Applied Composite Materials最新文献

SiCp/Al composites are widely used in many important engineering applications due to their excellent material properties. High-volume fraction SiCp/Al composites are recognised as a typical difficult-to-machining material with significant brittleness, and negative rake angles are more suitable for cutting brittle materials. Ultrasonic elliptical vibration cutting (UEVC) has proven to be a specialised machining method that can improve the machinability of difficult-to-machining materials. Elucidating the influence of the negative rake angle on the dynamic properties of composites during UEVC is therefore particularly important. In this paper, the direction of the combined cutting force is considered separately for negative rake angle tools, as well as UEVC's unique transient cutting thickness, variable cutting angle, transient shear angle and characteristic of friction reversal, a UEVC cutting force model based on negative tool rake angle has been developed. And the deviation of the main cutting force between the experimental value and the theoretical value is less than 15% by systematic turning experiments, which verifies the accuracy of the model. Finally, the influence of different machining parameters on the cutting force is determined using the established model. The results show its effect on the cutting force is more significant when the cutting speed is less than 200 mm/s, other things being equal. In addition, the cutting force tends to decrease significantly as the depth of cut from 5 μm to 20 μm increases. However, the cutting force fluctuated less when the feed was increased. This work provides the benchmark for negative rake angle cutting of SiCp/Al.

SiCp/A356 brake discs experience cyclic thermal loading during service, leading to a certain degree of mechanical deterioration in the brake disc material (SiCp/A356 composites), thereby reducing the thermal fatigue resistance of the brake disc, ultimately threatening the braking safety of urban rail trains. To investigate the mechanical deterioration patterns and mechanisms of the SiCp/A356 composites, thermal cycling experiments were conducted, along with simulation methods and microstructural analysis. The results indicate that the upper temperature limit of thermal cycling determines the microstructural damage modes and degree in SiCp/A356 composites, and the damage degree is positively correlated with mechanical deterioration. A temperature of 200 °C is identified as suitable for long-term service of SiCp/A356 composites. Thermal cycling induces thermal mismatch stress and residual stress within the material, serving as the primary driving forces for microstructural damage. Thermal cycling reduces the dislocation density in the near-interface (Al-SiC interface) matrix, improving the material's ductility. However, dislocation accumulation in the matrix far from the interface results in stress concentration, promoting matrix damage and crack formation, thereby compromising mechanical properties. The sole strengthening phase, Mg₂Si, is susceptible to aggregation and coarsening, leading to reduced mechanical properties after peak aging. The principal cause of interface crack is the stress concentration caused by dislocation accumulation, ultimately leading to interface failure. This research provides important guidance for the operation and maintenance of SiCp/A356 brake disc.

This study investigated the effectiveness of 3D woven structural composite-based aircrew helmets comprising a 3D woven solid shell and a 3D woven honeycomb liner. This research adopted a structured sequence of steps to integrate desired aircrew helmet properties. The study involved the analysis of 3D woven structural composites through quasistatic compression and dynamic impact tests to assess their compressive strength and impact energy properties, respectively. Initially, the study focuses on optimizing the honeycomb liner by adjusting its structural parameters to improve the compressive strength. The research then delved into the critical role of impact energy, aiming to enhance load transfer to the liner for maximal impact energy absorption. Key findings highlight that the L2T2H3 honeycomb liner configuration, when combined with the OR8L3M shell, significantly improves the protective performance by exhibiting superior impact energy, cushioning properties, and compressive strength. Factors such as weave architecture, impactor geometry, impactor velocity, and face sheet thickness were found to influence the energy absorption capacity, emphasizing the importance of structural design optimization. The combined use of helmet shell and liner components demonstrated superior energy absorption capabilities compared to individual components. This combination suggests a successful approach for achieving enhanced performance in aircrew helmets. By analyzing compressive strength and impact energy, this research contributes to the ongoing efforts to enhance the performance of aircrew helmets, thereby ensuring improved safety and protection for aircrew members operating in high-risk environments.

Carbon-Kevlar hybrid woven reinforcement materials have high specific strength and modulus, excellent fatigue resistance, which are widely used in aerospace applications. Due to its special mechanical properties by hybridization, the forming quality is affected by various factors such as reinforcement properties and process parameters. In order to improve the forming quality of Carbon-Kevlar hybrid woven reinforcement and reduce the forming defects, this paper proposes a new optimization method combined with genetic algorithm. Taking the maximum shear angle of the preform as the optimization objective, a genetic algorithm is used to optimize the load and size of the tetrahedral structure blank holder. The results indicate that the peak shear angle decreased from 52.14° to 43.90°, while the optimal forces on the five parts of the blank holder are RF₁ = 20 N, RF₂ = 26 N, RF₃ = 45 N, RF₄ = 14 N, RF₅ = 45 N, respectively, and the optimal gaps between the blank holder parts is BW₁ = 4 mm, BW₂ = 22 mm. Then, potential wrinkling areas were predicted by the in-plane negative strain. It was found that the minimum in-plane negative strain of the sample in the two main fiber directions was effectively controlled, and the negative strain distribution in the useful areas was more uniform, thereby reducing the potential wrinkling areas, indicating the effectiveness of the optimization method.

