Journal of Composite Materials

This study addresses the impact performances of recyclable composites made of all thermoplastic polymer-fiber-reinforced plastics (PFRPs), where the reinforcing fibers and matrix are made of thermoplastic polymers. Three woven PFRPs systems were evaluated, including polypropylene fibers, polypropylene matrix, and high-density polyethylene matrix. In low-velocity impact scenario with an impactor speed of less than 6 m/s, our results demonstrate the energy absorption capabilities of the flat laminate PFRPs compared to woven carbon fiber-reinforced plastics (CFRPs) and aluminum alloy 5052. For the systems studied, the PFRPs can reach the specific energy absorption 89% to 115% of the CFRPs. Even compared with the aluminum alloy 5052, the PFRPs can reach up to 97%. We investigate the failure morphologies of the PFRPs using X-ray µCT scans. They reveal the PFRPs’ unique ductile failure morphologies compared to common CFRPs. In addition, we heal the perforated region in the PFRPs by applying the manufacturing process identical to the initial curing process. The healed panels are perforated again, and they recovered 30% to 38% of their original specific energy absorption, a recovery not achievable with CFRPs. This study provides valuable experimental results, and concrete insights into the potential applications of recyclable PFRPs in various engineering fields. It emphasizes their excellent energy-absorbing capability and repairability.

Low-velocity impact of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) composite laminates was studied experimentally and numerically. Hybrid laminates containing blocked layers of GFRP/CFRP/GFRP with all plies oriented at 0° were investigated. Relatively high impact energies were used to obtain full perforation of the laminate in a low-velocity impact setup. Numerical simulations were carried out using the in-house transient dynamics finite element code, Sierra/SM, developed at Sandia National Laboratories. A three-dimensional continuum damage model was used to describe the response of a woven composite ply. Two methods for handling delamination were considered and compared: (1) cohesive zone modeling and (2) continuum damage mechanics. The reduced model size achieved by omission of the cohesive zone elements produced acceptable results at reduced computational cost. The comparison between different modeling techniques can be used to inform modeling decisions relevant to low velocity impact scenarios. The modeling was validated by comparing with the experimental results and showed good agreement in terms of predicted damage mechanisms and impactor velocity and force histories.

The Parametric High-Fidelity Generalized Method of Cells (PHFGMC) has been established as an advanced micromechanical approach well-suited for analyzing the material nonlinearity and failure behavior of diverse periodic composite materials. In order to overcome the prohibitive computational cost of integrating micromechanical models into multiscale structural analyses as constitutive models, a proxy-surrogate modeling approach has been proposed by implementing a reduction modeling approach with deep Artificial Neural Networks (DNNs or ANNs). The PHFGMC-ANN approach has been employed to investigate the low velocity impact (LVI) analyses of hat-stiffened laminated composite panels under impact loading at various locations and energies with two different support conditions. Subsequent analysis of stiffened panels under compression loading has been conducted to understand the failure behavior of impacted panels. Further investigation was conducted into the separation between the skin and the stiffener, focusing on a single hat-stiffened coupon subjected to LVI. The analysis results have been compared against the experimental tests, and the comparison of interlaminar delamination has been used to demonstrate the efficacy of the new framework in integrating refined nonlinear micromechanical models within a multiscale analysis.

Composite laminates, known for their strength and flexibility, are widely used but can delaminate under certain barely visible impact. Ultrasound Transmission (UT) scans can detect such failures, but the noise in the scans makes automation of delamination morphology challenging. Machine learning could solve this, but it requires substantial training data. Furthermore, given the considerable time and cost of conducting impact tests on composite laminates, such data remains sparse. This study overcomes data sparsity by enlarging UT scan dataset using image augmentation techniques and synthetic data generation methods. A combination of rotation and elastic deformation of real UT images produced augmented data. Synthetic data was generated by mimicking the statistical variations in real data, including delamination length and rotation per ply, and adding gradients to match the original image noise. A U-Net based machine learning segmentation approach was utilized to capture local and global information through a series of convolutions to apply per-pixel classification. Systematic experimentation was conducted to study the influence of adding augmented and synthetic data on segmentation accuracy. The results show that the use of augmented data increases accuracy significantly. With the addition of synthetic data to the augmented data, there is a marginal improvement in accuracy. However, feature edge accuracy is significantly improved. The preliminary results presented here show the promising use of machine learning techniques for complex, non-destructive inspection methods.

