neat resin while achieving a >97% reduction in viscosity. Each ENF panel type was assessed for Mode II fracture toughness (GIIc) of the parent material and repair of fractured coupons. Fractured coupons simulating an enclosed delamination were repaired: without contamination, with contamination, and after the novel contamination removal processes were completed. Mode II interlaminar fracture toughness was restored or increased when compared to control test groups for all coupons that were repaired or cleaned and repaired.
Design of Adhesively Bonded Composite Joints Using a Rapid Design Tool
The optimization of composite structural joints is an iterative process and a multiscale problem. High fidelity finite element modeling of joints with 3D woven and laminated materials can become computationally expensive. The aim of this paper is to present the applicability of a reliable analysis process for the optimization of the composite Y-joint (curved Pi-joint), to be used in an aircraft fuselage, using a commercial rapid joint design tool analysis optimization software. The rapid joint design tool was investigated as a substitute and/or complement to a finite element analysis software. A composite Pi-joint and a composite Y-joint were evaluated using the rapid joint design tool. Furthermore, two main preliminary parametric studies were performed to better understand the capability of the tool in predicting the failure load trends in the Y-joint. The parameters investigated were the joint curvature and the laminated skin thickness. Failure loads are found using interactive stress-based criteria. Lastly, the Y-joint modeled using the rapid tool was validated against experimental results with an agreement of less than 10% of the experimental value reported.
Ultrasonic Guided Waves Defect Signatures for Damage Identification in Composite Aerospace Structures
Damage growth and tolerance are major drivers to determine the frequency and cost of inspections and the lifespan of structures. The detection and identification of damages together with the assessment of structural integrity by non-destructive evaluation (NDE) methods is of fundamental importance and requires analysis towards effective solutions. Among the numerous NDE techniques, ultrasonic guided waves (UGWs) are acknowledged as one of the most effective tools to identify damage in composite structures, offering promising results and research opportunities for their nonattenuative nature and complex behavior. Generating from a well-defined interaction of ultrasonic waves with bounded media, UGWs become “naturallyâ€ supported from the structure itself and show high susceptibility to interference on a propagation path (i.e. damage or boundary) providing many advantages as large-area coverage, crosssectional area inspection, sensitivity to multiple defects and cost-effectiveness. The implementation and interpretation of UGWs, though, are very challenging, due to the infinite set of mode-frequency combinations to probe structures with. The propagation of UGWs into composite materials (multilayered, anisotropic), aircraft geometries (thin uniquely shaped components, i.e. curved skin, stiffeners, etc.) and interaction with composite impact damage (3D, highly heterogenous, load-structure dependent) add layers of complexity, as wavemode conversion and coupling, and nonanalytical solutions. More studies are needed to advance knowledge in UGWs interaction with specific composite damage modes to fully exploit the potential of this advantageous yet complex inspecting modality. Building on the experimental results of UGWs inspection by transfer function extraction in damaged aircraft panels, this work focuses on the analysis of UGWs measurements to identify impact damage signatures in a variety of impact damage energy levels and on two panel locations.
Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification
Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including 1semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.
The Effect of Ply Waviness on Damage Initiation and Growth in Composites Under Fully Reversed Cyclic Loading
This paper presents results of an experimental investigation of composites with embedded ply waviness defects subjected to cyclic loads. The aim is to investigate the influence of ply waviness defects on the initiation, interaction, and evolution of fatigue damage mechanisms. The composite laminates with ply waviness are tested in a four-point bend sandwich beam configuration. Fully reversed fatigue testing until failure and interrupted fatigue testing were conducted, and the sequence of fatigue damage mechanisms was studied via digital image correlation analysis. Results showed that during fully reversed cyclic loads, shear strains localize at the ply waviness region, which amplifies the stresses in surrounding plies. The failure mechanisms near the defect include delamination, matrix cracking, and ply splitting. However, at small ply waviness amplitudes, failure did not initiate at the defect but at other sites in the laminate where the strength was locally reduced. In these laminates, failure mechanisms due to microstructural defects compete and dominate the fatigue failure mechanisms at regions of ply waviness defects.
