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In this study, the performance of braided composite tubes under low-velocity transverse impact loading at mid-span was investigated using both numerical and experimental methods. Three types of braided composite tubes with different braiding angles (30°, 45°, and 60°) were manufactured. The transverse punch behavior of the tubes was examined on a low-velocity imspact test bench. A meso-level finite element model of the composite tube was also established for identifying the damage initiation and development. The numerical results showed a good correlation with the experimental data. The mechanical response including force–time histories, force–displacement histories, and fracture morphologies was compared between three types of composite tubes for analyzing the influence of braiding angle on the impact response and failure mode. Although suffering from the low bending stiffness depends on fiber volume fraction at initial impact stage, the braided tube with 30° angle engaged more portion to resist impact loading in subsequent process and thus presented higher peak loading than the one with large angle. In addition, there are distinct different failure modes between composite tubes with various braiding angles. Shear yarn breakage underneath the punch was prone to occur in 30° sample because the braiding yarn was closer to the axial direction of tube. In contrast, the resin was deboned severely from the braiding yarn and then the braiding yarn exhibits plastic deformation in 60° sample due to the stress concentration caused by the large braiding angle.

Custom socks, such as medical compression socks and hiking socks, are precisely designed and knitted according to the user's foot shape. However, developing styles of custom socks with commercial computer-aided design software requires workers to manually calculate the knitting parameters, and repeatedly adjust the knitting parameters through sample-making to meet the design requirements. We present a method to optimize the manual calculation and adjustment process of knitting parameters by using graphics technology. Our method converts a sock mesh model created by conventional modeling software into knitting parameters. Hosiery machines are able to knit socks with the same dimensions as the mesh based on the output parameters. Specifically, given user-defined top and toe markers on an input mesh, our system runs a sampling procedure over this mesh to gradually generate a knitting path that contains shape and dimension features of the mesh, and transforms the knitting path into knitting parameters for machine knitting. We demonstrated the feasibility of our method by knitting on a computerized hosiery machine. Filling the knitted socks with a soft foam model, we found that the knitted socks fit roughly well with the mesh surface, and the dimensional gap between the input mesh and the knitted socks (relaxed state) in several positions was below 4.90%.

Aiming at the problem of the malfunction of knitting machines caused by the unstable operation of the piezoelectric needle selector during the jacquard process, a state detection scheme for the piezoelectric needle selector that integrates the sensor and drive function co-located is proposed. The motion state of bimorph piezoelectric cantilever beam and its bi-directional piezoelectric effect in the jacquard process of piezoelectric needle selector are analyzed. Electrical and dynamic models were established for the electrical characteristics inside the bimorph piezoelectric cantilever beam and the dynamic characteristics of the cutter head and baffle of the needle selector. The signal detection circuit is designed to realize the real-time detection of the piezoelectric needle selector state by analyzing the time domain and frequency domain characteristics of the electrical signal. The results show that in the normal working state of the piezoelectric needle selector, the internal electric signal of the piezoelectric driver has two characteristic frequencies, which are between 155 and 180 and between 1630 and 1670 Hz, and the time for the piece to swing to the limit position is relatively long under abnormal working conditions.

Novel multifunctional Janus‐type membrane with both hydrophobic and anticorrosion abilities is constructed on the surface of aluminum (Al), using MoS2 as a hydrophobic layer and ZnO as a corrosion‐resistant layer. Al anode coated with the Janus‐type membrane is used as an example to study the specific property of the as‐prepared Janus‐type membrane. In the Al–air battery, the self‐corrosion of the Al anode is well inhibited since the Janus‐type membrane can block the invasion of excess hydroxide ions and water molecules simultaneously. The results show that the inhibition efficiency of the Janus‐type membrane is as high as 79.2%. Furthermore, the electrochemical measurements demonstrate that the discharge specific capacity of the Al–air battery with the Janus‐type membrane can reach up to 2095 mAh g−1, approximately two times as much as that of traditional batteries. The integrated strategy of combining hydrophobic and anticorrosion membrane is a novel method for corrosion protection of metal electrode. This Janus‐type membrane holds a great potential toward corrosion inhibition for the other metal in alkaline environment as well.

In this study, a dual-piezoelectric energy harvesting system with contact and non-contact characteristics was driven by a cantilever beam. The harvester performance of the multipoint energy harvesting system driven by cantilever-beam vibration was designed, detailed analysis and optimization strategies were developed, and its application in the security field was successfully demonstrated. Herein, we provide theoretical guidance for the design of the dual-piezoelectric energy harvesting. We designed and fabricated a prototype of the dual-piezoelectric energy harvesting. A test system was designed and constructed. The relationships among the distance and frequency of the two piezoelectric acquisition mechanisms and the open-circuit voltage were investigated. Additionally, the effects of different loads on the output power were examined. The peak power reached 10.12 mW under a gravitational acceleration of 1g. The analysis indicated that the dual-piezoelectric energy harvest device has a higher energy harvest efficiency than the singlepiezoelectric energy harvest device. Owing to the multipoint harvest strategy, even if a generator suddenly deteriorates or fails, the entire system can maintain a certain power output, which is more commercially feasible. The results of this study indicate that the output of the piezoelectric energy harvesting is stable and reliable and that the output energy satisfies the requirements for a safety warning device.

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To achieve accuracy when customizing knitted products, the size parameters of various parts of the user's body, such as arm length and waist circumference, are obtained via manual measurement or three-dimensional scanning. However, for customized products such as medical socks, which have high-precision design requirements, the existing customization design methods can only ensure the accuracy of key data, such as foot length and foot height, but cannot meet the requirements for all-round customization based on users' foot data. To improve design accuracy, this study proposes a method to generate automatically a continuous set of fine size parameters that are required for knitting from a three-dimensional model of socks based on the idea of simulated knitting. Specifically, a region segmentation method based on the shape diameter function and model skeleton is developed. The sock model is divided into regions such as heel, foot, and toe, which correspond to the knitting process. In addition, a method to simulate the knitting process of a sock machine is developed, which enables loop-by-loop knitting using a sock machine via layer-by-layer iterative sampling on the surface of the model. The sampling axis is generated based on the model skeleton as the direction of sock knitting for the simulation. In the process of simulating knitting, the knitting method is switched between the divided area. Then, the knitting path of the yarn and the parameters required for the simulated sock machine that meet the sock-making process conditions are obtained. Finally, actual socks are knitted using the machine with the obtained knitting parameters, and the proportion of each area of the socks is compared with that of the model. The error is less than 6%. The proposed method can improve the production accuracy of customized socks, which is of great significance for improving the three-dimensional molding technology of socks.