As the number of orbital structures increases, so does the threat posed by micrometeoroid and orbital debris (MMOD) impacts. These impacts range from the ballistic range (less than 1.5 km/s) to exceeding 20 km/s and can significantly weaken space structures such as the International Space Station (ISS), leading to further risk as the debris shed could damage the in-orbit assembly field. Space structures, including the James Webb Space Telescope (JWST) and the in-space assembled telescope (ISAT), often employ fiber-matrix composites in various shapes and sizes. While the effects of hypervelocity impacts (HVI) on flat plate composites have been extensively studied, there is a notable lack of research on HVI of composite tubes. Understanding how MMOD impacts affect the integrity of individual truss members, as well as the structure as a whole is essential for assessing the condition of existing space structures and improving future designs. To replicate MMOD impacts, HVI investigations from 1 to over 3 km/s were conducted on a specialized two-stage light-gas gun, showing the transition from single inlet wall damage to cascading internal fragmentation inside the tube, leading to increased damage with increasing velocity. Our investigation focuses on the image analysis of the damage area and ejecta fragmentation in the carbon fiber reinforced polymer (CFRP) tubes, as well as quantifying the resulting hole diameter. This data is crucial for validating corresponding computational models. In this study we present three separate methods of characterizing HVI including: impedance matching through equations of state, a hybrid Lagrangian finite element (FE) model using LS-DYNA with smoothed particle hydrodynamics (SPH), and experimental investigations. All methods agree that HVI can cause nearly three times the amount of damage within a tube compared to similar conditions on a plate. Our findings help enhance our understanding of MMOD impact risks on existing structures and contribute to the development of systems with greater resilience to HVI.

Machine learning is quickly becoming an invaluable tool for examining large databases to find patterns and predictions based on similar parameters tested in previous studies. A natural application of this subset of artificial intelligence revolves around material data sets where tests are repeated for basic studies (e.g. tension, compression, bending, or shear) and extrapolating the data for tests not yet considered. Dynamic testing and validation with machine learning is examined here, as a significant time and cost is required for understanding larger-sized specimens (cm scale and larger) especially when the samples are composite materials in tension. This is due in part to the challenges involved in ensuring failure at the region of interests for an anisotropic material and minimizing the number of repeated tests. In this study, the data sets were generated artificially via finite element analysis with failure, and a machine learning code applied to infer the shape of the tensile test coupon knowing only the failure and stress field. Then the algorithm was run to generate a library of ideal coupon geometries based on ply angle and area location of failure within the test specimen. The result is a highly efficient prediction algorithm that can create the ideal specimen shape for tensile testing at speeds orders of magnitude faster than comparable finite element codes.

Barely visible impact damage poses a significant threat to composite structures, particularly prevalent in the aerospace industry. The occurrence of low velocity impact (LVI) events can lead to substantial deformations in composite structures, causing interlaminar delamination and diminishing their compression load carrying capacity. Beyond LVI-induced interlaminar delamination, it is crucial to investigate failures occurring between co-cured composite structures. This study focuses on hat-stiffened coupon structures, to investigate the delaminating phenomenon between the hat and skin components. The outcomes of experimental results inform the development of a finite element model, enabling to capture the structural response and delamination dynamics. The primary objective of the experiments is to understand the delamination process which occurs suddenly upon impact. LVI experiments are conducted to understand the structural behavior at varied impact locations. A mesh study establishes the relationship between cohesive parameters and element size in the model to enable computational efficiency by avoiding the need for a highly refined mesh. When the mesh is relatively coarse, the finite element model’s capability to resolve stresses at near singular locations is limited, however the computational time is lower. Therefore, the balance between computational efficiency on the one hand, and resolving gradients on the other, requires a fine balance in order to carry out a large number of design iterations efficiently. This research significantly contributes to advancing our understanding of delamination mechanisms at free edges in composite structures, offering valuable insights for computational modeling.

Effective lightning strike protection for critical aerospace and wind applications requires high electrical conductivity to dissipate current efficiently. However, polymer matrix composites face a challenge due to their inherently insulating nature. While conventional carbon fiber-reinforced composites (CFRP) exhibit electrical conductivity in the planar direction, achieving through-thickness conductivity remains an ongoing challenge. In this work, we have undertaken the fabrication of CFRP interleaved with vertically oriented carbon fibers (Z-fiber) to impart higher electrical conductivity along the thickness direction. Two Z-fiber composite variations are prepared: Z-1 with a single layer of Z-fiber and Z-5 with five interleaved layers and compared with no Z-fiber layer (Z-0) composite. The composite panels were subjected to lab-scale lightning strike tests with a current magnitude of 100 kA. To emulate real-world service conditions, an aerospace-grade paint coating was applied to the composite laminates. Comparative analysis shows Z-1 reduces damage diameter to ∼22 mm compared to Z-0 (∼26 mm), while Z-5 exhibits the least damage (∼16.7 mm), confirmed by optical microscopy. Z-5 demonstrates nine times higher through-thickness electrical conductivity than Z-0, reducing electrical anisotropy substantially. Thermal-electric finite element damage modeling predicts surface damage within 6% of experimental values for both Z-0 and Z-5 composites. Flexural tests post-lightning reveal Z-5 retains 66% flexural strength and 86% modulus, significantly better than Z-0, which retains less than 40% for both properties. This study highlights the efficacy of Z-fiber composites in lightning strike protection, offering improved through-thickness conductivity and mechanical property retention.