Adhesively-Bonded Metal-CFRTP Bi-Materials: Enhanced Crack Growth Resistance Via Plasma and Quantified Fracture Via Size Effect Method
This work investigated air plasma effect on the Mode I crack growth resistance of adhesively-bonded metal-CFRTP dissimilar joints by using aluminum alloy (AA6061) and short-carbon-fiber-reinforced polyamide 66 (CFRPA66) as an example, and the Double Cantilever Beam (DCB) fracture testing as an evaluation method. The results showed that air plasma treatment can improve the fracture resistance of adhesively-bonded AA6061-CFRPA66 dissimilar joints with 140% enhanced Mode I fracture energy in maximum compared to non-treated ones. The quantified fracture energies from size effect method for both non-treated and plasma-treated cases are geometry-independent, whereas this is not true for modified beam theory causing geometry-dependent results. The foregoing improvement was confirmed from the failure surface morphology of plasma-treated specimens, showing fibers peeling off from CFRPA66 surface due to plasma-enhanced bonding between CFRPA66 and adhesive by the formation of covalent bonds at their interface. This study demonstrated air plasma as an efficient surface modification method to enhance the fracture resistance of adhesively-bonded metal-CFRTP dissimilar joints, and size effect method as a characterization method to properly quantify their fracture properties. These aspects are valuable in the area of multi-materials joining.
Finite Element Modeling for Compression Strength Prediction of Honeycomb Cores with Geometric Imperfections Measured Using X-Ray CT Imaging
Aluminum honeycomb cores are used in composite sandwich panels to achieve high bending rigidity while maintaining low weight. Geometric imperfections arise in the walls of metallic honeycomb cores during manufacturing, which affects their compression and impact response. This paper presents finite element modeling of metallic honeycomb cores with measured geometric imperfections. The honeycomb cores are modeled using shell geometry reconstructions of images of cores obtained using X-ray Computer Tomography. Flatwise compression responses of the cores are computed using finite element analyses of honeycomb cores for different representative volume element (RVE) sizes and boundary conditions. It is found that the compression response of the 10x11 cells RVE models can be predicted by the average of single RVE cell models sampled from the 10x11 cells RVE domain. However, this requires appropriate choice of boundary conditions. The non-periodic nature of the imperfection and the variation in geometric imperfection in the double and single thickness walls of the honeycomb core cells lead to interactive buckling of these walls and mode jumping during the amplification of initial imperfections under compression. These interactions play a significant role in the compression response and, therefore, the RVE size and boundary condition choices made should ensure this interaction are accurately captured.
Validation and Impact Response of Laminated Glass
Although glass has been used extensively in the course of human history, glass as a laminated structural component is a much more recent invention that came at the start of a burgeoning automotive industry, and to date, has not advanced significantly over the past few decades. One of the major challenges is extracting the material properties in order to predict failure under various loading conditions. We aim to address this shortcoming by examining the laminated glass system as a single unit via select tests designed to provide the necessary material constants and the validated load setup at the same time. To achieve this goal, we will use relatively large-size specimens (800 x 800 mm2) in both static and dynamic testing for loading perpendicular to the surface. These will be supplemented with additional tests in bending and tension and all tests, all of which can be used for finite element validation. Preliminary data shows good agreement in both static and dynamic analysis without requiring additional constituent level material tests. However, as this work is on-going, we anticipate better results with improvements to the methodology. Ultimately, this work is designed to provide a simple framework with relatively few instruments to support finite element validation efforts on laminated glass composites under dynamic loads.
Numerical and Experimental Investigation of Heat Transfer During Composite Fused Filament Fabrication
Additive manufacturing of fiber-reinforced composite materials enables production of parts with high specific stiffness and strength. Several manufacturers have released their versions of composite 3D printers with the most popular being Markforged® which relies on fused filament fabrication (FFF) process. This paper focuses on numerical and experimental investigation of heat transfer in composite specimens produced via the FFF manufacturing process. The experimental setup combines the Markforged® Mark Two™ composite 3D printer and the FLIR thermal camera. The camera is used to collect full field temperature history of a cylindrical composite specimen 12.7 ð‘šð‘š × 25.4 ð‘šð‘š (ð‘‘ð‘–ð‘Žð‘šð‘’ð‘¡ð‘’ð‘Ÿ × â„Žð‘’ð‘–ð‘”â„Žð‘¡) manufactured using composite filament Onyx™ consisting of nylon matrix and chopped carbon fibers. The thermal data is used to validate three-dimensional finite element simulations of transient heat transfer during the filament deposition process. Two approaches are used for the numerical simulation: “element-by-elementâ€ in which elements are activated in sequence following a realistic deposition path, and “layer-by-layerâ€ in which all elements of a layer are activated simultaneously and then allowed to cool. The latter approach is more computationally efficient. Micromechanical homogenization is used to estimate the effective conductivity values of the fiber-reinforced Onyx™ filament. Full-field temperature distribution and path plots are generated via both numerical approaches and from experimental data. The element-by-element approach appears to be capable of predicting the experimentally observed temperature distribution below the most recently deposited layer.
