In this study, an annular jet pump optimization method is proposed based on an RBF (Radial Basis Function) neural network model and NSGA-II (Non-Dominated Sorting Genetic Algorithm) optimization algorithm to improve the hydraulic performance of the annular jet pump applied in submarine trenching and dredging. Suction angle, diffusion angle, area ratio and flow ratio were selected as design variables. The computational fluid dynamics (CFD) model was used for numerical simulation to obtain the corresponding performance, and an accurate RBF neural network approximate model was established. Finally, the NSGA-II algorithm was selected to carry out multi-objective optimization and obtain the optimal design variable combination. The results show that the determination coefficient R² of the two objective functions (jet pump efficiency and head ratio) of the approximate model of the RBF neural network were greater than 0.97. Compared with the original model, the optimized model’s suction angle increased, and the diffusion angle, flow ratio and area ratio decreased. In terms of performance, the head ratio increased by 30.46% after the optimization of the jet pump, and efficiency increased slightly. The proposed jet pump performance optimization method provides a reference for improving the performance of other pumps.

CFD simulation and analysis of the internal flow field of the annular multi-nozzle jet pump are carried out to study the effects of nozzle section geometries on performance of the pump based on the finite volume method and realizable k-ε model. The results show that the square nozzle peak efficiency is 3% higher than that of the circular nozzle and 4.1% higher than that of the triangular nozzle. According to the simulation results, the mixing mechanism of the working fluid and second fluid is analyzed on the basis of the vortex dynamics. The results show the following: the recirculation area and the friction loss of the non-circular nozzle are reduced, and the mixing effect is improved; the streamwise vortex plays a major role in the mixing process and decays to an extremely small value at the end of the throat after attenuating rapidly in the suction chamber; compared with the streamwise vortex, the strength of the spanwise vortex is relatively stronger; the spanwise vortex still fluctuates after developing to a certain extent in the throat; the maximum streamwise vorticity peak value of the square nozzle is 31% more than that of the circular nozzle and 39% more than that of the triangular nozzle; the maximum spanwise vorticity peak value of the square nozzle is 19% less than that of the circular nozzle and 12% less than that of the triangular nozzle.

Bionic amphibious robots are the intersection of biology and robotics; they have the advantages of environmental adaptability and maneuverability. An amphibious robot that combines walking and swimming move modes inspired by a crab (Portunus) is presented in this article. The outstanding characteristic of the robot is that its environmental adaptability relies on the bionic multi-modal movement, which is based on two modular bionic swimming legs and six modular walking legs. We designed the biomimetic crab robot based on the biological observation results. The design, analysis, and simulation of its structure and motion parameters are introduced in this paper. The swimming propulsion capability and the walking performance are verified through indoor, pool, and seaside experiments. In conclusion, the designed bionic crab robot provides a platform with practical application capabilities in amphibious environment detection, concealed reconnaissance, and aquaculture.

Jet pump efficiency heavily relies on the geometrical parameters of the pump design and parameter global optimization in the full variable space is still a big challenge. This paper proposed a global optimization method for annular jet pump design combining computational fluid dynamics (CFD) simulation, the Kriging approximate model and experimental data. The suction angle, the flow ratio, the diffusion angle, and the area ratio are selected as the design variables for optimization. The optimal space filling design (OSF) method is used to generate sampling points from the design space of the four design variables. The optimization method solves the constrained optimization problem with a given head ratio by building the functional relationship established by the Kriging model between efficiency and design parameters, which makes the method more applicable. The design result shows that the annular jet pump efficiency is predicted well by the Kriging model; m is a key variable affecting the annular jet pump efficiency. As the area ratio m decreases, the mixing effect at the suction chamber outlet can be improved, but the frictional resistance increases.

Bionic-legged robots draw inspiration from animal locomotion methods and structures, demonstrating the potential to traverse irregular and unstructured environments. The ability of Portunus trituberculatus (Portunus) to run flexibly and quickly in amphibious environments inspires the design of systems and locomotion methods for amphibious robots. This research describes an amphibious crab-like robot based on Portunus and designs a parallel leg mechanism for the robot based on biological observations. The research creates the group and sequential gait commonly used in multiped robots combined with the form of the robot’s leg mechanism arrangement. This research designed the parallel leg mechanism and modeled its dynamics. Utilizing the outcomes of the dynamics modeling, we calculate the force and torque exerted on each joint of the leg mechanism during group gait and sequential gait when the robot is moving with a load. This analysis aims to assess the performance of the robot’s motion. Finally, a series of performance evaluation experiments are conducted on land and underwater, which show that the amphibious crab-like robot has good walking performance. The crab-like robot can perform forward, backward, left, and right walking well using group and sequential gaits. Simultaneously, the crab-like robot showcases faster movement in group gaits and a more substantial load capacity in sequential gaits.

Amphibious environments formed from sand and water present a formidable challenge to the running motion of field robots, as the mixing of granular media (GM) and water makes the force laws of robotic legs more complicated during robot running. To this end, we extended the granular resistive force theory (RFT) to saturated wet granular media, named saturated granular RFT (SGRFT), which can be suitable for saturated wet sand submerged in water. This method can extend RFT for dry GM to saturated wet granular media (SWGM) by using the method’s velocity and depth coefficient. The force laws of the robotic legs in dry GM and SWGM were tested, compared, and analyzed. The difference in force laws between the two kinds of media, from the sensitivity to speed (10 mm/s~50 mm/s) and depth (0~60 mm), was calculated. More than 70% of the prediction results of the horizontal resistive force using SGRFT have an error of less than 6%. The effectiveness of the SGRFT in legged robots is proved by simulation and testing of three kinds of legs. The difference in force laws when running is proved by the experiments of the robot equipped with the propeller-leg in dry GM and SWGM, which is vital for amphibious robots working in shoal environments (including dry GM and SWGM ground).