In this manuscript the low velocity impact resistance of a novel multilayered energy absorbing structure was studied and compared to the materials used in US Army Advanced Combat Helmets. We investigate the dynamic performance of 3D printed lattice structures sandwiched between carbon fiber composites and Kevlar fabrics to develop helmets that are lighter and have better blast protection. The energy absorbed by the sandwich structure was recorded based on the difference in acceleration between the top impacted surface and the base of the structure. A multi degree of freedom non-linear spring mass model was used to predict the response of the multilayer sandwich structures. Nonlinear stiffness values were determined through compression experiments. A good agreement between the model and the experiment at the measured boundary allows for better understanding of the material layers and provides a modeling framework for future predictions and optimization efforts. This study provides insights into the use of digitally 3D printed cellular materials, carbon fiber composites, and Kevlar fabrics to provide superior impact performance at a lighter weight compared to existing helmet systems.

State-of-the-art progressive damage and failure analysis (PDFA) tools for composites were developed for thermoset materials because of the prevalence of the material system within the aerospace industry and the need to address damage growth behavior of composites analytically. As the presence of thermoplastic materials has started to grow in the industry, it is necessary to be able to predict their behavior as well. However, it is unclear whether existing tools based on linear elastic fracture mechanics (LEFM) can be used to represent thermoplastics. One application area for PDFA tools is low velocity impact (LVI). This work presents two PDFA modeling methods originally validated for predicting damage of thermoset composites in low-velocity impact and evaluates their ability to model a thermoplastic material system in the same scenario. Both methods use MAT299, a continuum damage mechanics material model, to represent interlaminar damage and a cohesive tiebreak definition within LS-DYNA to represent delamination within a laminate. The results reveal that the cohesive tiebreak modeling method, while successful in modeling thermoset materials, is not currently capable of predicting the delamination response of thermoplastics. The larger strain energy release rates for the thermoplastic material in combination with a deficiency in the modeling method are believed to be the cause of the reduced delamination in the simulations. Potential routes for improving the delamination prediction in the simulations include adjusting the mode-mixity behavior, using a different cohesive approach for delamination, developing new best practices for cohesive behavior, and incorporating further non-linearity into the material model.

Aircraft manufacturers are investigating thermoplastic material systems to produce parts more quickly and efficiently. Detailed damage data is needed to evaluate existing damage analysis methods, developed for thermoset materials, to predict damage in thermoplastic materials. Damage maps were created for two thermoplastic material systems subjected to low-velocity impact over a range of impact energies. In this paper, the damage maps were used to investigate and compare the damage response of the different material systems. Impact specimens were manufactured from TC1225 LMPAEK T700G from Toray Industries and APC AS4D/PEKK-FC from Solvay. The effect of the degree of crystallinity on the damage response was also investigated using a third set of specimens manufactured using the Toray material and a quenching process. Using a combination of data obtained from X-ray computed tomography and ultrasonic testing, damage maps were created for every interface and ply for selected specimens showing matrix cracks, delamination outlines, and fractured fibers. The LMPAEK specimens were found to have fewer and smaller delaminations than the PEKK specimens for impacts at the same energy. However, the LMPAEK specimens contained a larger number of fiber breaks. A similar trend was observed when comparing low-crystallinity LMPAEK specimens with the baseline LMPAEK specimens. The LMPAEK specimens often contained lines of fiber fractures in near-surface plies emanating from the contact region that were not present in the PEKK specimens. The different damage responses may indicate that the material selection will be a function of the application and loading.

This study investigates the impact response of thermoplastic composite materials. The material system under consideration is a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK reinforced with T700 G (T700/LMPAEK). Several High Energy Dynamic Impact (HEDI) tests were performed wherein an aluminum projectile impacted T700/LMPAEK panels at different velocities. In the impact experiment studied herein, the projectile impacted the T700/LMPAEK panel at 73.8 m/s and rebounded. The ensuing damage to the T700/LMPAEK panel was characterized via ultrasonic C-scans, which enabled visualizing delamination extent and through-thickness matrix cracks as the boundaries between delaminations at individual interfaces. Since the projectile rebounded after impact in the current test, the fiber damage mode, while present, was not as significant as in the case of tests wherein the projectile perforated the panel. The impact event was modeled using a combined continuum damage mechanics and cohesive zone analysis approach with the commercially available hydrocode LS-DYNA®. The dynamic deformation and damage of the continuum, that is, the plies in the T700/LMPAEK laminate, were modeled using a Deformation Gradient Decomposition (DGD) material model, that is, MAT299 available within LS-DYNA. The interlaminar regions were treated as zero-thickness cohesive zones, wherein the dynamic delamination mechanics were modeled using a traction-separation formulation. Mixed-mode delamination growth was captured using the Benzegaggh-Kenane (B-K) traction-separation interpolation law. Strain-rate sensitivity of interlaminar fracture toughness was included using approximations based on published literature. The outcomes of the modeling effort demonstrate good correlations with test data regarding panel deflection, panel-projectile interactions, damage modes and damage extent.