Numerical Modeling of Ultrasonic Assessment in Additively Manufactured Composite Materials
Additive manufacturing (AM) is a layer-by-layer process of building the parts that allows to create objects with different shapes and geometries. AM is especially suited for fabrication of composite materials. The mechanical properties of the composite parts depend on fiber density, distribution and orientation. However, variability of printing parameters leads to uncertainties in the composite properties or initiation of damage. In this contribution, we demonstrate potential of ultrasonic techniques for damage detection and assessment of materials properties through experimental testing and numerical modeling. Numerical models were validated with laboratory data and enable further guidelines for experimental testing. A set of nylon composite samples were fabricated via Markforged Mark Two™ composite 3D printer with different layer thicknesses. The samples include solid blocks and blocks with simulated cracks. This enables exploration of the influence of the process parameters on the mechanical properties of the additively manufactured nylon cubes. Elastic properties were calculated for all tested samples in three directions using the ultrasonic technique. Crack detection was conducted for damaged specimens. Numerical model for wave propagation within the nylon specimens was developed and validated using experimental data. Also, numerical simulations for wave propagation within the additively manufactured Onyx™ composite (reinforced with carbon fiber) specimens were conducted.
Extraction of Damage-Sensitive Signal Features in Damaged Carbon/Epoxy Composite Structures Using Statistical Pattern Recognition
A statistical pattern recognition-based methodology for determining damagesensitive signal features and corresponding damage extent from nondestructive ultrasonic guided wave (UGW) testing of carbon/epoxy composite laminates has been established. Changes in signal features can be a function of several parameters, which can include operational and environmental variability in the experiment. Similarly, damage-sensitive features are functions of several random variables, and selecting optimal features are often subject to human bias. Multivariate statistical analysis (MSA) was utilized to determine a high variance in jointly distributed random variables, experiment parameters, and signal features to systematically distinguish damage-sensitive signal features. In Data Sets 1 and 2, the variances were examined with respect to experiment parameters in composite laminates with a range of damage levels. In Data Set 3, the variances of several signal features were examined with respect to changing notch sizes over a sweep of frequencies. The relative damage extent was distinguished in Data Sets 1 and 2 using multivariate analysis and damage-sensitive signal features were distinguished in Data Set 3.
Bond-Based Peridynamics with Stretch and Rotation Kinematics for Modeling Composite Laminates
This study presents the bond-based (BB) peridynamics (PD) with stretch and rotation kinematics for modeling the linear elastic deformation of a composite laminate. The laminate experiences only in-plane and transverse shear deformations and disregards the transverse normal deformation. The PD equilibrium equation for a laminate is derived under the assumption of small deformation and is solved by employing implicit techniques. The in-plane PD forces are expressed by considering the PD bond interactions among the points. The forces arising from the interaction of adjacent layers are expressed by considering a pointwise approach that utilizes PD differential operator (PDDO) in conjunction with the shear-lag theory. The micro-moduli associated with stretch and rotation are directly related to the constitutive relations between stress and strain components in continuum mechanics. It is restricted to only one constraint on the material constants leading to a fixed value of in-plane shear modulus. The capability of this approach is demonstrated by considering progressive failure in a quasi-isotropic laminate with a pre-existing crack. It employs critical stretch, the critical skew (relative rotation) angle and critical delamination angle in the bond breakage criteria.
Application of Digital Image Correlation in Hygrothermal-Mechanical Testing of Fiber Reinforced Composites
The Office of Naval Research High-Fidelity Building Block and Validation Protocols for NextGen Composite Methods project aims to develop validation protocols for NextGen structural analysis methods. For this purpose, more experimental validation data is needed in matrix dominated failure events and adhesive bonded joints under the effects of temperature and moisture. Matrix dominated events test articles and adhesive bonded joints were tested at elevated temperature wet (ETW, 180F), room temperature ambient (RTA, 70F), and cold temperature dry (CTD, -65F) conditions. Tests at cold and elevated temperatures are enabled by a custom oven that is designed for hot and cold mechanical tests with noncontact optical tracking of displacements and strains with minimal interference for the purpose of Digital Image Correlation (DIC). This article will discuss the use of DIC at hygrothermal mechanical loading and methods to mitigate interference in the optical measurements. Noise is introduced to the optical signals due to circulating air, moisture, and refraction. This is illustrated in applications in tensile, shear, and fracture specimens.
