bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTS OF CONSOLIDATION PROCESS ON THE TENSILE STRENGTH OF UHMWPE FILAMENTS EXTRACTED FROM COMPOSITE PANELS
Authors: OBAID AHMAD ABU , DOSHI SAGAR M. , YEAGER MICHAEL , BOGETTI TRAVIS A. , DEITZEL JOSEPH M. , GILLESPIE, JR. JOHN W.
Published: November 2023

This research focuses on the investigation of damage mechanisms induced through the processing and consolidation of UHMWPE composites (HB210). The HB210 composites consist of Dyneema® fibers and thermoplastic polyurethane resin. The composite panel consisting of 72 sheets was processed following the manufacturer’s recommended temperature and pressure profile of 100°C and 2 MPa (290 psi) for 10 minutes, followed by 125°C and 20.7MPa (3ksi) for 30 minutes. Each sheet consists of 0/90/0/90 ply orientation with an average sheet thickness of 200 μm. To quantify the effects of consolidation pressure on fiber deformation and tensile strength distribution, a technique for extracting fibers from the processed panels was developed. Specimens (11 x 19 x 152 mm) were cut from the panel and immersed in tetrahydrafuran (THF) fluid for 7-20 days (dependent on the specimen thickness). The THF effectively dissolved the matrix enabling UHMWPE fibers to be extracted at different locations through the thickness. The baseline tensile strength distribution was based on testing virgin fibers from the spool and fibers extracted using the THF method from a single as-received layer of HB210. The two baselines exhibited statistically equivalent tensile strength distributions proving the THF extraction method did not affect the fiber properties and that degradation of tensile strength is a result of the consolidation process. From tensile test data, strength distributions for extracted fibers from consolidated panel were generated, and strength at 50% failure probability was evaluated. Compared to the baseline, the fibers extracted from the processed panel showed a 15% reduction in the average tensile strength. SEM microscopy of the extracted fibers from the consolidated panel exhibits different damage modes. Surface cracking and flattening damage modes were induced by the consolidation pressure (20.7 MPa) applied in the thickness direction of the panel. Additionally, axial kinking was observed along the length of the fibers. The possible mechanisms for the formation of these kinks are – viscous forces from the resin during the consolidation process, where fibers loaded in compression are observed to kink into large voids between fibers, or due to the CTE mismatch between the fibers and the resin within a layer or between the 0 and 90 layers within a sheet during the cooling stage.
EFFECT OF SURFACE PREPARATION ON THE DAMAGE AND FRACTURE BEHAVIOR OF CARBON FIBER- REINFORCED POLYMER AND TITANIUM TUBULAR ADHESIVE LAP-JOINTS
Authors: KAISER ISAIAH , FERGUSON RYAN , TAN K.T.
Published: November 2023

This work evaluates the bond durability for adhesive tubular lap-joints (TLJs) between titanium and CFRP using static tensile tests. Five different treatment methods are introduced to prepare the surface of the CFRP: (1) sanding, (2) air atmospheric pressure plasma treatment (APPT), (3) as-received, (4) Frekote 710NC to act as contamination, and (5) Frekote 700NC plus air APPT to understand the APPT ability to remove contamination. Characterization of the treated surface is done using X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscope (SEM), and Water Contact Angle (WCA) to examine surface energy. Results show that air APPT produces the lowest WCA compared to the other treatment methods, indicating high surface energy and wettability. When the CFRP surface is prepared by sanding, it causes breakage to the underlying fibers, exposing them to the environment. As a result, asreceived CFRP has better bond strength than when prepared with sanding. This study evaluates the durability of adhesive TLJ and builds a relationship between surface characteristics and performance, providing insight into their behavior and knowledge of optimal surface preparation principles.
EVOLUTION OF VISCOSITY UPON CROSSLINKING IN EPOXY RESIN: AN ATOMISTIC INVESTIGATION
Authors: PRASAD DIPAK , MITRA NILANJAN
Published: November 2023

Adhesive materials such as epoxy resin (DGEBA/DETDA) are crucial in formation of any laminated and sandwich composites. Typically for these thermoset polymeric adhesives, crosslinking is an important step which eventually determines the thermomechanical response of the resultant composite. During this process of cross linking of epoxy resin, one observes changes in the viscosity of the resultant composite mixture of the resin and the hardener as well as change in temperature. This crosslinking of thermoset resins (DGEBA/DETDA at 2:1 ratio) is a complex chemical reaction process involving breaking of oxirane ring (C-O bond) in DGEBA, breaking of N-H bond in the amine (DETDA) and creation of N-C covalent bonds between the resin and the hardener. Apart from formation of new covalent bonds in the process, numerous non-covalent bonds such as hydrogen bonds and van der Waals interactions are also formed. This study is aimed at fundamental understanding of the correlation between viscosity changes in the composite upon crosslinking with the evolution of these non-covalent bonds. The study is primarily based upon molecular/atomistic investigations.
SILICON OXYCARBIDE NANOCOMPOSITE LAMINATES REINFORCED WITH CARBON NANOTUBES OF HIGH DEGREE OF ALIGNMENT AND ULTRAHIGH PACKING DENSITY
Authors: DAI JINGYAO , ACAUAN LUIZ , JAGANI SHAAN , PATEL PALAK , WARDLE BRIAN L.
Published: November 2023

