The surface integrity of ultra-high-strength steel has a significant influence on service performance, and cutting fluid plays an important role in maintaining surface integrity in production. In this paper, the surface integrity of ultra-high-strength steel 45CrNiMoVA was investigated under three cutting fluids: HY-103 (micro-emulsion), TRIM E709 (emulsion), and Vasco 7000 (micro-emulsion) from the aspects of cutting force, surface morphology, residual stress, micro hardness, microstructure, etc. The results showed that the changing trend of the cutting forces in three directions is HY-103 > Vasco 7000 > TRIM E709. The TRIM E709 contains the maximum lubricants, which reduce cutting force and Sa roughness, while the Vasco 7000 contains the minimum corrosive elements, which results in the least pitting. Both tangential and axial stresses under cutting fluid are tensile stresses. TRIM E709 and Vasco 7000 are reduced axially by 4.45% and 7.60% relative to HY-103, respectively. The grain refinement layer depths of HY-103, TRIM E709, and Vasco 7000 are 9 μm, 4 μm, and 8 μm, respectively, and TRIM E709 can induce recrystallized grains to grow along {001} of the sample cross section, which results from the lowest cooling rate. This work may provide an innovative control strategy for cutting fluid to improve surface integrity and service performance.

The friction between cutting tools and the workpiece/chip can significantly affect the tool wear, cutting force, cutting temperature, machined surface integrity, and machined parts’ service performance

研究了空间单位区域内两个曲面映射构成的动力系统的混沌特性. 研究发现两个曲面中有一个曲面振荡剧烈，另外一个曲面随机生成时系统更容易出现混沌，能生成众多有特点的混沌吸引子. 如果调整随机曲面使其成为满射，那么所构成的动力系统是混沌的概率可以达到1/2或者更高. 通过计算Lyapunov 指数以及绘制分岔图等方法对系统的混沌特性进行分析，同时给出了由两个曲面构造的系统出现混沌的必要条件. 和二维情形一样，一个三维正弦函数与两个三维多项式函数构造的动力系统是混沌的概率也很高，通过计算可以得到众多的具有观赏和实用价值的三维吸引子.

Microlens arrays have been widely employed to control the reflection, refraction, and diffraction characteristics of light due to its distinctive surface properties. Precision glass molding (PGM) is the primary method for the mass production of microlens arrays, of which pressureless sintered silicon carbide (SSiC) is a typical mold material due to its excellent wear resistance, high thermal conductivity, high-temperature resistance, and low thermal expansion. However, the high hardness of SSiC makes it hard to be machined, especially for optical mold material that requires good surface quality. The lapping efficiency of SSiC molds is quite low. and the underlying mechanism remains insufficiently explored. In this study, an experimental study has been performed on SSiC. A spherical lapping tool and diamond abrasive slurry have been utilized and various parameters have been carried out to achieve fast material removal. The material removal characteristics and damage mechanism have been illustrated in detail. The findings reveal that the material removal mechanism involves a combination of ploughing, shearing, micro-cutting, and micro-fracturing, which aligns well with the results obtained from finite element method (FEM) simulations. This study serves as preliminary reference for the optimization of the precision machining of SSiC PGM molds with high efficiency and good surface quality.

Surface quality has a significant impact on the service life of machine parts. Grinding is often the last process to ensure surface quality and accuracy of material formation. In this study, a high-quality surface was developed by determining the coefficient of friction in grinding a quartz fiber-reinforced silica ceramic composite. By processing the physical signals in the grinding process, a multi-objective function was established by considering grinding parameters, i.e., surface roughness, coefficient of friction, active energy consumption, and effective grinding time. The weight vector coefficients of the sub-objective functions were optimized through a multi-objective evolutionary algorithm based on the decomposition (MOEA/D) algorithm. The genetic algorithm was used to optimize the process parameters of the multi-objective function, and the optimal range for the coefficient of friction was determined to be 0.197~0.216. The experimental results indicated that when the coefficient of friction tends to 0.197, the distribution distance of the microscopic data points on the surface profile is small and the distribution uniformity is good. When the coefficient of friction tends to 0.216, the surface profile shows a good periodic characteristic. The quality of a grinding surface depends on the uniformity and periodicity of the surface’s topography. The coefficient of friction explained the typical physical characteristics of high-quality grinding surfaces. The multi-objective optimization function was even more important for the subsequent high-quality machining of mechanical parts to provide guidance and reference significance.