The sensitivity of carbon fiber composite laminate to impact damage makes impact damage a significant cause of composite material performance degradation. This study aims to investigate the influence of surface glass fibers on carbon fiber composite laminates under low-velocity impact. A user-defined VUMAT subroutine based on the Puck criterion was employed to implement an intralaminar damage model, while a bilinear cohesive model based on quadratic criterion in Abaqus was used to simulate interlaminar damage. By simulating the low-velocity impact behavior of carbon fiber laminates under three energy levels (2 J, 4 J, and 8 J), the predicted mechanical response results were compared with the experimental results from the literature to validate the rationality of the model. The mechanical response and damage evolution under impact loading were studied by adding glass fibers of different angles and thicknesses on the surface layer of carbon fiber laminate. The results show that increasing the thickness of surface glass fibers can effectively enhance the impact resistance of carbon fiber composite laminates, and a single layer glass fibers at 90° provides better protection than at 45°. The results of this study are instructive for the selection of the thickness as well as the angle of the glass fibers on the surface of carbon fiber composite laminates.

This study investigated the mechanical behaviour of glass fibre epoxy composites with and without an embedded polyethylene terephthalate (PET) substrate used for printed electronic applications, with the mechanical behaviour integrity studied under different loading modes: three-point bending, tensile, and short-beam stress (SBS) tests. The main objective of this study was to investigate the influence of the substrate location within the laminate. Fracture profiles were observed by visual inspection during the mechanical tests and scanning electron microscopy (SEM) after failure to identify differences in the damage mechanisms and their propagation. Tensile tests indicated that embedding the PET substrate did not affect the ultimate strength of the laminate, while the bending and SBS tests indicated that the substrate integration reduced the bending strength and ILSS by 10% and 50%, respectively, depending on the substrate location.

A multiscale model is developed for stress analysis and burst speed prediction of a titanium matrix composite (TMC) ring. The proposed multiscale model is based on finite-volume directly averaging micromechanics (FVDAM) to connect the TMC ring and the composite microstructure. Moreover, Bodner-Partom’s constitutive model is adopted to characterise the viscoplasticity of the titanium cladding and the matrix. The effects of viscoplasticity on the mechanical behaviour and burst speed of the TMC ring are presented and discussed for the first time via macromechanical and micromechanical analysis. The results suggest that considering the viscoplasticity of the titanium matrix and cladding leads to a decrease in the burst speed of the TMC ring, especially at elevated temperatures such as 315 ℃ and 482 ℃. Burst rupture of the TMC ring also occurs after a certain time in the load-holding stage at these elevated temperatures and a low, constant angular speed, even though no burst rupture is predicted in the loading stage. Hence, the newly defined load-holding burst speed, which is relative to the load-holding time, is predicted at elevated temperatures. The results of the load-holding burst speed provide more comprehensive information on the safety assessment of a TMC ring at elevated temperatures.

In this work, a numerical model was developed to investigate the layer wise temperature distribution during microwave curing to manufacture carbon fiber composites using COMSOL Multiphysics^® software package. A multivariable nonlinear regression analysis was conducted to acquire the cure kinetics parameters based on the heating rate. The resulting model demonstrated temperature and percentage degree of cure prediction accuracy within an error margin of 6% and 0.62%, respectively. In addition, a comparison was made between the contour of temperature distribution across different layers. The correlation with experimental and simulation data revealed that uniform heating occurred at 180 W due to a longer cycle time compared to power levels of 360 W, 540 W, and 720 W, in the presence of a standing wave. Conversely, the model indicated a temperature gradient of approximately 8.7 ℃, 10.2 ℃, 24.6 ℃, and 36.6 ℃ between the first and last layer for power levels of 180 W, 360 W, 540 W, and 720 W, respectively. Utilizing a dwell period of 65 s at a temperature of 100 ℃, the gradient between the first and last layer reduced to approximately 5.21 ℃, 7.97 ℃, 8.91 ℃, and 9.04 ℃ for power levels of 180 W, 360 W, 540 W, and 720 W, respectively, at the end of the curing process. Furthermore, a comparative examination of temperature distribution and degree of cure at 180 W revealed a higher degree of cure in regions where the temperature was elevated due to the standing wave.

Graphical Abstract

The accurate prediction of failure of load-bearing fiber-reinforced structures remains a challenge due to the complex interacting failure modes at multiple length scales. In recent years however, there has been considerable progress, in part due to the increasing sophistication of advanced numerical modelling technology and computational power. Advanced discrete crack and cohesive zone models enable interrogation of failure modes and patterns at high resolution but also come with high computational cost, thus limiting their application to coupons or small-sized components. Adaptively combining high-fidelity with lower fidelity techniques such as smeared crack modelling has been shown to reduce computational costs without sacrificing accuracy. On the other hand, machine learning (ML) technology has also seen an increasing contribution towards failure prediction in composites. Leveraging on large sets of experimental and simulation training data, appropriate application of ML techniques could speed up the failure prediction in composites. While ML has seen many uses in composites, its use in progressive damage is still nascent. Existing use of ML for the progressive damage of composites can be classified into three categories: (i) generation of directly verifiable results, (ii) generation of material input parameters for accurate FE simulations and (iii) uncertainty quantification. Current limitations, challenges and further developments related to ML for progressive damage of composites are expounded on in the discussion section.