With properties including high stiffness, high strength, low density, and high aspect ratio, carbon nanotubes (CNTs) are ideal reinforcements for ceramic matrix composites (CMCs) for enhanced strength and toughness. However, prior studies on CNT- reinforced CMCs generally showed limited mechanical and multifunctional property enhancements due to damage, random orientation, low volume fraction, and agglomeration of the introduced CNTs. In this study, we developed a bulk nanocomposite laminating process for ceramic matrix composites (BNL4CMC) to overcome such limitations and to enable the fabrication of ceramic nanocomposite laminates reinforced with highly aligned, uniformly distributed CNTs of ultrahigh packing densities (>40 vol%). Instead of direct mixing, the polymer precursors for the ceramic can be infused into horizontally aligned CNT (HA-CNT) arrays followed by curing and pyrolysis to convert the polymer matrix to ceramic while preserving the CNTs’ high degree of alignment and packing density. Silicon oxycarbide (SiOC), which possesses high modulus, high hardness, creep resistance, and good thermal/chemical stability, is selected as the matrix for this study. Using the BNL4CM approach, we successfully fabricated 4-ply HA-CNT/SiOC laminates with ultrahigh CNT packing density (> 40 vol%), uniform distribution, and nanofiber alignment. Microstructure and morphology characterizations including X-ray micro-computed tomography (X-ray μCT) and scanning electron microscopy (SEM) are used to study the evolution of HA- CNT/SiOC laminates’ microstructure during the fabrication process. Nano-indentation was performed to obtain the elastic modulus and hardness of the fabricated HA- CNT/SiOC laminates. The process-structure-property relation obtained will inform the design and manufacturing of other HA-CNT reinforced ceramic systems for enhanced mechanical and multifunctional properties.
GRAPHITE ENHANCED GNP/PVA COMPOSITE PIEZORESISTOR WITH A STABLE LOADING RESPONSE
Authors: ÖNDER MELIKE NUR , GÜLGÜN MEHMET ALI , PAPILA MELIH
Published: November 2023

This study introduced graphite particle enhanced graphene nanoplatelet (GNP)/Polyvinyl alcohol (PVA) nanocomposite piezoresistor. The intention was to explore and use the synergy between graphite particles (GPs) and GNPs. The role of the GPs would be to create the backbone for conduction paths. Hence, they can reduce the variations in the conductive path formation as the number of cycles increases. The GNPs’ on the other hand, is to enhance the piezoresistive effect of the nanocomposite piezoresistor. Different filler ratios of the GPs and associated synergy with the GNPs were examined. As the GPs constituted the backbone for conduction, they decreased the sensitivity loss under cycling loading. The synergy assured repeatable and consistent Gauge factor over the cycles and a linear response to the applied strain. The piezoresistor was produced in ink that allows the application with a spatula or a brush on a substrate. This application method provides structural health monitoring of the materials with an easy application. In our study, plexiglass was selected as the substrate. Their response under cycling loading was examined as a function of resistance change of composite piezoresistor. The data was collected via a multimeter.
EFFECT OF FIBER REINFORCEMENT ON THE PROCESS PARAMETERS OF INJECTION MOLDING MANUFACTURING PROCESS
Authors: GARG NIKHIL , RAGAB ABDALLAH M. , POKKALLA DEEPAK KUMAR , HASSEN AHMED A. , OGLE RYAN , OZCAN SOYDAN , VAIDYA UDAY , KIM SEOKPUM
Published: November 2023

Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
MODELING THE IN-PLANE COMPRESSION RESPONSE OF AS-MANUFACTURED STEERED FIBER LAMINATED PLATES
Authors: VIJAYACHANDRAN AVINKRISHNAN AMBIKA , WAAS ANTHONY M.
Published: November 2023

Robotic Automated Fiber Placement (RAFP) is a novel additive manufacturing modality for the production of laminated fiber reinforced composites. In addition to faster and precise manufacturing of composite structures, RAFP enables the designer to now use optimal steered fiber directions to maximize structural performance indices. The optimal solutions depend on loading and boundary conditions and are called “Variable Stiffness” (VS) laminates. Several studies have established that VS designs show significant benefits when compared to traditional laminates. A novel algorithm to derive optimal fiber paths to maximize uniaxial and biaxial buckling loads of 20 in ×20 in square VS laminates was introduced by the authors. The study utilized Bezier splines to represent the course center-lines, along with a “global manufacturing mesh” that would reduce the number of optimization variables. A surrogate model in conjunction with a multi-objective Genetic Algorithm (GA) was used to obtain a “Pareto front” of feasible solutions from which three feasible solutions were identified based on the criteria that the total gain in mass be less than 10%, the decrease in global stiffness capped at 10% and more than 25% increase in buckling load compared to a unidirectional laminate. These chosen designs were then manufactured and tested for uniaxial in-plane compression response. The proposed study presents the development of a numerical model using a pixelated FE mesh that captures manufacturing signatures like gaps and overlaps as well as the measured initial curvatures of the panels as manufactured. The load v/s load point displacement response of seven of the nine panels are well captured using the numerical model, with less than 5% error in initial stiffness and transition loads. A model with relaxed boundary conditions is used to correct for the deviation in the response curves for the rest two panels. Further, an optimization problem is introduced to examine the optimal straight fiber paths that maximizes the transition loads of the slightly curved panels and comparisons are drawn to establish that the steered fiber panels perform better than the straight fiber paths by up to 25% in terms of transition loads.
AN EXPERIMENTALLY VALIDATED HYPER-VISCOELASTIC MODEL FOR THE BENDING RESPONSES OF PRE-IMPREGNATED TAPES UNDER PROCESSING CONDITIONS
Authors: WEI QINGXUAN , WEI QINGXUAN , ZHANG DIANYUN , ENOS RYAN
Published: November 2023

