The utilization of additive manufacturing in producing tubular honeycomb (THC) structures, leveraging capabilities of fused filament fabrication, enables the introduction of attributes, such as buckling initiators, to augment energy absorption characteristics. Increasing crush efficiency and/or energy absorption efficiency of THC structures bolsters payload and occupant protection in vehicular systems during impact scenarios such as collisions for ground vehicles or harsh landings for aircraft. In this investigation, THC structures composed of acrylonitrile butadiene styrene (ABS) plastic were additively manufactured so that buckling initiators (BIs) could be efficiently incorporated in the THC structure and readily positioned at the top, 3/4 height, or half height of the samples. Each configuration was subjected to quasi-static (0.03 mm/s) and constant (0.5 m/s) velocity testing employing an MTS machine, with three specimens manufactured for each test condition. Results demonstrated a notable 12.60% increase in energy absorption efficiency and a 15.75% increase in crush efficiency for specimens featuring BIs at the top of the sample as compared to those without BIs under quasi-static conditions. Furthermore, substantial improvements were also observed under constant velocity testing, indicating the efficacy of BIs at the top of the sample in promoting structural folding and progressive collapse, thereby increasing crush energy absorption and crush efficiency.
Moisture absorption during the uncured stage often leads to a reduction in the energy release rate after curing epoxy adhesives. Therefore, an effective method for removing moisture from adhesives is highly desired. In this study, we explored the application of freeze-drying—commonly used in food processing—to uncured epoxy adhesives. Film-type epoxy adhesives, AF555 (3M) and FM309 (Solvay), were subjected to freeze-drying and evaluated using the Double Cantilever Beam (DCB) method. The results showed an increase in energy release rate and a decrease in data dispersion, indicating improved reliability of the bonded joints.
The use of carbon fibers is increasing worldwide, leading to the need for recycling of those materials. From a fiber matrix separation point of view there are already existing technologies available for the reclamation of recycled carbon fibers (rCF). On the other hand, there are not many existing industrial applications where recycled carbon fibers are used. The aim of this study is to investigate the mechanical properties of reinforced polyamide and thermoset matrix systems and their behavior at different temperatures and the influence of an industrial forming process in case of thermoplastic matrix systems to then identify possible applications for the material. Overall, this study investigates the use of a novel PA66/6I polymer supplied by Asahi Kasei Corporation as a matrix material with rCF from cut-off waste and a flame-retardant additive. The PA66/6I composites are compared with PA66 and epoxy composites, each reinforced with rCF in the form of a dry-laid nonwoven, through bending tests at different temperatures ranging from -30°C to 150°C. Also, the influence on the mechanical properties of an organic aluminum phosphinate based flame retardant (FR) was investigated. In addition, the processing of organic sheets made with the thermoplastic polymers is studied and the impregnation quality of isothermal molded parts is shown. It was found that the PA66/6I matrix results in similar mechanical properties compared to highly used PA66 or epoxy matrix materials but offers advantageous wetting and impregnation behavior during production of the CFRPs, resulting in more homogeneous CFRP parts and faster part production, which is very important for the use in e.g. automotive applications.
Carbon fiber reinforced thermoplastic sheet molding compounds (CFRTP-SMCs) consist of short, thin tapes that undergo complex rearrangement during compression molding, forming dense, randomly distributed architectures that critically influence the final mechanical performance. However, once consolidated, it becomes extremely difficult to distinguish and trace individual tapes using conventional X-ray computed tomography (XCT), which relies on indirect inference from local fiber orientation differences. To address this limitation, this study introduces a direct visualization strategy based on marker tapes, comparing three candidates—conductive paint (silver-copper-based), copper foil tape, and aluminum foil tape—in terms of X-ray attenuation, adhesion, and visualization performance. The three markers exhibited distinct attenuation characteristics: copper foil showed the highest absorption, conductive paint moderate, and aluminum foil the lowest. Despite its moderate attenuation, conductive paint adhered firmly to the tape surface, preserved flexibility during molding, and provided continuous, deformation-responsive markings, enabling reliable visualization of tape flow and distortion. Among the tested options, conductive paint proved the most practical and effective marker for tape-level tracing. The proposed multi-marker approach opens a pathway to analyze macroscopic tape rearrangement and deformation, bridging process parameters with tape distribution in SMCs.