Multiscale Analysis of Composite Structures and Materials by SwiftComp Mobile App
SwiftComp mobile App based on iOS and Android platforms has been developed to analyze composite materials using Google’s Flutter framework and dart language. It is a user-friendly App for computing properties for composites by utilizing SwiftComp capability. The App is currently available to download on iOS AppStore and Google Play Store. The current functionalities of this App include the calculation of lamina stress/strain, lamina engineering constants, laminate stress/strain, laminate plate properties, laminate 3D properties, and composite properties for unidirectional fiber reinforced composites. More multiscale constitutive modeling capabilities of the desktop version of SwiftComp will be implemented in the future version of this App. The SwiftComp App is jointly developed by both authors and is free to use on smart phones.
NextGen High Fidelity Datasets to Validate Advanced Computational Methods for Composite Hygrothermal-Mechanical Response
Industry at large has been slow to adopt novel advanced structural analysis techniques for composite structures despite several recent government, industry, and academia partnership efforts to advance the maturity of the tools. Much of the challenge is associated with the value of the developed technical data packages as the demonstrated capabilities of the methods lacked industrial relevance for current and next generation material systems and composite construction. While simple coupon level analysis for static strength at room temperature ambient conditions has shown tremendous growth in Technical Readiness Levels, many methods are still immature to address higher level elements in the structural building block and lack appropriate validation protocols for accounting for the effects of temperature and moisture. These conditions often drive structural sizing and present a near term opportunity to better understand temperature and moisture effects that often take several months before test data is available. The High Fidelity Building Block and Validation Protocols for NextGen Composite Methods Program (N00014-21-C-1008) seeks bridge the gap of high fidelity test data and associated protocols for validating advanced structural analysis tools for composite structures including temperature and moisture. The program includes test articles that are fabricated from IM7/5320-1 tape as well as FM309-1 structural adhesive to maintain a high degree of relevancy for future aircraft needs and to increase the value of the technical data packages required for industry adoption of methods. The paper provides an overview of industry needs for advanced analysis capabilities and how the high fidelity data can be used to address them.
Verification and Validation Approach for Advanced Material Modeling Using Composite Off-Axis Tension and Compression High Fidelity Test Data
The predictive capability of progressive damage and failure analysis (PDFA) methods for composite structures must be validated against experiment for effective maturation to be achieved. The lack of publically available experimental data has protracted the development of such methods and slowed forward progress in the field. As such, a high fidelity database of composite failure characterization tests using IM7/5320-1 was created through the Office of Naval Research (ONR) High Fidelity Database and Validation Protocols program to aid in verification and validation (V&V) of PDFA methods. As a next step, the ONR High Fidelity Building Block and Validation Protocols for NextGen Composite Methods program seeks to expand upon the high fidelity database and the V&V protocols developed in the previous program. This work presents a V&V approach developed for simulating off-axis tension (OAT) and compression (OAC) samples as demonstrated using the material modeling capabilities within MAT299 in LS-DYNA. The simulations are first verified with analytical solutions for stiffness and strength of the OAT and OAC models. Validation is then completed against experimental data obtained at room-temperature ambient (RTA), cold-temperature dry (CTD), and elevated-temperature wet (ETW) conditions. Limitations in the modeling method are discussed as well as applicability of the LaRC- 04 failure envelope to test data at different environmental conditions.
In-Situ Bending Performance of Nanostructured Carbon Fiber Reinforced Polymer Composites
Depositing carbon nanotubes (CNTs) into carbon fiber reinforced polymer composites (CFRPs) is challenging because of the need for complicated lab-scale processes and toxic chemical dispersants that makes conventional means of processing less compatible with existing industrial procedures for large-scale applications. In this work, a scalable supercritical CO2-assisted atomization technique is used to effectively deposit hybrid CNTs in CFRPs allowing them to boost their functionality and tailor the microstructure. Cellulose nanocrystals (CNCs) are utilized to create hybrid nanostructures with CNTs (CNC bonded CNT) that enables stabilization of CNTs in nontoxic media, i.e., water, and this promotes the scalability of the process. According to Zeta potential values, CNCs successfully stabilize CNTs in water suspension. Scanning electron microscopy (SEM) micrographs show hybrid CNC bonded CNTs are homogeneously dispersed on the carbon fiber surface. According to the in-situ bending test under the optical microscope, crack propagation is hindered by engineered hybrid CNT nanostructures in the modified CFRP whereas neat CFRP exhibits low crack growth resistance due to the uninterrupted crack propagation in the continuous epoxy matrix. Our results imply that this strategy probes the importance of new controlled manufacturing of hybrid nanostructures through evaporation‑induced self‑assembly of nanocolloidal droplets, and allows for tailoring of the desired properties of nanostructured composites.
