Fiber hybridization can effectively solve the localized brittle fracture problem of composite honeycomb, but the interaction between different fibers leads to a very complex failure mechanism. Hence, 3D-printed hybrid continuous fiber composite honeycombs with a combination of carbon and Kevlar fibers are designed to study the structural failure behaviors by the experiment and simulation method. The experimental samples, including Onyx, carbon, Kevlar, carbon/Kevlar, and Kevlar/carbon composites, are fabricated based on Markforged 3D printing technology, and the crushing tests are conducted to evaluate the failure behaviors. An equivalence finite element modeling method to replace the heterogeneous microstructure of hybrid composites is proposed to analyze the failure behaviors. Results indicate that carbon/Kevlar honeycomb exhibits the highest energy absorption and cost effectiveness, while CFRP honeycomb demonstrates the highest load-carrying capacity. It is found that carbon/Kevlar and Kevlar/carbon honeycombs have significant hybrid effects compared to single-fiber honeycombs, which also reveals the hybrid mechanisms between carbon and Kevlar fibers. Furthermore, the Onyx honeycomb, lacking long fibers, exhibits brittle collapse, whereas other honeycombs show ductile collapse due to the presence of Kevlar fibers. Combining the simulation studies, the damage evolution mechanisms of honeycombs, including fiber/matrix tension and compression, shear damage, interface damage, etc., are further revealed. This work provides valuable insights into the design and failure analysis of 3D-printed hybrid fiber composite honeycombs.

Rigid polyurethane-based foam is an ideal choice for sandwich-panel-filling materials due to its high strength, low thermal conductivity, high adhesion, and high chemical resistivity. Since sandwich panel materials often face cyclic mechanical loads during their service, it is significant to study the design methods of fatigue-resistant rigid polyurethane foam and its fatigue failure mechanism to improve the performance of sandwich-panel-filling materials. In this study, a fatigue-resistant rubber powder/polyurethane composite material was prepared by introducing rubber powder, and its fatigue failure mechanism was systematically studied. The static mechanical test results indicate that with the introduction of 20% rubber powder, the compressive strength (at 85% strain) increased to 588 kPa. Additionally, thanks to the excellent energy absorption and dissipation properties of rubber powder, it can effectively dissipate mechanical energy during cyclic loading. The fatigue test results show that after the introduction of rubber powder, the fatigue life of the polyurethane foam material increases from 10,258 cycles (for PU, stress ratio 0.6) to 45,987 cycles (for 20R-PU, stress ratio 0.6). This study not only proves the fact that rubber powder can improve the fatigue performance of foam materials but also provides a potential option for the design of high-performance filling materials.

Based on the RNG k-ε turbulence model and VOF multiphase flow model, a numerical model of horizontal water-entry of the vehicle was established, and the numerical method was verified by experimental results. The cavitation characteristics, fluid resistance, and motion of the vehicle under different conditions were studied during the vehicle’s water-entry process. The results show that the cavitation process can be divided into the cavity development stage, saturation stage, and collapse stage. With the increase in initial velocity and mass of the vehicle, more water vapor will be generated during the water-entry process. The initial velocity of the vehicle had a limited effect on the resistance coefficient. The resistance coefficient in the stable stage remained almost unchanged for vehicles with different masses. Nevertheless, the time interval of the stable stage was shortened, and the resistance coefficient was greater in the gradually increasing stage for the vehicle with a smaller mass. For vehicles with higher initial velocity or smaller mass, the instantaneous velocity decreased faster after it entered the water. The vehicle with a streamlined design was able to reduce the generation of water vapor and decrease fluid resistance and its coefficient, and the vehicle can run farther during the water-entry process.

A hybrid aquatic–aerial vehicle (HAAV) is a novel type of aircraft capable of both aerial flight and underwater navigation. Inspired by the swan’s gliding and landing motion on water surfaces, this study investigates the dynamic modeling and integrated optimization design of an HAAV equipped with a biomimetic skipping plate. By comprehensively accounting for the aerodynamic, impact, hydrodynamic, and frictional forces during the water entry process, a dynamic model for the HAAV’s gliding water entry is established. The reliability of the model is verified through comparisons between numerical simulations and theoretical predictions. Parametric modeling of the skipping plate’s configuration and layout is performed to analyze the influence of different parameters on the water entry dynamics. With the objectives of minimizing the overload and pitch angle variation, a hybrid infilling strategy based on a radial basis function neural network (RBFNN) surrogate model is constructed to improve optimization efficiency. This is combined with a quantum-behaved particle swarm optimization (QPSO) algorithm to conduct the multi-objective optimization of the biomimetic plate, thereby obtaining its optimal configuration and layout parameters. The results demonstrate that the established dynamic model is effective and can accurately capture the kinematic characteristics of the gliding water entry process. The error between the peak load and the pitch angle variation is less than 5%. Compared with the direct QPSO algorithm, the proposed method reduces the number of model evaluations by 66.7%, the computational time by 52.1%, and the optimal solution response value by 12.01%, demonstrating strong potential for engineering applications.