Applied Composite Materials最新文献

This study presents a novel experimental methodology designed to assess damage in woven glass fibers reinforced polyamide 6,6/6 composites, specifically subjected to low-velocity impact and cyclic tensile loading. Conventional ultrasonic testing techniques often fail to detect subtle material degradation, particularly when dealing with barely visible impact damage (BVID), which can go unnoticed but still significantly compromise structural integrity. In contrast, the proposed approach utilizes multi-directional ultrasonic Lamb wave analysis, a more advanced technique that offers greater sensitivity and precision in identifying damage at various stages of the composite’s lifespan. In this work, a damage indicator is defined based on the velocity profile of Lamb waves, which are sensitive to changes in material properties such as stiffness degradation. The Lamb wave-based methodology is rigorously validated through detailed comparisons with X-ray tomography. These comparisons reveal strong correlations between the two techniques, highlighting the effectiveness of the proposed ultrasonic approach in detecting BVID. Moreover, the study demonstrates that this methodology is not only highly sensitive but also scalable, making it suitable for industrial applications where automated inspection of composite components is essential. The proposed method offers a significant advancement in non-destructive testing (NDT) techniques based on Lamb wave diagnostic tools in composite material testing.

Increasing power density and power consumption in electronic devices necessitate heat-dissipating components with high in-plane and cross-plane thermal conductivity to prevent overheating and enhance performance and reliability. Traditionally, polymer composites are made by incorporating rigid, high thermally conductive fillers within the polymer matrix. However, the filler loadings required to achieve significant thermal conductivity enhancement can impact the mechanical properties of the material system, often making them significantly more rigid or brittle than the base polymer. In this study, we developed a method to incorporate an ultra-high molecular weight polyethylene (UHMWPE) three-dimensional fiber mat and eutectic gallium indium alloy (EGaIn) liquid metal into an epoxy matrix. We integrated in-plane and cross-plane thermal conductivity measurements with flexural modulus assessments to understand the impact of the high thermal conductivity fillers on the thermal and mechanical response of the material. This approach enhances both the in-plane and cross-plane thermal conductivity of the composite, achieving thermal conductivities three times higher in the cross-plane direction and six times higher in the in-plane direction compared to the base polymer. Moreover, mechanical characterization reveals that the mechanical performance of the composite is comparable to that of a fiber-reinforced polymer composite, and the incorporation of liquid metal does not significantly impact stiffness, even at high filler loadings. This work demonstrates the potential of strategic composite design to achieve polymeric materials with optimized thermal-mechanical coupling. These new materials offer a solution to the challenges posed by higher power consumption in electronics, providing improved heat dissipation capabilities for more reliable devices.

Aiming to improve the impact resistance of structures, a technique to prepare carbon fiber composite laminates based on bonding methods was proposed. CFRP laminates with different numbers of bonding surfaces were fabricated, and then the impact toughness and impact bearing capacity of the laminates were evaluated based on pendulum and drop hammer impact tests, respectively. Results showed that the introduction of bonding surfaces noticeably reduced the generation of manufacturing defects within CFRP. Moreover, the bonding surface at 1/2 thickness as a neutral layer was conducive to the energy absorption of composite layers and the bonding surfaces at 1/4 and 3/4 thickness prevented the extension of shear cracks. As a result, compared to the specimen B0 without bonding surface internally, the specimen B1 with only one bonding surface at 1/2 thickness showed the best impact resistance in the drop hammer impact test. The peak force increased by 8.6% and the energy absorption before failure was increased by 30.6%. When three bonding surfaces were introduced and distributed at 1/4, 1/2 and 3/4 thickness, the best impact toughness was obtained in the pendulum impact test. The impact absorption work and impact toughness of the specimen B3 increased by 19.61% and 17.02%, respectively. However, the specimen B2 with two bonding surfaces distributed at 1/4 and 3/4 thickness showed poor impact bearing capacity. In conclusion, both B1 and B3 showed advantages in terms of impact resistance, proving the beneficial effects of the introduction of bonding surfaces with a reasonable distribution on CFRP.

This paper presents an equivalent damage model for efficiently predicting compression-after-impact (CAI) behaviors of laminated composites, based on the intelligent numerical reconstruction of impact-induced damage. Using the k-means +  + clustering algorithm, the 3D spatial distribution of delamination is quantitatively identified from C-scanning time-of-flight (TOF) images and then discretized into a numerical mesh along with the soft inclusion. With the incorporation of interlaminar and intralaminar damage models, the CAI residual strength, failure modes, and damage scenarios of the composite laminate after low-velocity impact are predicted, showing good agreement with the experimental results at various impact energies. The proposed model enables fast evaluation of CAI strength within 1.5 h, without requiring impact energy information and maintaining accuracy, which is beneficial for application in damage tolerance design and optimization of engineering laminated structures.

Despite significant progress in additive manufacturing, processing defects remain a persistent challenge. Artificial intelligence (AI) enabled early defect detection and process optimization is promising solution for this problem. In this study, real image data from a composite 3D printing setup was used to evaluate the anomaly detection performance of three models: Autoencoder, Support Vector Machine (SVM), and the Zero Bias Deep Neural Network (DNN). The results demonstrate that the Zero bias model achieved an accuracy of 97.96%, significantly outperforming the Autoencoder (93.38%) and SVM (89.80%). Multiple thresholds in the zero bias model enable explain ability.

