Inspired by the macro- and microstructures of the lotus leaf, a series of biomimetic hierarchical thin-walled structures (BHTSs) was proposed and fabricated, exhibiting improved mechanical properties. The comprehensive mechanical properties of the BHTSs were evaluated using finite element (FE) models constructed in ANSYS, which were validated by the experimental results. Light-weight numbers (LWNs) were used as an index to assess these properties. The simulation results were compared with the experimental data to validate the findings. The compression results indicated that the maximum load carried by each BHTS was very similar, with the highest bearing load being 32,571 N and the lowest being 30,183 N, resulting in only a 7.9% difference between them. In terms of the LWN-C values, the BHTS-1 exhibited the highest value at 318.51 N/g, while the BHTS-6 had the lowest value at 295.16 N/g. For the torsion and bending results, these findings suggested that increasing the bifurcation structure at the end side of the thin tube branch significantly improved the torsional resistance properties of the thin tube. For the impact characteristics of the proposed BHTSs, enhancing the bifurcation structure at the end of the thin tube branch significantly increased the energy absorption capacity and improved the energy absorption (EA) and the specific energy absorption (SEA) values of the thin tube. The BHTS-6 had the best structural design in terms of both the EA and SEA among all the BHTSs, but its CLE value was slightly lower than that of the BHTS-7, indicating slightly lower structural efficiency. This study provides a new idea and method for developing new lightweight and high-strength materials as well as designing more effective energy absorption structures. At the same time, this study has important scientific value in understanding how biological structures in nature exhibit their unique mechanical properties.

Inspired by the macro/microstructures of starfish and beetle elytra, a series of bio-inspired structures (BSs) with improved comprehensive mechanical performance were proposed and fabricated. In the BS design, the principle of the branching structure of starfish was borrowed and each arm was endowed with calcified exoskeletons that can bend autonomously, enabling the starfish to move flexibly and adapt to changing shapes. At the same time, inspiration was taken from the concave-convex structure design principle of beetle elytra to enhance the internal complexity and mechanical performance of the BS. By increasing the number of polygons inside the thin-walled tubes, the performance of the BS in torsion and three-point bending was effectively improved. To evaluate the mechanical properties of the BS, finite element models were constructed using ANSYS and verified through experimental measurements. Universal testing machines and electronic torsion testers controlled by a microcomputer were used to study the compression, bending, and torsion properties of the BS. The results indicated that the differences in maximum compressive load-bearing capacity between each BS were small, and their lightweight compression values (LWN-C) remained unchanged, around 310 N/g. Increasing the number of polygons inside the thin-walled tubes effectively improved the performance of the BS in torsion and three-point bending. Moreover, the crashworthiness behaviors of the bio-inspired lightweight tube were also studied using a drop hammer impact tester. These findings have significant implications for the development of bio-inspired designs, particularly in the fields of machine arms, vehicle shafts, and bumpers, where lightweight yet high-strength structures are highly desirable.

With the aim of understanding cavitation damage of stainless steel under the effect of cavitation collapse in an aqueous environment, morphology, phase, chemical state, electrochemical, and other properties after cavitation and erosion are methodically examined. The obtained results indicate that the addition of metal ions in pure water strengthens the dynamic effect of cavitation collapse. When the cavitation collapses, it is capable of releasing a high temperature and transferring it to the surface of the stainless steel in a short time. Then, through the rapid cooling of the pure water environment, the martensitic structure is generated, but the presence of a massive amount of metal ions leads to a decrease in the speed of heat conduction and absorption of some heat. After the collapse of the bubble, the passivation film on the surface of the stainless steel incorporates into the creation of initial micropores. A concentration difference and a growth of the current density at the bottom of the hole, as well as a reduction in the pH value are detectable. Compared with pure water, 3.5% NaCl solution contains more free ions and its local current density is higher, so its corrosion resistance is worse.

Air quality index prediction research is of great significance to people’s life. Various prediction methods are used to pursue its accurate prediction. A novel BP neural network with wavelet transform inputs for air quality index prediction is proposed in this paper. The proposed method introduces wavelet transform in the front of the neural network. It decomposes the original time series signal into a linear superposition of the main signal and some noise signals. After establishing the predictive BP neural network for each decomposed signal, the air quality index is restored based on the linear additivity of wavelet decomposition. The simulation experiments show that the prediction accuracy of proposed method is high. The relative error of long-term prediction for 50 consecutive days is only 4.3994% for Xuzhou City’s air quality index. The research work provides a useful reference for air quality index prediction.