A new wear prediction method of tooth surfaces of involute gears based on a real tooth surface model and a modified fractal method is developed. The real tooth surface model of an involute gear pair is introduced, and microgeometry feature detection of tooth surfaces is achieved by monitoring variations of normal vectors of each discrete data point of the real tooth surface model. To predict wear progression of tooth surfaces of a gear pair, an abrasive wear analysis model and the modified fractal method are used to analyze contact performance and its changes with accumulation of surface wear. The abrasive wear analysis model can analyze wear depths of gear tooth surfaces with sliding distances, local contact pressure, and directions of wear progression based on Archard's model. The modified fractal method is proposed to calculate instantaneous contact stiffness and estimate elastic and plastic deformation regions based on an asperity contact model. Microgeometry features of tooth surface asperities can be described as the basis of an asperity contact model and allow tooth contact analysis of real tooth surface models with their local microgeometry feature changes due to plastic deformations. Feasibility and effectiveness of this wear prediction method were verified by comparing predicted results of gear surface wear progression with gear wear test results.

Scratches in fused silica are notorious laser damage precursors to UV laser damage initiation. Ductile and brittle scratches were intentionally generated using various polishing slurries. The distribution, profile and the dimension of scratches were characterized. The damage resistance of polished surfaces was evaluated using raster scanning damage testing protocol. The results show that both ductile and brittle scratches greatly increase area proportion of laser damage about one to two orders of magnitude relative to unscratched surface and brittle scratches are more deleterious. Moreover, finite difference time domain (FDTD) simulation was used to numerically calculate the light field distribution around scratches on rear surface (i.e. exit surface for light) which indicates that modulated light intensity is susceptible to the profile and size of scratches. FDTD simulation results also indicate that the light field intensification is elevated with the dimension of scratches and light modulation effects in triangular scratches are usually not as notable as serrated and parabolic scratches.

The thermal error of high-precision computer numerical control (CNC) form grinding machine has become the critical factor affecting its locating precision. Because the thermal error is more complicated to be measured directly, most of the measurement tests are usually aimed at no-load conditions. In this article, a method to evaluate the machine tool thermal error based on the principle of tooth profile error through the gear grinding precision is presented. Based on high-precision CNC form grinding machine need to maintain isoperibol, this paper proposed the ambient temperature as a variable, for different ambient temperature to measure the thermal error of the machine tool. According to the measurement results of the thermal error, the method of partial least squares neural network is used to structure the thermal error prediction model of the machine tool. The experimental data show that the grade of the gear precision can reach four levels at different temperatures. This approach shows a promising prospect in the application of high-precision CNC gear form grinding machine in the future.

Gears are pivotal in mechanical drives, and gear contact analysis is a typically difficult problem to solve. Emerging isogeometric analysis (IGA) methods have developed new ideas to solve this problem. In this paper, a three-dimensional body parametric gear model of IGA is established, and a theoretical formula is derived to realize single-tooth contact analysis. Results were benchmarked against those obtained from commercial software utilizing the finite element analysis (FEA) method to validate the accuracy of our approach. Our findings indicate that the IGA-based contact algorithm successfully met the Hertz contact test. When juxtaposed with the FEA approach, the IGA method demonstrated fewer node degrees of freedom and reduced computational units, all while maintaining comparable accuracy. Notably, the IGA method appeared to exhibit consistency in analysis accuracy irrespective of computational unit density, and also significantly mitigated non-physical oscillations in contact stress across the tooth width. This underscores the prowess of IGA in contact analysis. In conclusion, IGA emerges as a potent tool for addressing contact analysis challenges and holds significant promise for 3D gear modeling, simulation, and optimization of various mechanical components.