Applied Composite Materials最新文献

This study investigates the interfacial bonding quality and forming stability of carbon fiber reinforced polyether ether ketone (CF/PEEK) thermoplastic composites during laser-assisted automated fiber placement (LAFP). Single-factor experiments on layup temperature, compaction force, and placement speed were conducted to evaluate their effects on laminate short-beam shear strength (SBSS). A quadratic model was developed using response surface methodology (RSM) to correlate the process parameters with the SBSS and warpage. The model was then integrated with grey relational analysis (GRA) and principal component analysis (PCA) for multi-objective optimization. The optimal process parameters were determined as follows: a layup temperature of 416 °C, a compaction force of 355 N, and a placement speed of 0.09 m/s. Under these conditions, the laminates exhibited an experimental SBSS of 70.02 MPa and a warpage of 0.2118%. The model predictions were 68.61 MPa (2.06% error) for SBSS and 0.1977% (7.13% error) for warpage. These results indicate that the constructed models are reliable and applicable to optimizing the LAFP process for CF/PEEK composites.

Ceramic matrix composites (CMCs) are widely used in the aerospace industry owing to their excellent physical properties, such as low density, high specific strength, and high-temperature resistance. As multiphase inhomogeneous materials, CMCs exhibit varied damage modes and failure patterns during high-temperature service, which have important implications for structural safety. To clarify the damage mechanism of CMCs, the mesostructural evolution of carbon fiber reinforced carbon and silicon carbide ceramic composites was observed in-situ using synchrotron radiation computed tomography (SR-CT) at both 25℃ and 1200℃. In addition, digital volume correlation (DVC) was employed to measure the deformations. The results indicate that a large number of matrix cracks exist in the initial state of the material. However, these matrix cracks are not the dominant factor governing failure. At 25 °C, interfacial debonding is the primary failure mechanism, whereas at 1200 °C, with increasing load, the main crack initiates at the edge of the specimen and propagates inward due to fiber breakage and crack coalescence, eventually leading to specimen failure.

The relationship between the viscosity and impact resistance of M-STF (Multi-walled carbon nanotubes doped shear thickening fluid) as well as its sensing mechanisms remains unclear. The synergistic effect of SiO₂ and MCNT (Multi-walled carbon nanotubes) content on the electrical resistance and rheological behaviour of M-STFs was studied. A novel design of using M-STF/TPU (Thermoplastic polyurethane tube with M-STF injected in) tubes as weft yarns to construct an impact-resistant smart 3D fabric was evaluated. The results revealed that the shear thickening effect of STF was enhanced with the increase of MCNT. The peak viscosity of M-STF70-0.5 (the mass ratio of SiO₂ and MCNT are 70% and 0.5%) was 16,400 Pa·s with a lowest critical shear rate of 3.4 s^− 1. A positive correlation between the viscosity and electric resistance was witnessed in low viscosity M-STF systems. Among them, the resistance change rates of M-STF65-1.7/TPU and M-STF65-0.9/TPU systems were the most significant, and the sensing performance was stable and repeatable, which can effectively and stably feedback the waist motion signals. The peak force of M-STF/TPU/PPTA (para-aramid fabrics with M-STF/TPU tube as one of the weft yarns) composite was 19.51% higher than that of pure PPTA fabrics upon low-velocity impacts. The M-STF/TPU/PPTA composite is also highly sensitive to impact energy, with a sensitivity exceeding 9.12 J^− 1. Therefore, as an impact protective, smart in motion sensing compliant composite, M-STF/TPU/PPTA was successfully designed, which will broaden the applications of impact protective textiles.

This work details the development of smart composites comprising of nanoparticle infused centrifugally spun piezoresistive composite sensors intended for their Structural Health Monitoring. The thermoplastic polyurethane (TPU) solution in dimethyl formamide (DMF) was spun in the form of fibrous webs using custom-built centrifugal spinner. A solution of carbon nanoparticles (CNPs) dispersed in tetrahydrofuran (THF) was then used to dip-coat TPU fibers with CNPs after they had been fabricated through centrifugal spinning. The solution had a concentration of 25% w/v CNPs which led to the formation of piezoresistive fibers with strain-sensing capabilities. The fibers were spun into yarns using a manual twisting tool that imparted 2–3 twists per inch, improving fiber compaction and strain-transfer stability. The sensors were characterized and attached to different composite specimens having widely varying configurations for mechanical testing including tensile testing, three-point flexural testing, and impact testing. The sensor’s exceptional sensitivity enabled it to detect the loads exerted on the composite structures and trace the overall deflection trajectory. The findings indicate that the newly designed composite strain sensors are appropriate for Structural Health Monitoring of Composite Structures.

Hybrid structures made of metal sheets and FRP offer high lightweight potential and can contribute to lower CO₂ emissions resulting from automotive structural parts. To realize intrinsic hybrids, a hybrid forming method was introduced that combines LFT compression molding and sheet metal stamping, as well as adhesive bonding, in one manufacturing process step. Stiffness-based design and simulation approaches for hybrid parts are already state-of-the-art. However, plasticity and failure are rarely considered which is the topic of this work. For this material modeling, first, a long fiber-reinforced PA6 GF40 material (LFT) suitable for hybrid forming was mechanically characterized, and the joining properties between steel and LFT, realized by a bonding agent, were determined. The hybrid-formed steel–LFT U-profile showed up to 92% higher specific energy absorption in comparison to mono-material profiles under bending. In addition, pure PA6 GF40 designs showed brittle behavior and rapid failure propagation under bending load, whereas steel–LFT hybrid structures showed fail-safe behavior. The corresponding FE modeling for hybrid forming, which does not need complex integrative simulation but offers sufficient accuracy to predict failure of hybrid formed structures was developed. This strategy involves LFT with failure by considering the stress state dependent Johnson-Cook failure criterion, and use LAW83 along with the corresponding SN-Connect failure model for the bonding zones between steel and LFT. The study found that the failure and force-displacement/torque-torsion angle curves in a hybrid-formed U-profile can be predicted with acceptable accuracy.

