The dynamic mechanical behavior of thermoplastic composites over a wide range of strain rates has become an important research topic for extreme environmental survivability in the fields of military protection, aircraft safety, and aerospace engineering. However, the dynamic compression response in the out-of-plane direction, which is one of the most important loading conditions resulting in the damage of composite materials, has not been investigated thoroughly when compared to in-plane compression and tensile behavior under high strain rates. Thus, we used split Hopkinson pressure bar (SHPB) tests to conduct the out-of-plane compression test of cross-ply carbon fiber-reinforced polyetheretherketone (AS4/PEEK) composite laminates. Afterward, the damage mechanism under different strain rates was characterized by the macrostructure morphologies and scanning electron microscope micrographs. Two major cases of the incomplete failure condition and complete failure condition were discussed. Dynamic stress-strain curves expound the strain rates dependencies of elastic modulus, failure strength, and failure strain. An obvious spring-back process could be observed under incomplete failure tests. For the complete failure tests, secondary loading could be observed by reconstructing and comparing the dynamic response history. Lastly, various failure modes that occurred in different loading strain rates illustrate that the damage mechanism also shows obvious strain rate sensitivity.

The widespread use of composite materials has led to an increased focus on restoring the mechanical properties of damaged composite structures to ensure system safety. This study combines compression experiments and finite element simulations to investigate the effectiveness of different patch sizes and repair methods, including single- and double-sided repairs, in restoring the structural strength of composite laminates with barely visible impact damage (BVID). The results demonstrate that low-velocity impact significantly affects the strength of the laminate, reducing it to 68.53% of its original strength, highlighting the necessity of patch repair. For composite specimens repaired using patching, an increase in the patch radius consistently enhances strength recovery, reaching up to 93.96% of the original strength. However, this also leads to an increase in weight, suggesting that the patch radius should be selected based on the specific requirements of the application. Furthermore, double-sided patching is preferable to single-sided patching. This approach improves the repair efficiency by 4.96%, primarily due to its ability to provide a more uniform stress distribution. Consequently, the risk of premature buckling and failure under compressive loading is significantly reduced, ensuring improved structural integrity and durability. The finite element simulation results presented in this study align well with the experimental findings, with a maximum error of no more than 10.68%. In conclusion, this work provides reliable guidance for the optimal patch repair of composite structures and lays a solid foundation for the practical application of patch repairs in engineering.

In the article, we propose a new method to generate representative volume element (RVE) of random spatial distributions with cylindrical fibers and spherical particles based on the Improved Artificial Bee Colony (IABC) algorithm. In this employed bee phase of IABC, the proposed algorithm adopts a new search strategy, which improves the computational efficiency. To analyze the differences between the fiber distribution generated by this algorithm and the actual fiber distribution, we conducted statistical analysis on the distribution of the generated RVE. The statistical analysis results of the nearest neighbor distance (NND), Second-order intensity function, and pair correlation function were in good agreement with the experiment and complete spatial randomness (CSR) patterns. In addition, the predicted elastic properties were compared with experimental measurements and theoretical prediction methods. The results demonstrate the accuracy and efficiency of the proposed algorithm. This algorithm can quickly generate the RVE of cylindrical fibers and spherical particles with volume fractions of 80% and 62%, and the calculation time for generating the RVE of cylindrical fibers is about 17s.

To reduce the reliance on large training sets for representative volume element (RVE) generation using machine learning, this work presents a novel approach based on physics-informed neural network (PINN) to generate RVEs for unidirectional fiber-reinforced composites with non-uniform fiber distributions and high-volume fractions. The method embeds physical constraints including fiber non-overlap, volume fraction, and boundary conditions directly into the neural network’s loss function. This integration eliminates the need for large training datasets, which is typically required by traditional machine learning methods. Moreover, it achieves volume fractions exceeding 0.8, surpassing the jamming limit of conventional generation techniques. Exhaustive statistical measurements taken at different scales confirm that the proposed method could accurately reproduce local fiber distribution patterns in realistic microstructures while maintaining complete randomness at larger scales. Finite element analysis was employed on the generated RVEs to predict the elastic properties and damage behavior that taking into account the interfacial debonding and nonlinear damage in matrix. The predictions of both macroscopic mechanical properties (elastic properties and strength) and microscopic damage patterns show good agreement with experimental results. The proposed PINN-based framework provides an efficient and reliable tool for computational micromechanics of polymer matrix composites.

This study explores the vibration damping performance of a lightweight, compact, and highly efficient nonlinear damping device—NiTiNOL–steel wire rope (NiTi–ST). Based on the improved Bouc–Wen (BW) model, a formula for the equivalent dynamic elastic modulus of NiTi–ST was derived, and tensile tests were conducted to determine its constitutive parameters. The hysteresis behavior of NiTi–ST under various tensile displacement limits was accurately reproduced, with simulation results achieving Pearson correlation coefficients (PCCs) no lower than 0.97. Subsequently, the vibration suppression capabilities of three different NiTi–ST configurations were evaluated under various excitation conditions. Under impact excitation, the six NiTi–STs configuration achieved a vibration reduction of 74.95%, while the three NiTi–STs configuration demonstrated optimal performance under random excitation, with a 47.15% reduction. These findings highlight the excellent damping performance of NiTi–ST and demonstrate that higher NiTi–ST deployment densities significantly improve the structure’s resistance to impact. Simulation results under impact excitation further indicated that the average simulation error of blade was 6.68%, and the integration of NiTi–ST had minimal impact on the stress distribution and modal shapes of the blades, thus preserving the structure’s original design characteristics. Detailed analyses revealed that, to achieve optimal vibration suppression, a multi-directional NiTi–ST configuration is essential, as it alleviates stress concentrations and extends the operational lifespan of the blade. In conclusion, as a novel nonlinear damper, NiTi–ST demonstrates exceptional damping performance and mechanical properties, making it a promising solution for aerospace applications.