High volume fraction SiCp/Al composite materials have excellent material properties. Therefore, it is mainly used in aerospace equipment, precision guided weapons, electronic packaging and other fields. However, when machining it with large hardness using traditional methods (TM), tool wear is severe, and processing efficiency is low. At the same time, the thermal softening characteristics of laser assisted machining (LAM) and the variable cutting depth and tool detachment features of two-dimensional (2D) ultrasonic elliptical vibration turning (UEVT) have unique advantages in reducing tool wear. Therefore, a novel technique involving their combination (LUEVT) is suggested. As tool temperature directly impacts on the tool wear, and the characteristics of the two machining processes make changes in cutting temperature more complex. We have developed an analytical model and a finite element model to predict the tool temperature. This model considers the influence of ultrasonic parameters, laser parameters, particle effects, etc. First, the temperature distribution and temperature variation characteristics of the transient tool are analyzed. Subsequently, the temperature values of the models are validated experimentally, and the effects of machining parameters on the average temperature of the tool and the wear width of the tool are analyzed. According to the prediction models, the maximum error is 16.7%, demonstrating good agreement with experimental data. The effective reduction of tool temperature depends on the effective combination of ultrasonic, laser and cutting parameters, etc. Compared with TM, LUEVT can significantly decrease tool wear, but the tool temperature is higher than TM. The developed models are important for the temperature control and tool life study of SiCp/Al composites in UEVT and LAM.

中文翻译：

---

激光超声椭圆振动车削高体积分数 SiCp/Al 复合材料期间刀具温度的估算

高体积分数SiCp/Al复合材料具有优异的材料性能。因此主要应用于航空航天装备、精确制导武器、电子封装等领域。但采用传统方法（TM）加工大硬度时，刀具磨损严重，加工效率低。同时，激光辅助加工（LAM）的热软化特性和二维（2D）超声椭圆振动车削（UEVT）的可变切削深度和刀具脱离特征在减少刀具磨损方面具有独特的优势。因此，提出了一种涉及它们组合的新技术（LUEVT）。由于刀具温度直接影响刀具磨损，而两种加工工艺的特点使得切削温度的变化更加复杂。我们开发了一个分析模型和一个有限元模型来预测工具温度。该模型考虑了超声参数、激光参数、粒子效应等的影响。首先分析了瞬态工具的温度分布和温度变化特征。随后，对模型的温度值进行了实验验证，并分析了加工参数对刀具平均温度和刀具磨损宽度的影响。根据预测模型，最大误差为16.7%，与实验数据吻合良好。刀具温度的有效降低取决于超声波、激光和切削参数等的有效结合。与TM相比，LUEVT可以显着降低刀具磨损，但刀具温度高于TM。所开发的模型对于 UEVT 和 LAM 中 SiCp/Al 复合材料的温度控制和刀具寿命研究具有重要意义。