Compaction of pre-impregnated fiber sheets (prepregs) is crucial to the formation of defects such as wrinkles and void. This study presents an anisotropic hyper-viscoelastic constitutive model to predict the compaction deformation and force of prepregs considering the influence of temperature on resin behaviors. The entire stack of individual prepregs is homogenized as an anisotropic continuous material whose strain energy density function is developed considering normal, shear, and coupling between normal behaviors. The proposed constitutive model integrates prepreg relaxation responses through generalized Maxwell models. The proposed novel constitutive model was implemented in the commercial Finite Element Analysis (FEA) software Abaqus as a user-defined material subroutine, UMAT. The modeling parameters were characterized by a discrete micromechanics model. The modeling approach was further applied to simulate a stepwise compaction process of carbon fiber/polyamide 6 prepregs to demonstrate the predictive capability.
USING MACHINE LEARNING TO PREDICT MECHANICAL PROPERTIES OF LONG FIBER THERMOPLASTICS BASED ON MANUFACTURING PROCESS PARAMETERS
Authors: ISKANDER JOSEPH , JOHRENDT
Published: November 2023

Long Fiber Thermoplastic Direct Extrusion Compression Molding (LFT-D) is an effective manufacturing process for semi-structural composite parts. LFT-D requires the user to know the influence each process parameter (e.g., temperature setpoints, rotational machinery speed, twin screw extruder configurations, matric flow rates, etc.) has on the resulting mechanical property of the manufactured part. This case study highlights the LFT-D manufacturing of carbon and glass fiber reinforced PA6 (CFRP, GFRP) at the Fraunhofer Innovation Platform (FIP) at the University of Western Ontario in London, Ontario, Canada. Data was collected for forty-six trials conducted over three years, varying fiber concentrations, fiber volume weights, screw configurations, temperatures, torques, forces, and pressures. The mechanical properties were measured and recorded in zero- and ninety-degree fiber directions. Machine Learning (ML) models like linear regression, random forest regression, ridge regressor, and lasso regressor were used to predict mechanical properties like Young's modulus and tensile strength of the part based on the process parameters as inputs. Data preprocessing and cleaning techniques were used to reduce the dimensionality of the dataset and to reduce the number of inputs to the model. These models were then evaluated using cross-validation to select the best model. Once the model was selected, the validation and testing datasets were used to determine the accuracy of the model. A sensitivity analysis was also conducted to determine how the variation in the output of each model can be attributed to the variation in input parameters. With this information, models can be further refined to obtain a more accurate prediction of the outputs and determine which inputs are essential when in the design phase of a product. The application of machine learning in the manufacturing process will ultimately accelerate composite product development and reduce the costly and iterative manufacturing process.
FABRICATION AND CHARACTERIZATION OF CARBON NANOTUBE/POLY(METHYL METHACRYLATE) NANOCOMPOSITE LAMINATES
Authors: LIN YUYING , LI CARINA , DAI JINGYAO , ACAUAN LUIZ , WARDLE BRIAN L.
Published: November 2023

Aligned carbon nanotubes (A-CNTs) are advantageous reinforcements for polymer nanocomposites (PNCs) due to their high mass-specific physical properties, including strength, elastic modulus, thermal conductivity, and electrical conductivity, which create potential applications in both structural reinforcement and multifunctionality. To utilize these properties, the CNTs should be aligned and densely packed within the polymer matrix, similar to existing carbon microfiber composites. However, past methods to fabricate CNT-reinforced PNCs have focused on random dispersion of the nanofibers, resulting in uneven distribution and low packing density. As such, it has been difficult to fully realize the benefits of reinforcing PNCs with A-CNTs. In more recent work, the high volume fraction bulk nanocomposite laminating (BNL) process with A-CNTs has been demonstrated. PNC laminates containing uniform, aligned and highly-dense CNTs at unprecedented high volume fractions (> 50 vol%) using the aerospace-grade thermoset bismaleimide (BMI) polymer have been successfully manufactured. In this work, the BNL fabrication technique is applied to the manufacturing of the first high volume fraction aligned-CNT BNL with a thermoplastic matrix, namely poly(methyl methacrylate) (PMMA). Composites with thermoplastic matrices are used extensively in aerospace and civil structures due to their rapid processing, high ductility, improved recyclability and repairability. It is shown in this study that PMMA-matrix BNL with a high packing density and a void-free morphology have been successfully fabricated, based on assessment using micro-computed tomography (μCT). Crystallinity and glass transition temperature (Tg) are shown to be largely unaffected by the aligned CNTs using DSC. With the high specific strength, rapid manufacturing process, and multifunctionality of aligned CNTs, the thermoplastic PMMA BNL has the potential to replace conventional materials in additive manufacturing and electronic applications.
ANALYZING THE PROGRESSIVE DAMAGE OF COMPOSITES DUE TO MANUFACTURING INDUCED DEFECTS THROUGH A SEMI-DISCRETE DAMAGE MODEL
Authors: MEKA SAI KRISHNA , ENOS RYAN , ZHANG DIANYUN
Published: November 2023