This study presents a comprehensive experimental investigation into the performance of lug structures made from Carbon Fibre Reinforced Polymers (CFRP) with three distinct lay-up configurations: Hard (L-C-H), Quasi-Isotropic (L-C-QI), and Soft (L-C-S). The behaviour of these CFRP lugs was compared against conventional metallic aluminium lugs (L-Al) to evaluate their load-bearing performance under uniaxial tensile loading. Among the CFRP configurations, the L-C-QI lay-up exhibited the highest load-bearing capacity, even surpassing that of L-Al. In contrast, the L-C-H lay-up demonstrated the lowest strength within the CFRP group. L-C-S exhibited matrix cracking near the bore hole, facilitating stress relief similar to ductile metals. The L-Al lugs underwent significant plastic deformation and ligament necking, leading to 136% higher energy absorption compared to the best-performing CFRP lug (L-C-QI). Additionally, the study found that as the Hooke’s stiffness of the lugs decreases, the angle between the failure surface and the loading direction increases, indicating a transition in failure mode from shear tear-out to net section tension. Significant delamination was observed on the bearing side of the lug bore hole in CFRP lugs, while aluminium lugs exhibited plasticity on the bearing surface and ligament necking. These findings offer insights into the static tensile behaviour and failure mechanisms of composite and metallic lug structures.

This study investigates the effects of alkali treatment, moisture exposure, and thermal cycling on the mechanical properties of woven jute fiber/epoxy composites. The samples were fabricated with a vacuum-assisted resin infusion technique with untreated and alkali-treated (5% NaOH solution – 4 h) jute fibers. Three levels of thermal cycling profile (-5 ℃ – 65 ℃) as low (50 cycles), medium (250 cycles), and high (500 cycles) were applied to samples that were designated as dry and moisture-exposed (120 h water-soaked samples). Tensile, impact, and hardness tests were conducted to understand the mechanical performance of the samples. Experimental results indicate that alkali treatment improves tensile strength by 17.68%, tensile modulus by 6.01%, and elongation at break by 2.85%, primarily due to enhanced fiber-matrix interaction. Impact strength also increased by 16.54% following alkali treatment. However, exposure to moisture and thermal cycling resulted in significant degradation. Moisture-exposed samples showed reductions of 55.54% in tensile strength, 55.58% in impact strength, and 41.46% in hardness, highlighting the detrimental effects of water absorption. Thermal cycling alone caused tensile strength reductions of 29.50% after 500 cycles due to thermal stresses and micro-crack formation. The results indicate that environmental conditions must be considered for jute/epoxy composites, particularly in humid and temperature-variant mediums. In long-term use, the products may be exposed to more severe conditions and thus the design assumptions could mismatch the practical occurrences.

Needle-punched carbon/carbon composites (NP C/Cs) are extensively utilized in aerospace applications due to their superior mechanical performance at elevated temperatures. However, it is susceptible to oxidation in high-temperature, oxygen-rich environments, leading to alterations in the structure and volume content at the material interfaces, which ultimately compromises their mechanical properties. In this study, the shape evolution curve of circular arc fiber during steady state ablation is derived. Utilizing embedded element technology, an embedded solid beam mixed element model was developed to predict the axial compression behavior of NP C/Cs both before and after oxidation. This approach not only simplifies the model but also enhances computational efficiency. The findings indicate that as the mass loss ratio increases from 0% to 16.84%, the predicted residual elastic modulus ratio decreases from 100.00% to 58.34%, while the residual compressive strength ratio drops from 100.00% to 59.82%. The strong correlation between experimental and simulation results for residual modulus and strength ratios validates the proposed model, confirming its effectiveness in predicting the mechanical performance of NP C/Cs under oxidative conditions.

This study investigates the damage and energy absorption of 3D woven Kevlar/epoxy composites under dynamic impact conditions to clarify their impact resistance. Low velocity impact tests were conducted using a drop weight tester at various velocities. Load-displacement curves and energy absorption results, combined with damage morphology analysis, were used to identify different damage modes and the critical energy for complete penetration. High-speed imaging combined with digital image correlation (DIC) technique was employed to examine the full-field strain distribution and damage evolution during the impact process. An enhanced damage-tracking algorithm was implemented, specifically designed for large out-of-plane deformations and discontinuities and could be broadly applicable to other material systems that undergo large out-of-plane deformations. Results showed that maximum load increased with impact velocity, while bending stiffness remained constant. At lower velocities (1 m/s), elastic behavior with significant rebound was observed, with no delamination or penetration. At 2 m/s, the penetration energy threshold was determined to be 44.3 J, while at 3 m/s, the composite was fully penetrated, showing increased maximum load, displacement, and plastic energy absorption. Higher impact velocities led to longer cracks, with weft cracks consistently exceeding warp cracks in length due to the straight arrangement of weft yarns, which facilitates damage propagation. Microstructural analysis identified fiber fracture, interfacial debonding, and matrix cracking as the main failure modes of the 3D woven Kevlar/epoxy composite. These findings provide valuable insights into the damage mechanisms, strain evolution, and mechanical behavior of 3D woven composites.

A microscopic mechanical model is developed to investigate the mechanical properties and damage behavior of aluminum matrix composites. The effect of particle size distribution and shapes on the properties of aluminum matrix composites is investigated by building three-dimensional (3D) representative volume elements (RVE). The particle size-dependent strengthening and mismatch of thermal expansion strengthening are considered using Taylor-based nonlocal theory of plastic. The damage of matrix is predicted based on the Gurson–Tvergaard–Needleman (GTN) theory. Shear effects are introduced to the GTN model to better describe the failure behavior at low levels of stress triaxiality. A maximum principal stress criterion is used to describe the failure behavior of SiC particles and cohesive behavior is adopted to simulate interface debonding between matrix and particles. Results show that particle size and shape have a significant effect on the failure behaviour of aluminum matrix composites.