This study investigates the flexural behavior of 3D printed thermoplastic composites reinforced with short and long carbon fibers under varying environmental conditions. Three composite configurations: Nylon reinforced with random short fibers(RSC), and RSC reinforced with continuous fibers oriented at 0°(CF_0) and RSC with 90°(CF_90) were fabricated via fused deposition modeling. The samples were subjected to salt spray for 42 days followed by drying for seven days. After saline-humid exposure the flexural properties were evaluated at room temperature. Further, to understand the temperature effects on flexural performance of the composites the tests were conducted at -20 °C, 27 °C, 65 °C, 75 °C. CF_0 exhibited the highest flexural strength (281.3 MPa) and modulus (14.94 GPa), while RSC showed significant deformation and the highest deflection recovery (93.3%). Increasing temperature and salt exposure led to notable performance degradation, particularly in long-fiber composites. Fractographic analysis revealed brittle failure at sub-zero temperatures and ductile matrix-dominated behavior at elevated temperatures. The novelty of this work lies in systematically examining the combined influence of fiber length, fiber orientation, and environmental degradation (temperature and saline-humid exposure) on the flexural behavior of 3D printed thermoplastic composites, and the insights from this study give a new path for the adaptation of 3D printed composites in real-life applications.

Ceramic fiber insulation tile (CFIT) and surface coating play a vital role in the thermal protection system of spacecraft. As brittle materials, they are subjected to particle impacts during the takeoff/landing of spacecraft, as well as impact loads during installation. To investigate the ability of CFITs to resist low-energy impacts during installation and takeoff/landing of spacecraft, a user-defined subroutine (VUMAT) was developed from a UMAT to incorporate of energy evolution and damage updates, and was implemented in ABAQUS/Explicit. First, the finite element and experimental methods are employed to investigate impact on the CFIT, thereby validating the accuracy of VUMAT. Meanwhile, the penetration depth-angle and load-displacement curves are obtained at different impact angles. Besides, this work also focuses on the impact behavior of the CFIT with borosilicate glass coating. The results demonstrate that the coating can improve the impact resistance of CFIT, and the application thickness of the coating is predicted. The simulation results from this work can provide a theoretical reference for CFIT’s low-energy impact behavior, and provide a theoretical basis for subsequent research on high-speed impact behavior.

The rapid progression of machine learning (ML) has revolutionised numerous fields, including engineering, where these technologies are being leveraged to optimise design, improve efficiency, and automate complex processes. In next-generation polymer composites (NGPC), ML is driving a paradigm shift in materials science, offering new opportunities to transform how composites are designed, manufactured, and tested. These tools enable the development of high-performance, cost-effective materials by predicting optimal material combinations, fibre orientations, and structural configurations, significantly reducing the reliance on traditional trial-and-error methods. This paper provides a comprehensive review of the current state-of-the-art ML applications in NGPC, focusing on key areas such as material engineering and selection, optimisation and modelling of manufacturing processes, and the prediction of material properties. Furthermore, it underscores the role of cutting-edge ML techniques in damage assessment through non-destructive testing and structural health monitoring of composite structures. Despite these promising developments, ML applications in NGPC remain in a relatively early stage, with ongoing efforts needed to overcome limitations in data availability, model generalisability, and practical deployment. The review concludes by outlining current challenges and future research opportunities for integrating modern ML approaches into NGPC, offering valuable insights for researchers and engineers in this rapidly evolving domain.

Hybrid fiber-reinforced polymers (HFRP) are susceptible to hygrothermal aging, leading to significant changes in mechanical properties, but the underlying mechanisms remain unclear. Hence, the hygrothermal aging and penetration failure behaviors of carbon/Kevlar hybrid fiber composites are studied. Samples with three typical hybrid stacking sequences (C2K4C2, C4K4, C6K2) with different hybrid ratio, sensitive to hygrothermal environments, are fabricated using molding method. Samples undergo the artificial accelerated aging at 30 °C and 60 °C. By combining finite element analysis simulations and quasi-static penetration tests, the variation patterns of the penetration properties of laminate under different aging conditions are analyzed. Results indicate that the stacking sequence significantly affects the evolution of moisture absorption and penetration properties. A balancing mechanism between short-term penetration performance improvement and long-term aging stability decline is revealed based on the position of CF and KF layers. Within a certain period, the maximum load and energy absorption initially increase due to Kevlar and matrix plasticization induced by moisture absorption, then gradually decrease due aging. Finally, at the microscopic level, hydrogen bonds form between the polar groups of water molecules and resin molecular chains, thereby weakening intermolecular forces and enhancing the matrix’s ductility. Micro/macro failure analysis reveals the interfacial failure and fiber/matrix debonding, clarifying the hybridization mechanisms. This study provides theoretical insights into the penetration resistance design of HFRP under hygrothermal conditions.