Composite Laminate Progressive Damage Failure Analysis Benchmarking Using High Fidelity Inspection Damage Maps for Open Hole Tension Coupons at Two Environmental Conditions
This paper presents an approach for using high fidelity test data to inform modeling methods on progressive damage failure analysis for composite open hole tension specimens at room temperature ambient and cold temperature dry conditions. To do this, the progressive damage failure models will use a publically available continuum damage mechanics based material model (MAT299) to represent lamina level damage in unidirectional composite systems within LS-DYNA. The models will be evaluated against a high fidelity experimental database from a project sponsored by the Office of Naval Research. The database consists of experimental data for the material system IM7/5320-1. Soft, medium, and hard laminates at each environmental condition will be the focus of this paper.
Advanced Composite Materials: The Processing-Structure-Property Relationships in Layered Hierarchies
Advanced composite materials (ACMs), especially nanoparticle-reinforced polymer composites (NpRPCs), exhibit desirable physical and chemical properties that include low density coupled with directed high stiffness and strength, optimal dimensional stability, superior temperature, and chemical resistance, as well as relatively cost-efficient manufacturing. Successful manufacturing of high-performance nanocomposites depends on the precise control of processing factors, including (i) uniform dispersion of the nanoparticles, (ii) effective matrix-filler interfacial interactions at the molecular level, and (iii) alignment/orientation of the nanoparticle and/or polymer chains. Discussions of layers at multiscale (e.g., nano, micron, and macro scales) and their effects on the processing-structure relationship, especially the nanoparticle assembly with different mechanisms, will be the focus of this research. In particular, thermoplastic and thermoset polymers, as well as nanoparticles of various morphologies (e.g., 1D or 2D), have been used for scalable fabrication of 1D fibers, 2D coatings, and 3D architectures via 3D printing. The demonstrations in structural supports, thermal dissipations, electrical conductors, plastics recycling, stimuliresponsive systems, and tissue scaffolds show massive potential in national defense, space exploration, energy storage, and human health.
Effect of Crystalline Ceramic Oxide on the Densification-Crystallization Behavior of Binary Lithium-Di Silicate Glass Compositions
In the present work the crystallization and densification behavior of Lithium-Disilicate (LD) glass compositions were studied with the presence of various nucleating agent and ceramic oxides. A 30 mol% Li2O-70 mol% SiO2 LD system was modified using Al2O3, P2O5 and ZrO2 by keeping SiO2/ Li2O ratio constant at 2.33. The role of 2 to 5 mol% Al2O3, P2O5 and ZrO2 were studied in terms of Differential Scanning Calorimetry, XRD and SEM. The DSC results suggest that glass transition temperature increased with the inclusion of Al2O3 and ZrO2. It is also found that, inclusion of Al2O3 and ZrO2 helped lowering melting temperatures which reduced energy cost for melt processing. The study also suggested that densification was aided by the inclusion of P2O5 and ZrO2. Keywords: Densification; Crystallization; Glass-Ceramics; DSC.
Damping Behavior of Dry and Epoxy- Impregnated Carbon Nanotube Yarn
Multiwalled carbon nanotubes (CNTs) are believed to add beneficial damping to fiber reinforced polymer composites on account of their weak, reversible inter-wall bonding and CNT/polymer bonding. An effective way to add a large volume fraction of CNTs to a fiber composite is to form the CNTs into condensed yarns and add the yarns to the interlayer regions of composites with the CNTs oriented along the primary loading direction. To address the ongoing need for additional data on the damping provided to fiber composites by CNT yarns, the current investigation focuses on the tensile damping behavior of a commercially available yarn with and without epoxy impregnation. Based on quasi-static tensile tests using cross-sectional areas measured by ethanol immersion testing, dry yarn was observed to have an elastic modulus of 109 GPa and an ultimate tensile strength of 1.30 GPa, while impregnated yarn had a modulus of 62 GPa and a strength of 0.813 GPa. Dry and impregnated yarns exhibited a ratcheting mechanism, where permanent strain is accumulated with repeated load cycling. Through dynamic mechanical analysis, it was shown that both dry and impregnated yarns exhibited high damping, with average initial loss factors of 0.110 and 0.0953, respectively. With continued cycling and increased strain, the storage modulus of impregnated yarns increased by 450%, while the loss modulus increased by 256% and the loss factor decreased by 35%. Dry and impregnated yarns exhibited quasi-static and dynamic properties that were highly sensitive to loading history, although impregnated yarns showed greater degrees of change over larger numbers of loading cycles. It is shown that an established micromechanical model can predict to within 6% the loss factor of a [90]6 hybrid carbon/epoxy laminate containing 10 vol% CNT yarns aligned in the 0° orientation, based on known dynamic properties of the impregnated yarn and the baseline laminate without CNTs.