Composite-based additive manufacturing (CBAM) is a novel sheet lamination-based additive manufacturing (AM) process that facilitates the rapid production of high-modulus, high-strength fiber-reinforced thermoplastic composites. However, CBAM-produced parts exhibit high porosity and a relatively rough surface, which limit their use in demanding engineering applications. While polymer powder coatings mitigate these effects, the conventional application method struggles to achieve uniform surface quality, underscoring the need for advanced surface treatment approaches. Electrophoretic deposition (EPD) is an advanced coating method to deposit conformal coating on such complex geometries. However, the traditional EPD methods are only suitable for electrically conductive substrates. Therefore, the non-conductive nature and non-connected porosity of CBAM-fabricated glass fiber/nylon-12 (GF/PA12) composites pose a challenge in adopting the established EPD method. This study aims to develop an anodic EPD system of graphite oxide (GO) flakes suspended in deionized water on CBAM-fabricated GF/PA12 composites by utilizing their inherent porosity. A field-assisted capillary trapping mechanism was demonstrated by employing a flush-mounted anode configuration, where the electric field concentrates within liquid-filled surface pores to drive the deposition of GO particles. A comprehensive parametric study was performed to identify appropriate EPD process parameters by varying suspension pH, concentration, applied voltage, and deposition time. The results reveal that suspension stability is the governing factor; adjusting the GO suspension to neutral pH (~7.1) and lower (0.5 g/L) concentrations reduced blockage at pore entry regions and enhanced electrophoretic migration into surface pores. This study, for the first time, demonstrated a viable pathway to apply EPD to porous, non-conductive fiber-reinforced composites in future engineering applications.
As NASA missions extend beyond low Earth orbit, increasing reliance is placed on carbon fiber reinforced polymer (CFRP) composites for spacecraft structures where mass efficiency, durability, and long-term reliability are critical. In service, these materials are subjected to a combination of ultraviolet radiation, vacuum, ionizing radiation, atomic oxygen, and extreme thermal excursions under sustained mechanical loading. Flight systems such as the Boeing Starliner and SpaceX Dragon employ external composite structures that will experience these environments for extended durations. Although prior spaceflight and ground studies have reported limited changes in bulk mechanical properties, the synergistic effects of these environments on composite microstructure, particularly at the fiber matrix interphase, remain insufficiently characterized and represent a potential qualification and reliability risk. This study investigates the effects of short-term cryogenic exposure on a radiation shielding carbon epoxy composite, SC2020, as a ground-based analog for space relevant thermal extremes. The SC2020 material system has previously flown on the International Space Station under the Materials International Space Station Experiment (MISSE) program. Composite specimens were exposed to liquid nitrogen for 6 and 24 hours and evaluated using a multiscale characterization framework that combined ASTM D3039 tensile testing, Atomic Force Microscopy (AFM) based interphase analysis, and helium gas permeability measurements. Tensile testing showed no statistically significant or permanent degradation in global strength or modulus following cryogenic exposure. In contrast, AFM measurements revealed reductions in interphase modulus, weakened adhesion, and increased nanoscale heterogeneity, indicating localized degradation mechanisms not captured by conventional bulk testing. Gas permeability measurements showed a progressive increase in helium diffusion with exposure duration, consistent with micro-void formation or partial interfacial debonding. The results indicate that cryogenic exposure initiates degradation at the fiber matrix interphase while leaving global mechanical properties largely unchanged over short durations. These findings underscore the importance of multiscale diagnostics for identifying early-stage damage mechanisms that may influence long term performance and qualification margins for spaceflight composite structures. The data presented establish a cryogenic baseline for comparison with forthcoming MISSE flight exposure results and support ongoing NASA Established Program to Stimulate Competitive Research (EPSCoR) efforts aimed at improving composite qualification methodologies, risk assessment, and reliability prediction for space environments.
