This paper presents a practical human-computer interaction system for wheelchair motion through eye tracking and eye blink detection. In this system, the pupil in the eye image has been extracted after binarization, and the center of the pupil was localized to capture the trajectory of eye movement and determine the direction of eye gaze. Meanwhile, convolutional neural networks for feature extraction and classification of open-eye and closed-eye images have been built, and machine learning was performed by extracting features from multiple individual images of open-eye and closed-eye states for input to the system. As an application of this human-computer interaction control system, experimental validation was carried out on a modified wheelchair and the proposed method proved to be effective and reliable based on the experimental results.

A combination of simulation and experimental approaches to optimize the vacuum carburizing process is necessary to replace the costly experimental trial-and-error method in time and resources. In order to accurately predict the microstructure evolution and mechanical properties of the vacuum carburizing process, a multi-field multi-scale coupled model considering the interaction of temperature, diffusion, phase transformation, and stress was established. Meanwhile, the improved model is combined with the heat treatment software COSMAP to realize the simulation of the low-pressure vacuum carburizing process. The low-pressure vacuum carburizing process of 20CrMo gear steel was simulated by COSMAP and compared with the experimental results to verify the model. The results indicated that the model could quantitatively obtain the carbon concentration distribution, Fe-C phase fraction, and hardness distribution. It can be found that the carbon content gradually decreased from the surface to the center. The surface carbon concentration is relatively high only after the carburizing stage. With the increase in diffusion time, the surface carbon concentration decreases, and the carburized layer depth increases. The simulated surface carbon concentration results and experimental results are in good agreement. However, there is an error between calculations and observations for the depth of the carburized layer. The error between simulation and experiment of the depth of carburized layer is less than 6%. The simulated surface hardness is 34 HV lower than the experimental surface hardness. The error of surface hardness is less than 5%, which indicates that the simulation results are reliable. Furthermore, vacuum carburizing processes with different diffusion times were simulated to achieve the carburizing target under specific requirements. The results demonstrated that the optimum process parameters are a carburizing time of 42 min and a diffusion time of 105 min. This provides reference and guidance for the development and optimization of the vacuum carburizing process.

This paper addresses the effect of gear steel on distortion and residual stresses due to phase transformation in carburizing and quenching. In particular, the martensitic and bainitic phase transformation expansion and transformation plasticity properties of two automotive gearbox steels (20CrMnTiH and 20MnCr5) and their physical parameters are measured by experiments of transformation plasticity properties. Numerical simulations of the actual carburizing and quenching process of the gearbox spline helical gears were carried out in combination with the thermal and mechanical properties with temperature variations calculated by the material design software JMAT-Pro. In particular, the phase transformation properties of the two materials and their influence on the distortion and residual stresses after carburizing and quenching were verified by experiments of transformation plasticity and numerical simulations. A reliable basis is provided for predicting the distortion mechanism of gear steels in carburizing and quenching.

Linking to the S element hybrid strategies, S-doped carbon materials having different macrostructures and defect concentrations are prepared by using sulfur and coal-tar-pitch as raw materials in a carbonization temperature range of 700–1000 °C. The evaluations of macrostructure and surface characteristics are performed through XRD, TEM, Raman and XPS measurements. Through the linear fitting among the Na⁺ storage capacity with I_D/I_G and d₀₀₂ values, the correlations of Na⁺ storage capacity with macrostructures and defects are respectively investigated in detail. It is observed that S-doped carbon materials exhibit storage capacity at 120 mAh/g after the charge-discharge is being carried out 2000 cycles at 2.0 A/g. Studies have shown that adsorptions of introduced defects on graphene-like carbon sheets mainly play the role to enhance the storage capacity, and the expanded carbonaceous lamellar spaces of highly disordered and pseudo-graphitic macrostructures provide the channels for fast transfer of Na⁺. Our studies are able to provide references for designs and fabrications of coal tar pitch based soft carbon materials as sodium-ion batteries (SIBs) anodes when using heteroatoms doping methods.