During composite manufacturing processes, multiple steps are involved, each step introducing new physical and chemical processes. These processes alter the properties of the constituents (fiber and matrix), affecting the behavior of the composite materials. The changes in the properties of the fiber are not that significant. Whereas the mechanical and thermal properties of the matrix such as Young’s modulus, Poisson’s ratio, coefficient of thermal expansion etc. change significantly. Residual stresses are developed in the composite due to thermal expansion mismatch of the constituents and cure shrinkage of the resin. These resulting residual stresses have a considerable impact on the mechanical properties and performance of the composites. Also, cracks develop in the composite system during the manufacturing process which can affect the performance of the composite. When the composite system with residual stresses is mechanically loaded, the system exhibits a drop in the strength after a critical stress state is reached. To predict the critical stress at which the drop occurs we use the continuum damage method called the Smeared Crack Approach (SCA). Using SCA we can predict the stress-strain behavior of an RVE as the damage progresses. The critical stress value of the microscale RVE acts as the corresponding strength of the composite on a macro-scale level. To account for the variability in a composite system we randomly generate different RVEs. This is done by varying the number of fibers and the location of fibers using a statistic distribution for a fixed volume fraction. Then we conduct the simulations of manufacturing and progressive damage to identify the strength values of the RVEs. The strength values obtained are then used to assign to the different regions of a semi-discrete damage model of a composite laminate in macro-scale. The unique aligned meshing strategy of the model decomposes the bulk non-linearity and localization zones which provide a proper load transfer pathway. This random assignment of the strength values simulates the realistic behavior of a composite where each region has almost the same material properties but different strength values due to the uncertainties associated with the manufacturing processes.
RAPID DESIGN AND ANALYSIS OF BONDED COMPOSITE JOGGLE LAP JOINTS
Authors: PINEDA EVAN J. , WEINTRAUB MAX , BEDNARCYK BRETT A. , AINSWORTH JAMES , JONES STEPHEN
Published: November 2023

Progressive failure analysis to determine the strength and damage tolerance of joggle lap joints containing pre-existing cracks was performed using the finite element method and virtual crack closure technique. Two adhesive, and four adherend, thicknesses were considered. Two pre-cracked configurations were considered that contained 0.25 in. long placed at the top adhesive/adherend interface or inside the laminate in the joggle region. The joints with the adhesive cracks exhibited stable crack growth followed by a transition into unstable crack growth. Meanwhile, the advancement of the interlaminar crack was entirely unstable. The line load strength of the joints displayed substantial sensitivity to changes in the thickness of the adherend. However, while the adhesive crack also was affected by changes in the thickness of the adhesive, the interlaminar crack was relatively insensitive to these changes.
METHODOLOGY FOR CHARACTERIZING THE FORMING LIMITS OF HIGHLY ALIGNED DISCONTINUOUS FIBER COMPOSITE LAMINATES
Authors: MORRIS KYLE S. , CENDER THOMAS A. , THOSTENSON ERIK T. , YARLAGADDA SHRIDHAR
Published: November 2023

Highly aligned discontinuous fiber (ADF) composite laminates have demonstrated potential to stretch form biaxially to complex geometry while retaining aerospace grade properties. This work utilizes Tailored Universal Feedstock for Forming (TuFF) [1], an ADF format that uses 3mm IM7 fibers and PEKK 7002 thermoplastic resin converted to unidirectional prepreg and multiaxial blanks. To lay the groundwork for the forming process-structure-property relations, a novel methodology is developed for defining the forming limits of an ADF composite lamina by constructing a forming limit diagram (FLD). The ADF-FLD defines the strain mode forming limits based on lamina fiber orientation and will be defined with respect to a broader set of failure criteria—which can be material uniformity, consolidation quality, or specific mechanical properties. To demonstrate the methodology, ADF TuFF blanks were stretch formed at various strain levels and strain modes (longitudinal and transverse plane strain). Surface strain on stretch formed samples was measured by photogrammetry. Preliminary failure criteria were established based on acceptable variability in strain measurements to reflect the uniformity of material deformation. This unique approach to defining forming limits will be used in studying material and process variables in forming ADF composites, as well as providing part geometry and forming process design requirements.
3D PRINTABLE FLAME RETARDANT GRAPHENE-POLYMER NANOCOMPOSITES
Authors: DATTILO VITALIANO , BACHIM KUNAL , HAGUE ISABELLA , SHONKWILER BRIAN J. , MAKEEV ANDREW , ORR MELISSA S. , MACALUSO ROBIN T. , BOZLAR MICHAEL
Published: November 2023

Polymer nanocomposites that can combine various properties, including flame retardant behavior, ElectroMagnetic Interference (EMI) shielding, as well as mechanical strength are highly desirable in the automotive and aerospace industries. Graphene is a low-dimensional material with unique properties that impart multifunctionality. In this work, we investigate the properties of graphene-reinforced high-density polyethylene produced via extrusion. We carry out complete analytical studies to investigate the physical and chemical properties of the nanocomposites. We then compare the mechanical and thermal properties of the graphene-reinforced nanocomposites to recent results from the literature, as well as benchmark values established by industry.
CHARACTERIZATION OF PLY-WAVINESS MANUFACTURING DEFECT IN COMPOSITE AEROSPACE LAMINATES BY ULTRASONIC SCATTERING ANALYSIS
Authors: MACHAK NATHAN , DONABEDIAN ALEXANDER , AYALA GABRIELA  GONZALEZ , VENKATARAMAN SATCHI , DIAZ-MONTIEL PAULINA , CAPRIOTTI MARGHERITA
Published: November 2023