This study investigates the interfacial behavior of two composite systems: carbon fiber reinforced with EPON 862 epoxy (CF/EP862) and stainless steel laminated HTS wire bonded with EP29 LPSP epoxy (HTS/EP29) under ambient (25 °C) and cryogenic (−196 °C) conditions. Pullout tests, dynamic mechanical analysis, surface roughness measurements, and scanning electron microscopy were used to evaluate interfacial shear strength (IFSS), failure modes, and surface morphology. Results show that HTS/EP29 exhibits a ~156 % increase in IFSS at −196 °C due to residual compressive stresses from differential thermal contraction, while CF/EP862 experiences a ~31 % reduction in IFSS as the epoxy becomes brittle and stick–slip behavior emerges. Surface roughness significantly enhances mechanical interlocking in CF/EP862 but has minimal effect in HTS/EP29. These findings highlight the combined roles of resin stiffness, thermal contraction, interfacial adhesion, and reinforcement surface characteristics in determining interfacial performance under rapid thermal shock. The study provides insights into the design of composites intended for extreme temperature applications, including aerospace and cryogenic systems.
This paper presents a hybrid physics and machine learning framework for predicting the thermal conductivities of woven composites. A two-step homogenization procedure based on mechanics of structure genome (MSG), a top-down multiscale modeling approach, is used to compute effective thermal conductivities of woven composites. First, fiber and matrix at the microscale are homogenized to obtain effective thermal conductivity of yarn for subsequent mesoscale analysis. Then, the mesoscale model is homogenized to compute the effective thermal conductivities of woven composites, accounting for yarns, matrix, and different weave patterns. The resulting dataset is used to train an artificial neural network for rapid prediction of in-plane and out-of-plane thermal conductivities across a wide design space. The core contribution is the integration of this model with an AI-powered composite expert system, CompositesAI, which allows users to query designs and retrieve predictions conversationally without deep knowledge in the theory or the code itself. The framework also supports dynamic retraining as new physics-based data are generated, ensuring continuous model improvement. This approach combines multiscale modeling accuracy with AI-driven accessibility, enabling efficient and scalable design exploration in composite materials and structures.
This study presents an innovative approach to designing filament-wound conical pressure vessels loaded by internal pressure, combining analytical computations based on classical lamination theory with data-driven evolutionary algorithms. The most critical area of the whole cone is the balanced layer at the lower base, in which the safety level is evaluated using the failure index based on Hoffman's strength criterion. The designed mathematical model related the geometrical parameters of the cone to the magnitude of internal pressure, representing the performance of the structure and safety expressed by the failure index. The optimization loop runs on two modules-Evolutionary Deep Neural Networks EvoDN2 module for machine learning and creating a lighter surrogate model, together with Constrained Reference Vectors Evolutionary Algorithms (cRVEA) for multicriteria optimization. This was applied to three different material configurations: E-glass/DA4518U (glass-epoxy), T300/N5208 (carbon-epoxy) and AS4/3501-6 (carbon-epoxy). The results show that the critical area is invariant to the material configuration. In addition, it was shown that the material configurations with higher anisotropy achieve a more uniform distribution of the load in the layers of the conical three-layered wall.
It is crucial to accurately detect hidden defects in the fibers of carbon fiber-reinforced polymer (CFRP) composites when these materials are used in the aerospace or automotive industries. Active infrared thermography (AIT) is a suggested nondestructive evaluation (NDE) method that is contactless, quick, and provides full-field detection, making it capable of identifying such defects. Unfortunately, traditional analytical methods struggle to precisely determine defect depths due to the complex thermal behavior of CFRP materials. Deep learning models, such as Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRUs), have been successfully employed to interpret thermal responses and characterize defects, as reported in existing literature. In this study, we introduce a deep learning framework to estimate flat-bottom hole (FBH) depth in CFRP composites from simulated active flash thermography thermal data. Finite Element Method (FEM) simulations were conducted to generate time-temperature profiles for FBHs of various sizes and depths. To enhance the model’s robustness, the dataset was augmented with synthetic variations. A 1D-CNN architecture was trained on this dataset to analyze the temporal patterns in thermal decay signals. The model’s performance was evaluated on a reserved test set using mean absolute error (MAE) and root mean square error (RMSE), showing promising accuracy in predicting defect depth. The findings demonstrate the potential of combining deep learning and AIT to precisely locate defects in CFRP materials. This approach ultimately aims to advance NDE, improve structural health monitoring, and enhance maintenance workflows and strategies.
