Efforts to enhance the speed and reduce the energy consumption of underwater vehicles have led to the proposal of a novel mucus release structure inspired by the secretion of mucus cells on fish skin. This structure features interconnected microgrooves with excellent flexibility for adjusting to different states, effectively reducing drag through mucus release. Numerical analysis of the drag reduction performance of the mucous-releasing micro-pore structure was conducted using ANSYS Fluent 19.2 software. This structure is capable of reducing the velocity gradient near the wall and, owing to the presence of micro-pore structures, decreasing the overall compressed area, thereby achieving drag reduction effects. The experimental results revealed a drag reduction effect of 20.56% when the structure was bent at an angle of 120°. The drag reduction varied under different attitudes such as tension and compression. This mucus release structure achieves reusability through a direct mucous injection process. This research provides valuable insights for the drag reduction study of underwater vehicles, such as ships and submarines, laying a foundation for advancing the development and applications of this field in the future.

Underwater vehicles typically rely on batteries or other energy sources for operation, where drag reduction can significantly lower energy consumption and extend operational endurance. Inspired by the skin structure of loaches, a flexible structure with scales and mucus pores was designed. First, numerical simulations were conducted. To accurately demonstrate the interaction between the flexible flow field and the fluid flow field and to capture the movement boundaries of the plates, a bidirectional fluid–structure interaction simulation method was used. The numerical results indicate that the flexible structure has a positive effect on drag reduction. In channel experiments, the drag reduction effects of flexible and non-flexible structures were compared. Both showed optimal drag reduction at a water flow speed of 2 m/s and mucus flow speed of 0.1 m/s. The maximum drag reduction rate for the flexible structure was 28.5%, compared to 22.8% for the non-flexible structure. This difference is attributed to the flexible structure altering the flow pattern of the near-wall boundary layer, reducing the velocity gradient of the boundary layer, and increasing its thickness. The findings of this study can provide guidance for future research on flexible surface drag reduction technologies.

Visualizing the near-field distribution of microwave field in a monopole antenna is very important for antenna design and manufacture. However, the traditional method of measuring antenna microwave near field distribution by mechanical scanning has some problems, such as long measurement time, low measurement accuracy and large system volume, which seriously limits the measurement effect of antenna microwave near field distribution. In this paper, a method of microwave near-field imaging of a monopole antenna using a nitrogen-vacancy center diamond is presented. We use the whole diamond as a probe and camera to achieve wide-field microwave imaging. Because there is no displacement structure in the system, the method has high time efficiency and good stability. Compared with the traditional measurement methods, the diamond probe has almost no effect on the measured microwave field, which realizes the accurate near-field imaging of the microwave field of the monopole antenna. This method achieves microwave near-field imaging of a monopole antenna with a diameter of 100 µm and a length of 15 mm at a field of view of 5 × 5 mm, with a spatial resolution of 3 µm and an imaging bandwidth of 2.7~3.2 GHz, and an optimal input microwave phase resolution of 0.52° at a microwave power of 0.8494 W. The results provide a new method for microwave near-field imaging and measurement of monopole antennas.

This review summarizes advancements in flexible pressure sensor design, including materials, devices, algorithm design, and systems, using bibliometric methods. The materials used in the system section are sourced from Vecteezy (Vecteezy.com).

This paper proposes a new type of flexible force-sensitive structure that is resistant to gamma radiation and is made of tungsten oxide (WO₃) powder, polydimethylsiloxane (PDMS), and carbon nanotube (CNT) sponge. The thickness of the sample was 2.2 mm, the middle interlayer was composed of a carbon nanotube (CNT) sponge and PDMS to form a conductive layer, and the upper and lower layers were made of tungsten oxide and PDMS, which formed a gamma-ray shielding layer. When the particle size of the tungsten oxide powder was 50 nm, 100 nm, and 1 µm, the composite force-sensitive structure exhibited better force-sensitive performance. The composite force-sensitive structure was irradiated with doses of 5, 20, 50, and 100 KGy through 60Co- rays with an energy of 1.25 MeV. The results showed that the force-sensitive characteristics changed little in significance after irradiation by different doses of gamma rays, indicating that the force-sensitive structure has good resistance to gamma radiation. This flexible stress sensor can be used in soft robots and health inspection, even in harsh environments without significant performance loss.

A fast and accurate bauxite recognition method combining an attention module and a clustering algorithm is proposed in this paper. By introducing the K-means clustering algorithm into the YOLOv4 network and embedding the SE attention module, we calculate the corresponding anchor box value, enhance the feature learning ability of the network to bauxite, automatically learn the importance of different channel features, and improve the accuracy of bauxite target detection. In the experiment, 2189 bauxite photos were taken and screened as the target detection datasets, and the targets were divided into four categories: No. 55, No. 65, No. 70, and Nos. 72–73. By selecting the category volume balanced datasets, the optimal YOLOv4 network model was obtained after training 7000 times, so that the average accuracy of bauxite sorting reached 99%, and the reasoning speed was better than 0.05 s. Realizing the high-speed and high-precision sorting of bauxite greatly improves the mining efficiency and accuracy of the bauxite industry. At the same time, the model provides key technical support for the practical application of the same type of engineering.