The use of composite materials in the aerospace industry has considerably increased in the last decades. Despite their superior mechanical performance and tailorable nature, they are hindered by their expensive manufacturing processes and complex damage evolution behavior during their lifetime. Among the manufacturing defects that particularly characterize automated methods and/or complex parts, ply waviness in Carbon Fiber Reinforced Polymer (CFRP) could lead to strength reduction and complex behavior, and needs further attention, both in its detection and understanding of damage evolution. Ultrasonic c-scanning techniques are well suited for composite inspection: they are currently used in the aerospace industry for non-destructive evaluation of newly manufactured parts, in- service inspections and maintenance, and can be tuned to detect ply waviness. In this work, CFRP laminate beams specimens with induced out-of-plane ply waviness have been inspected in a water submerged C-scan system, using ultrasonic pulse-echo technique. Data were collected for different specimen parameters and system settings, including ply waviness severity, ultrasonic transducer frequency, and C-scan resolution. A customized code was then developed to process, visualize, and analyze the waveforms collected from the tests. Front-wall, back-wall, and internal wave- packets were identified using estimated calculations of the wave velocity in composite laminates. Then, different waveform features such as time-of-flight and amplitude were extracted to visualize and analyze the ply waviness and its characteristics. It was found that internal and back-wall wave packets experienced a decrease in amplitude over the ply waviness region of the specimen. Furthermore, regions to the left and right of the ply waviness experienced noticeable differences in time-of-flight and amplitude for various wave packets. Additional features and signal processing techniques are employed to consistently characterize ply waviness defects and study their evolution under fatigue and other loads by means of ultrasonic scattering analysis.
UTILIZING TAILORED FIBER PLACEMENT METHODOLOGY TO ENHANCE FRACTURE TOUGHNESS OF WAVY COMPOSITE LAMINATES
Authors: FLORES MARK , ZHOU ERIC , BRAGINSKI MICHAEL , TANNER CALEB , HUELSKAMP SCOTT , TANDON G. P. , ABBOTT ANDREW , FURMANSKI JEVAN
Published: November 2023

Polymer matrix composites can be used to design various aircraft components because of their strength-to-weight advantages and durability. However, the material must satisfy the necessary design allowable when implemented into a structural application. Tailor Fiber Placements is a process in which dry carbon fibers can be stitched into any fabric, impregnated with resin, and molded to any geometrical component. In our study, in-plane waviness was introduced to the material to enhance the fracture toughness of the laminated composite—a sinusoidal function defined by four different types of waviness. The overall objective is to develop a fracture tolerant material creating a tortuous path for damage to propagate, which could enhance impact resistance, susceptibility to extreme environments, and dissipative energy mechanisms.
AI-ASSISTED STATISTICAL ANALYSIS OF FRAGMENTATION RESPONSE OF HETEROGENEOUS LAYERED MEDIA
Authors: ABEDI REZA , HYUNH GIANG , POURKAMAI-ANARAKI FARHAD , AMIRKHIZI ALIREZA , FUREY COLIN , LEE HANBYUL LE , HANSEN CHRISTOPHER J.
Published: November 2023

The fracture response of materials is highly dependent on their microstructural details, especially for fragmentation problems. The fragmentation response of a ring expanding with constant radial velocity is often analyzed using the method of characteristics. While most studies assume homogeneous material properties, we treat fracture strength as a random field to elucidate the interaction of key characters of the random field, correlation length and point-wise variation, with loading rate and other fracture and elastic parameters. The output parameters include dynamic strength and macroscopic energy dissipation capacity of the material. Due to the high dimensionality of the input random fields and other types of input data, e.g., loading rate, training machine learning models for predicting output parameters is challenging. For this purpose, we consider a few neural network architectures and feature extraction techniques to predict the response accurately with only a handful of influential input parameters.
RELAXATION BEHAVIORS OF ADHESIVE BONDED CARBON FIBER REINFORCED COMPOSITES USING DIELECTRIC RELAXATION SPECTROSCOPY AND THERMALLY STIMULATED DEPOLARIZATION CURRENT
Authors: RAHMAN MINHAZUR , VADLAMUDI VAMSEE , RAIHAN RASSEL
Published: November 2023

