The glass sponge is a porous lightweight structure in the deep sea. It has high toughness, high strength, and high stability. In this work, a super-depth-of-field microscope was employed to observe the microstructure of the glass sponge. Based on its morphological characteristics, two novel bio-inspired lightweight structures were proposed, and the finite-element analyses (FEA) of the structures were carried out under compression, torsion, and bending loads, respectively. The structure samples were fabricated using stereolithography 3D-printing technology, and the dimension sizes of the samples were equal to those of the corresponding FEA models. Mechanical tests were performed on an electronic universal testing machine, and the results were used to demonstrate the reliability of the FEA. Additionally, lightweight numbers (LWN) were proposed to evaluate the lightweight efficiency, and a honeycomb structure was selected as the reference structure. The results indicate that the lightweight numbers of the novel bio-inspired structures are higher than those of the honeycomb structure, respectively. Finally, the proposed structures were optimized by the response surface, BP (Back Propagation) and GA-BP (Genetic Algorithm optimized Back Propagation) method. The results show that the GA-BP model after training has a high accuracy. These results can provide significant guidance for the design of tube-shaped, thin-walled structures in the engineering.

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.

In this study, an enhanced hybrid Grey Wolf Optimization algorithm (HI-GWO) is proposed to address the challenges encountered in traditional swarm intelligence algorithms for mobile robot path planning. These challenges include low convergence accuracy, slow iteration speed, and vulnerability to local optima. The HI-GWO algorithm introduces several key improvements to overcome these limitations and enhance performance. To enhance the population diversity and improve the initialization process, Gauss chaotic mapping is applied to generate the initial population. A novel nonlinear convergence factor is designed to strike a balance between global exploration and local exploitation capabilities. This factor enables the algorithm to effectively explore the solution space while exploiting the promising regions to refine the search. Furthermore, an adaptive position update strategy is developed by combining Levy flight and golden sine. This strategy enhances the algorithm’s solution accuracy, global search capability, and search speed. Levy flight allows longer jumps to explore distant regions, while golden sine guides the search towards the most promising areas. Extensive simulations on 16 standard benchmark functions demonstrate the effectiveness of the proposed HI-GWO algorithm. The results indicate that the HI-GWO algorithm outperforms other state-of-the-art intelligent algorithms in terms of optimization performance. Moreover, the performance of the HI-GWO algorithm is evaluated in a real-world path planning experiment, where a comparison with the traditional grey wolf algorithm and ant colony algorithm validates the superior efficiency of the improved algorithm. It exhibits excellent optimization ability, robust global search capability, high convergence accuracy, and enhanced robustness in diverse and complex scenarios. The proposed HI-GWO algorithm contributes to advancing the field of mobile robot path planning by providing a more effective and efficient optimization approach. Its improvements in convergence accuracy, iteration speed, and robustness make it a promising choice for various practical applications.

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.

High-manganese steel (HMnS) coating was prepared using laser wire feeding cladding technology. Erosion damage behavior and erosion rate of both the HMnS coating and the HMnS substrate were investigated at room temperature using an erosion testing machine. SEM/EDS, XRD, EPMA, and microhardness analyses were used to characterize the cross sections of the coating and matrix, as well as the morphology, phase composition, and microhardness of the eroded surface. The phase composition, orientation characteristics, and grain size of the eroded surfaces of both the coating and substrate were examined by using the EBSD technique. The erosion mechanism under different erosion angles was revealed. By analyzing the plastic deformation behavior of the subsurface of the HMnS coating, the impact hardening mechanism of the high-manganese steel coating during the erosion process was investigated. The results demonstrated that the HMnS coating, prepared through laser wire feeding cladding, exhibited excellent metallurgical bonding with the substrate, featuring a dense microstructure without any cracks. The erosion rate of the coatings was lower than that of the substrate at different erosion angles, with the maximum erosion rate occurring at 35° and 50°. The damage to the coating and substrate under low-angle erosion was primarily attributed to the micro-cutting of erosion particles and a minor amount of hammering. At the 90° angle, the dominant factor was hammering. After erosion, the microhardness of both the coating and substrate sublayer increased to 380HV0.3 and 359HV0.3, respectively. Dendrite segregation, refined grains, low-angle grain boundaries, and localized dislocations, generated by laser wire feeding cladding, contributed to the deformation process of HMnS. These factors collectively enhance the hardening behavior of HMnS coatings, thereby providing excellent erosion resistance.