Automated Fiber Placement (AFP) is a key enabling technology for high-rate production of aerospace-grade composite structures. Although AFP provides precise and repeatable material deposition, prevailing inspection practices remain predominantly manual, interrupting production flow and limiting throughput. To mitigate these limitations, a novel In-Process AFP Manufacturing Inspection System (IAMIS) has been developed. IAMIS integrates advanced sensing hardware with machine learning (ML)-based analytics to autonomously detect, classify, quantify, triangulate, and respond to defects in real time during AFP operations. Comparative roundrobin evaluations confirmed IAMIS's superior accuracy, sensitivity, and robustness in detecting and categorizing diverse defect types when compared with commercially available inspection systems. Beyond real-time defect detection, IAMIS incorporates an AI-based predictive analytics module (IAMIS-AI) that leverages inspection data acquired by IAMIS to support continuous process optimization. Trained on historical manufacturing data-including process parameters, defect characteristics, and part geometry-the IAMIS-AI framework predicts defect occurrence and visualizes potential defect regions on a 3D digital layup model during AFP program planning. These predictive insights enable proactive process adjustments, targeted quality-assurance actions, and reduced downstream rework and downtime. This paper presents the IAMIS system architecture, ML and AI framework design, and experimental validation methodology, and demonstrates how integrating data-driven intelligence into AFP can significantly enhance quality assurance and production efficiency. The adoption of IAMIS establishes a transition from labor-intensive, post-process inspection to a fully automated, intelligent inspection and optimization ecosystem aligned with stringent aerospace manufacturing requirements, while substantially reducing cycle time and cost.
Thermoplastic composites offer significant advantages for aircraft structural applications, including superior high-temperature capability, impact resistance, chemical and environmental durability, and inherent flame resistance. A distinguishing characteristic of thermoplastics is their ability to undergo multiple melt–reprocess cycles without degradation of intrinsic material properties, enabling efficient manufacturing, repair, and end-of-life recycling in support of a circular economy. Additional benefits—such as resistance to aggressive service environments, reduced cleanroom requirements, and the absence of material shelf-life limitations—make reinforced thermoplastics (RTPs) particularly attractive for high-rate aerospace manufacturing. Unlike thermosetting polymers, thermoplastic matrices can be reheated, melted, and re-consolidated, enabling fusion bonding (welding) as a structural joining method. Thermoplastic welding offers the potential for substantial reductions in structural weight, assembly time, and manufacturing cost relative to mechanical fastening and adhesive bonding. However, because weld performance is inherently process-dependent, the certification of welded thermoplastic joints presents unique technical and regulatory challenges. This paper presents guidance for the development and certification of a qualified thermoplastic weld system, encompassing material selection, interface constituents, process controls, joint design, and heat-affected zone (HAZ) management. Treating the welded joint as an integrated, systems-based entity is fundamental to achieving a predictable, repeatable, and certifiable joining approach. The proposed framework supports robust structural performance across production, maintenance, and in-service repair operations, and provides a structured pathway for regulatory acceptance of thermoplastic welded joints in primary and secondary aircraft structures.
This project evaluates the effectiveness of various geometries created using advanced additive manufacturing (AM) of Kevlar fiber and chopped carbon fiber-reinforced filament for ballistic protection applications. This study expands on sandwich panel designs with woven Kevlar face sheets and investigates an optimal fiber-reinforced filament-core structure. A unit cell workflow was developed in nTop (nTop, New York, NY, USA) to leverage its custom cell modeling and Finite Element Analysis (FEA) capabilities. Unit cell types were simulated and tested from the hexagonal honeycomb, gyroid Triply Periodic Minimal Surface (TPMS), and re-entrant auxetic cell families. Core structure thickness and cell size were additive manufacturing parameters that were varied to assess impact absorption. Moreover, the additively manufactured cell structures were encapsulated with a damping material, particularly silica. To determine the best type of silica for ballistic applications, three types of silica with varying tensile strengths were molded into shapes matching the cores. The samples were then tensile tested using an Instron 8801 universal testing machine (Instron, Norwood, MA, USA) to determine which offered the best balance between strength and ductility. The experimental approach began by determining the material characteristics for test coupons for both continuous fiber and chopped fiber in 0- and 90-degree filament orientations. A technology demonstration was also conducted by performing ballistic testing in a shooting range with 9 mm rounds to assess failure modes of the fabricated cellular structures based on these ballistic impacts.