Improving the reliability and durability of adhesive bonds is one of the biggest challenges in critical composite structures in industries such as Aviation, Automotive, Marine, and so on. Characterizing the interfacial region of the adhesive and composite adherends can yield vital information in this regard. Dielectric Relaxation Spectroscopy (DRS) is a technique used to investigate relaxation behaviors in terms of dielectric constant and loss tangent as a function of frequency. The material's response to polarization mechanisms at different frequencies can be captured by conducting Broadband Dielectric Spectroscopy (BbDS). Among these polarization mechanisms, interfacial polarization is most relevant to adhesively bonded joints. Thermally Stimulated Depolarization Current (TSDC) is also an effective tool that provides information about interfacial polarization and polarization of polar groups in epoxy-based polymers. The relaxation behaviors of the specimen are described by the depolarization current that is emitted as the polarized dipoles are relaxed in relation to temperature. Adhesively bonded carbon fiber composite adherends with different surface properties were manufactured and studied using TSDC and DRS techniques. Different polarization current spectra were observed with bonded specimens of varying surface characteristics. The morphological changes made to the adhesive-adherend interfaces are found to be reflected in the relaxation times and corresponding frequencies at different temperatures. These two complementary techniques portray conclusive relaxation mechanisms triggered by the external electrical fields.
EXPERIMENTAL INVESTIGATION OF BUBBLE MOBILITY IN POROUS MEDIA DURING RESIN TRANSFER MOLDING
Authors: CHEN SHIH WEN , NIKNAFS NAVID , SIMACEK PAVEL , ADVANI SURESH G.
Published: November 2023

Liquid Composite Molding (LCM) is a class of manufacturing processes such as Resin Transfer Molding (RTM) and Vacuum Assisted Resin Transfer Molding (VARTM) used to produce composite materials. One of the challenges in LCM is elimination of voids or air pockets in the final composite part which can compromise its structural integrity. One source of voids are the bubbles that are present within the resin as it enters the closed mold and are trapped as the resin cures. The first step to eliminate such voids is to understand their flow behavior in a resin that is injected into a fabric. We have carried out an experimental study to characterize the bubble movement through the pore network formed by the fabric weave architecture. The movement of bubbles within the resin is tracked using a camera within a transparent mold for three different fabric types. The bubble diameter and its velocity are measured as it goes through the fibrous media. By introducing dimensionless numbers that characterize bubble mobility (how fast the bubble moves compared to the resin velocity) as a function of dimensionless channel within the fabric weave (ratio of bubble diameter to the spacing of fiber tows) it is demonstrated that bubble mobility is much higher for tighter weaves and larger bubbles. This can help to optimize the LCM processes and minimize the voids by tunning the bubble mobility during the manufacturing process.
STUDY OF MICROSTRUCTURAL VARIABILITY OF FIBER REINFORCED COMPOSITES USING MULTI-SCALE MODELING AND MACHINE LEARNING
Authors: STAPLETON SCOTT , HUSSEINI JAMAL F. , BARLOW GEORGE J. , GHAFFARI SEYEDEH HENGAMEH , SCHEY MATHEW , HAJIBABAEE PARISA , POURKAMALI-ANARAKI FARHAD , PINEDA EVAN J. , BEDNARCYK BRETT A.
Published: November 2023

This paper presents an overview of research conducted to track the variation in fiber reinforced composites at the microscale induced from manufacturing, and determine the effect composite properties. For this effort, the microscale was first quantified using statistical descriptors. These descriptors are needed in order to determine statistical equivalency of artificially generated microstructures. The artificially generated microstructures have been made using a combination of randomly distributed fibers and simulations. Numerical parameters of the simulation can be manipulated to produce different features found in common microstructures such as fiber clusters and matrix-rich regions. Finally, reduced order structural models were used to quantify the variation in the response due to variations at the microstructure. Meso-scale simulations utilize integration point variation in material properties to simulate the overall variation in the response. Machine learning can be used to replace models at the microscale level and capture variation without having to link multi-scale models.
AUTONOMOUS CONTINUOUS FIBER INFILL GENERATION FOR COMPOSITES 3D PRINTING
Authors: HERNANDEZ MARIANA , TEKER AYTAC , POCHIRAJU KISHORE
Published: November 2023

Additive Manufacturing (AM) techniques are advantageous in manufacturing polymeric composites over traditional procedures that require molding, mounting, etching, and post-cleaning. AM is conducive to material allocation reinforcing in critical regions or directions by increasing the fiber volume fraction or by the selective orientation of the fibers. However, state-of-the-art entails fiber orientations be specified manually during the slicing and infill planning steps without any awareness of the desired material properties. In this paper, we formulate and solve the continuous fiber infilling with additively manufactured parts as a fiber path planning problem with constraints on the desired minimum fiber-volume fraction and optimal fiber orientations. The autonomous path planner maximizes the fiber-volume fraction in areas requiring high stiffness while minimizing the continuous-carbon filament in the rest of the part. The fiber orientation is also optimized to maximize the use of continuous carbon filaments. The software tools for generating continuous carbon fiber infills packaged with commercial composite 3D printers cannot automatically satisfy machine-imposed constraints, and the user is often asked to provide the infill geometries manually. The algorithms presented in this paper consider the geometry, stiffness requirements, and printing device constraints while formulating the infill structure. The algorithm was implemented into an open-source parametric 3D modeler. The implementation imports the mesh file representing the solid geometry, cleans and repairs the mesh, calculates the space between faces, and slices the part. Before creating the infill path, the algorithm obtains the face and hole contours and establishes the continuous carbon infill regions. The continuous carbon fiber placement paths are then determined within the infill region to maximize the fiber volume fraction while satisfying the machine constraints. The paper describes solutions with continuous fiber infilling using several example part geometries.
SCALABLE HIGH TENSILE MODULUS COMPOSITE LAMINATES USING CONTINUOUS CARBON NANOTUBE YARNS AND GAMMA RAY TREATMENT
Authors: EVERS CECIL , THAGARD KAYLEE , PARK JIN GYU
Published: November 2023

