Analytical model for thermo-mechanical interaction induced residual stress distribution during multi-conditional machining Inconel 718

被引:0
|
作者
Liang, Xiaoliang [1 ,2 ,3 ]
Liu, Zhanqiang [1 ,2 ]
Ren, Lifei [3 ]
Wang, Bing [1 ,2 ]
Wang, Chunjin [1 ,3 ]
Yao, Gonghou [1 ,2 ]
Cheung, Chi Fai [1 ,3 ]
机构
[1] Shandong Univ, Sch Mech Engn, Key Lab High Efficiency & Clean Mech Manufacture, MOE, Jinan 250061, Peoples R China
[2] Shandong Univ, Key Natl Demonstrat Ctr Expt Mech Engn Educ, Jinan 250061, Peoples R China
[3] Hong Kong Polytech Univ, Dept Ind & Syst Engn, State Key Lab Ultraprecis Machining Technol, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Cutting process; Thermo-mechanical field; Tool wear; Residual stress; Inconel; 718; ENHANCED ANALYTICAL-MODEL; INVERSE ANALYSIS; TOOL WEAR; PREDICTION; TEMPERATURE; RADIUS;
D O I
10.1016/j.ymssp.2023.110835
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Residual stress induced by coupling thermo-mechanical fields cannot be completely released and remains inside the workpiece after the cutting process, which has a significant impact on the fatigue resistance, corrosion resistance and deflection of manufacturing parts. This work focused on an analytical model for thermo-mechanical fields induced residual stress distribution during multi-conditional machining superalloy Inconel 718. Based on the relationships of material properties, cutting parameters, and cutting geometric conditions, the proposed analytical model investigated the thermo-mechanical fields based on the semi-infinite space elastic mechanical line load and the uneven film thermal stress distribution under the action of moving heat sources. The development process of residual stress was examined through the changes in the stress release process from loading to unloading based on the in-plane stress assumption solution. The effects of basic cutting variables including cutting speeds, uncut chip thickness and tool wear on the thermo-mechanical fields were discussed. According to the experimental and predicted results, the residual stress distribution characteristics were evaluated including surface residual stress, reverse peak stresses, transition position, and total influence depth, indicating that the proposed analytical model could obtain the residual stress distribution characteristics with the predicted error of approximately 4.3%-11.9%, 3.9%-73.4%, 4%-33.3%, and 3.3%-25.7%, respectively. This work can provide significant theoretical support for the analysis of the residual stress generation to control surface integrity during the cutting process.
引用
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页数:23
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