As a lightweight and strong alternative to metals, composites have become a dominant aerospace manufacturing material. Traditional fastening methods damage the underlying fibers, degrade the long-term performance, and the hardware offsets the weight savings. As a result, adhesives are used in the manufacturing process for composite-to-composite and composite-to-metal bonding. However, composites are non-polar, with low surface free energies (SFEs), and require surface preparations to achieve structural bond strengths. Common methods often require harsh mechanical or chemical treatments and pose high operator and environmental safety hazards. Atmospheric pressure plasma jets (APPJs) are a nondestructive surface preparation method that removes contaminants and activates surfaces, increasing SFE, to initiate covalent bonding to adhesives. Air-based plasma achieves cleaning and activation by producing reactive electrons, ions, and free radicals that modify surfaces without etching material. APPJs are scalable, energy efficient, and produce no hazardous waste. Plasma treatments were also compared to other surface modification methods such as solvent wiping, laser ablation, hand sanding and grit blasting. Plasma treatment resulted in higher bond strength than the other methods, without damage or exposure of carbon fibers. This is important as exposed carbon fibers in carbon fiber reinforced polymers used in composite-to-metal bonding create a conductive channel for galvanic corrosion. Plasma treatment provides similar or better bond strength while mitigating the corrosion pathway. Corrosion prevention can be further improved through plasma deposition of a nanoscale anticorrosion barrier tie layer added to metallic substrates. The coating prevents ingress of moisture into the bond line and validated with resistance to a copper sulfate test solution on aluminum coupons.
Additive manufacturing (AM) is an advanced technology where parts are fabricated layer-by-layer to create three-dimensional parts in less time. However, challenges exist due to the timeconsuming and material waste in costly testing of the parts for a specific application. In this study, we aim to accelerate the qualification process of AM Inconel 718 parts by establishing the locationbased microstructural changes impact on the mechanical behavior of the part and correlating to the thermal history of the part at those locations. Using Hall-Petch relationships, yield strength at different locations related to the part's microstructural parameters and thermal history. This study reveals effect of location-based microstructure and properties on global performance of the part. Local properties will be extended to create a global stiffness matrix, and boundary conditions will be applied to the part in a model to predict the lifetime of an AM metallic part. Hence, this approach reduces the cost of testing, and the time required to qualify an AM metallic part to an extent across various industries.
In an earlier publication Bartosz and Chen [1] developed an accelerated test for UV exposure of plastic materials. This test simulates the damage from multiyear outdoor weathering by exposing test articles under higher intensity UV light but at much shorter times, on the order of weeks only. The equivalence between laboratory exposure time and actual field duration was tallied by accounting for the quantity of photons striking the test surface. The intensity and nature of the UV damage was additionally characterized by fracture studies and compared with field data from one of our products deployed for known exposure times at specific global locations. The similarity in results from both test samples and the fielded samples provided an initial confirmation of this accelerated test. For engineering units that have now sustained long term UV degradation during the four years from when this method was introduced, quantifying their UV damage by measuring the color change over time in CIELAB color space and correlating with our accelerated test has since reinforced its correctness to the point that we have used this method for both analyzing field degradation and screening components in our supply chain. This paper reports on these new developments along with how they further corroborate the effectiveness of this accelerated UV test.