Continuous carbon nanotube (CNT) yarns are used to fabricate scalable composite laminates with high strength and stiffness for scaled-up manufacturing and potential engineering applications. CNT yarns are shown with specific tensile strengths of 1.77 N/tex due to a high degree of nanotube alignment. These properties are transferred to scalable unidirectional CNT yarn reinforced composite laminates fabricated using filament winding and aerospace resin matrices. Gamma ray treatments of 200 kGy, 700 kGy, and 1200 kGy are used to further improve the mechanical and interface properties of the constituent CNT yarns. The optimal dose is 700 kGy, yielding a specific tensile strength of 1.89 GPa/(g cm-3) and specific modulus of 258 GPa/(g cm-3), which represents a 37% and 44% improvement over the properties of the control laminate. The specific modulus exceeds current state-of-the-art unidirectional carbon fiber composite laminates. The results demonstrate an effective approach transferring high-strength CNT yarns into composites that retain the tensile performance of CNT materials at the flight article scale.
PROGRESSIVE DAMAGE ANALYSIS OF OPEN HOLE COMPRESSION SPECIMENS CONTAINING COMPLEX 3D TEXTILE ARCHITECTURES USING DISCRETE DAMAGE MODELING AND INDEPENDENT MESH METHOD
Authors: HOOS KEVIN H. , ADLURU HARI K. , ZHOU ERIC , POPELAR CARL , BALLARD M. KEITH , IARVE ENDEL V. , MOLLENHAUER DAVID
Published: November 2023

Discrete Damage Modeling (DDM) and Independent Mesh Method (IMM) are applied to progressive damage analysis in angle-interlock woven 3D textile composites with open hole loaded in uniaxial compression. The predictions were made by considering, geometrically nonlinear formulation, thermal residual stresses and compression-shear interaction in the tows in the framework of LaRC04 failure criterion. The effects of each of these consideration as well as their combinations was evaluated and concluded that while each separately has only an incremental effect it is their combined effect that resulted in accurate prediction of the warp direction open hole compression strength in angle-interlock woven 3D textile.
SIMULATION OF DYNAMIC CRUSHING BEHAVIOR OF SIMULATED CARBON/EPOXY STANCHIONS USING MAT58 AND MAT213 IN LS-DYNA
Authors: HALUZA RUDY T. , PEREIRA J. MICHAEL , RICKS TRENTON M. , GOLDBERG ROBERT K. , BAKIS CHARLES E. , KOUDELA KEVIN L.
Published: November 2023

Carbon fiber-reinforced polymer (CFRP) composites have shown promise as a material for structures designed to absorb energy in crush-style impact loading. However, simulating the behavior of CFRP structures in dynamic, crushing-style impact loading is challenging because of the many damage and failure modes that are essential to capture in the model. For the present investigation, CFRP stanchions were tested using a crash sled experimental test rig. The stanchions were designed by the Composite Materials Handbook-17 (CMH-17) Crashworthiness Working Group for the purpose of comparing experimental crash sled tests to corresponding simulations of the tests. The stanchions are C-channel shaped and represent a geometry common in the interior of aerospace vehicle structures. Explicit simulations in LS- DYNA were performed using a well-established composite material model (MAT58) and a next-generation material model (MAT213). Simulating the crushing of the stanchions occurred in two phases. First, the material models were calibrated using flat specimens that were manufactured with the same layup as the stanchions. While the original goal was calibration of material-related properties, mesh- dependent behavior was observed in simulations with both material models, and an unstructured mesh was therefore selected to remediate undesirable mesh-dependent failure modes. Additionally, for both the MAT58 and MAT213 models, it was found that either the crush force or the failure mode could be modeled accurately, but no set of parameters could be identified to optimize both results in the same model. Once satisfactory calibration was achieved, the same material parameters were applied to the stanchion crush simulations. The stanchion simulations showed that MAT213 more accurately predicted the experimentally determined crush force, and both material models predicted key aspects of the experimentally observed failure modes.
EXPLORING UNDERLYING CORRELATIONS IN MULTI-FIDELITY FINITE ELEMENT SIMULATIONS OF OPEN-HOLE TENSION TESTS: A COMPARATIVE STUDY USING MACHINE LEARNING
Authors: ESKANDARIYUN AMIRALI , FU HUILONG , REINER JOHANNES , VAZIRI REZA , ZOBEIRY NAVID
Published: November 2023