Improving the life cycle of composite materials begins with low-energy manufacturing to achieve useful mechanical properties and often ends with either disposal or recycling. Thermoset composite recycling techniques typically involve burying, burning, solvent soaking, chopping, or grinding with only a small fraction of recycled material being used in down-cycled products. These resource-intensive processes are primarily driven by the environmental robustness of the composite and the difficulty of separating the reinforcement from polymer matrix. Prior work has demonstrated that dicyclopentadiene (DCPD) copolymerized with a cleavable comonomer, 2,3-dihydrofuran (DHF), can be deconstructed in solution via DHF hydrolysis by hydrochloric acid (HCl) in cyclopentyl methyl ether (CPME). In this paper, we discuss the recovery and reuse of carbon fibers and fabrics from the deconstruction of composites having a copolymer matrix of poly(DCPD-co-DHF) which can be cured by frontal polymerization. We explore the kinetics of composite deconstruction as a function of comonomer concentration. Carbon fibers were successfully deconstructed, recovered, and reused in multiple composites without significant structural degradation observed. The surface properties of the recovered carbon fiber were analyzed by contact angle measurements and X-ray spectroscopy to confirm that the chemical composition of the fibers remains largely unaltered by the deconstruction process.
The need for strong and lightweight materials in the aerospace and automotive industries has led to the development of composite materials which have a unique ability to tailor material properties to their applications. Although these composites are typically made by combining thermoset resins with fibers, recent applications for fiber-reinforced thermoplastics include Large Format Additive Manufacturing (LFAM). Fiber-reinforced thermoplastics allow the coefficient of thermal expansion of the material to be lowered enough to prevent excessive warpage and print quality parts at a larger scale. Although success has been shown for LFAM in some applications, there are still some significant strength and endurance concerns with LFAM-produced parts. This review will explore the developments and use of fiber-reinforced thermoplastics, their applications, and specifically their use and influence in the LFAM industry. It will also show the potential of using fiber-reinforced thermoplastics in future applications and explore various methods to improve the anisotropic properties. These methods include improving the LFAM process and combining LFAM with other manufacturing methods to improve properties. By using methods to improve the material properties of both the extruded material and the finished part, there is great potential for expanding the use of LFAM to more industries and applications.
Material response (MR) modeling is critical to understanding and predicting the behavior of thermal protection systems (TPS) materials. It is also critical to the design of novel TPS materials. Developing an accurate MR model can be a complex, expensive, and time-consuming process. This paper details the development of a MR model of an Oxy-Acetylene Test Bed (OTB) system. 1dFIAT (One-Dimensional Fully Implicit Ablation and Thermal response program) was used to develop the MR model. Surface thermochemistry was generated using two different programs to create B-prime tables for the MR model. A model ablative material, Phenolic Impregnated Carbon Ablator (PICA), was evaluated at 5 different heat fluxes on the OTB. A sensitivity analysis of 1dFIAT was then performed to investigate the parameters that were contributing most to the error between the predicted and experimental values. A combination of material properties and environmental properties were measured and calculated to fulfill the required inputs to the MR model. The accuracy of the MR model was validated against the OTB experimental results for the PICA material. Learnings and challenges associated with the creation of the numerical model using this method and future applications of this approach are also discussed.
This study examines the fatigue and flammability performance of TC1810/T1100GC fire-resistant carbon fiber composites used in structural components of firefighting and fire surveillance drones. These systems operate in high-temperature environments where materials must endure repeated tensile and flexural loads. Composite laminates with a [0/90]6S stacking sequence were fabricated and tested under load-controlled tension–tension fatigue conditions, using a sinusoidal waveform at a frequency of 5 Hz and a stress ratio of R = 0.1. Additionally, static tensile and flexural properties were evaluated. Thermal behavior was characterized using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The flame retardancy was evaluated using Limiting Oxygen Index (LOI) testing. The material exhibited has LOI greater than 50%, confirming its strong flame retardancy. Fatigue life decreased with increasing stress levels, while specimens at 40% of ultimate tensile strength (UTS) survived one million cycles without failure. Stiffness degradation trends revealed early-stage matrix damage followed by gradual fiber–matrix debonding. These results demonstrate that TC1810/T1100GC composites provide a favorable combination of mechanical endurance and fire resistance, making them suitable for use in aerial systems functioning in thermally and mechanically demanding environmental conditions.