generate another database of simulation results. Both databases were used to create a training set for an ML model, aiming to study the correlation between low- and high-fidelity inputs that result in similar failure responses. The results enable increasing use of low-fidelity FE models to generate data for the training of ML models.Certification of composite aerostructures is typically achieved via analysis supported by testing, following the building block approach. Analysis of failure and crash at different scales, as well as design iterations and optimization, require fast and validated numerical models. Given the complexity and interactions of multi-failure mechanisms in composites, high-fidelity FE models are often needed to explicitly simulate the behavior of individual layers and their interlaminar interfaces, using a mix of continuum and discrete damage models. However, high-fidelity FE models require a considerable amount of time to set up, calibrate, and perform. On the other hand, low-fidelity modeling approaches, such as laminate-based smeared models, may provide reduced accuracy in some cases, while offering shorter simulation times and thereby lower computational costs. In this study, progressive failure of Open-Hole Tension (OHT) tests on HEXCEL IM-7/8552 quasi-isotropic laminates are investigated using both low- and high-fidelity FE models. A Machine Learning (ML) technique is then employed to perform a comparative study between the inputs and outputs of these models. The ultimate goal is to identify areas in the FE parameter space where the low-fidelity model can be used as a substitute for the high-fidelity model with reasonable accuracy and to discover the relationships among main parameters to reproduce high-fidelity results from the low-fidelity model in an accelerated manner. To generate the low-fidelity model, a laminate-based FE model was created in LS-DYNA, using a continuum elastoplastic damage-based material card, MAT081. The model parameters were varied randomly, and simulations were performed to generate a large database of low-fidelity FE results. Similarly, a ply-based FE model employing MAT261 for continuum intralaminar damage modeling combined with cohesive tiebreak contacts to capture discrete interlaminar delamination was created. This high-fidelity model was also used to
DESIGNING A FUNCTIONALLY GRADED S-2 GLASS/EPOXY COMPOSITES FOR IMPROVED ENERGY ABSORPTION
Authors: KUBOTA MUNETAKA , GILLESPIE, JR. JOHN W.
Published: November 2023

SC-15 epoxy while the low yield strength epoxy was a TGDDM based modified system with monoamine functionalized partially reacted structure (mPRS), synthesized by collaborators at Drexel University. Compared to the baseline VARTM panel made from plain weave S-2 glass fabric with a 463 sizing and SC-15 epoxy, the penetration resistance was improved by ~25% by using a low yield strength with a high interface strength combination of 8-harness satin with mPRS. The thin laminate samples (6 mm) showed a 14% improvement in V50 when normalized by areal weight compared to a plain weave/SC-15 baseline by using plain weave/TGDDM with 20%mPRS. These two systems were combined to make an FGM panel (1.8 cm thick, 1.2 cm DoP system on strike face and 0.6 cm thin laminate on the back surface) which allowed for a 18% % increase in energy absorption capability compared to the baseline VARTM plain weave/SC-15 system on an equivalent areal density basis. This study demonstrates that the ballistic performance of GFRP can be improved through a material by design approach where constituents are varied through the thickness for maximum energy absorption.Glass fiber reinforced polymers (GFRPs) are often used in protective-structural applications due to their high specific stiffness, strength, and energy absorption. During an impact event, GFRP laminates absorb energy at multiple length scales through fiber/matrix interphase debonding, resin plasticity, fiber failure, fabric ply delamination, and overall laminate deformation. Meanwhile, the through-thickness role and energy absorption mechanism of the GFRP going through a penetration event changes from a confined punch shear/crush under hydrostatic compression on the front face to delamination and in-plane tension failure in the layers near the back face. Traditional composite panels use a single fabric/sizing and resin which are not optimized for the different energy absorption mechanisms at the different phases of impact and penetration. This indicates a potential opportunity to improve the impact performance of GFRPs by functionally grading the constituents through-thickness of the laminate to optimize the specific properties of the constituents during to improve penetration resistance. In this study, a 1.8 cm thick functionally graded (FGM) composite was designed using the depth of penetration tests to select the strike face material system and a thin laminate ballistic perforation test for the back side material selection. Two commercially available S-2 glass fabrics, an 814 g/m2 plain weave with a 463 sizing and a 302 g/m2 8-harness satin fabric with 933 sizing, were tested with low and medium yield strength epoxy resins. The medium yield strength is the baseline
PROCESS MODELING OF THE FIRST PYROLYSIS CYCLE OF SMP-10 CERAMIC MATRIX COMPOSITES
Authors: NIETO ZACKERY , RUESCHHOFF LISA , APOSTOLOV ZLATOMIR , CASTELLANOS ALEJANDRA
Published: November 2023

Ceramic matrix composites (CMCs) are widely used in high-temperature applications like hypersonic thermal protection systems. The polymer infiltration and pyrolysis (PIP) process is commonly employed to manufacture CMCs. The PIP process consists of repeated cycles of preceramic polymer infiltration and pyrolysis to progressively increase the density of CMCs. However, it presents challenges such as gas evolution, shrinkage of the preceramic polymer (PCP), and the formation of cracks, porosity, and internal stresses during pyrolysis. Detecting these defects is difficult, and they can lead to interlaminar delamination, reducing the CMC structure's strength, stiffness, and durability. Currently, determining the number of PIP cycles and manufacturing parameters relies heavily on experimental results due to the complex nature of CMC manufacturing. However, the high costs and time required for experiments hinder process optimization. Thus, there is a need for high- fidelity computational tools that can capture PIP process defects and analyze the effects of manufacturing parameters. This research aims to develop a multiphysicsbased model with temperature and degree of cure dependencies to simulate the first pyrolysis cycle of the PIP process and its resulting defects (pores and cracks) in CMCs. The FEA software ABAQUS and user subroutines will be used to implement this model. A comparison will be made between the predicted defects by the computational model and experimental results from AFRL. A comprehensive multiphysics model will be developed, integrating a thermo-chemical model, thermo- mechanical model, and crack initiation and propagation model. Initial findings have demonstrated encouraging agreement between the material model and thermogravimetric analysis (TGA) data, particularly concerning the impact of temperature and ceramic conversion.