材料工程与机械制造

直角切削6061-T6铝合金剪切区力学行为及微观结构演化预测

  • 周滔 ,
  • 何林 ,
  • 田鹏飞 ,
  • 杜飞龙 ,
  • 吴锦行
展开
  • 1. 贵州大学 机械工程学院, 贵阳 550025;
    2. 六盘水师范学院 矿业与土木工程学院, 六盘水 553000;
    3. 贵州大学 现代制造技术教育部重点实验室, 贵阳 550025

收稿日期: 2020-03-14

  修回日期: 2020-04-10

  网络出版日期: 2020-07-10

基金资助

国家自然科学基金(51765009,51665007);贵州省研究生科研基金(YJSCXJH(2019)013)

Prediction of mechanical behavior and microstructure evolution of shear zone in orthogonal cutting 6061-T6 aluminum alloy

  • ZHOU Tao ,
  • HE Lin ,
  • TIAN Pengfei ,
  • DU Feilong ,
  • WU Jinxing
Expand
  • 1. College of Mechanical Engineering, Guizhou University, Guiyang 550025, China;
    2. School of Mining and Civil Engineering, Liupanshui Normal College, Liupanshui 553000, China;
    3. Key Laboratory of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, China

Received date: 2020-03-14

  Revised date: 2020-04-10

  Online published: 2020-07-10

Supported by

National Natural Science Foundation of China (51765009, 51665007); Graduate Research Foundation of Guizhou Province (YJSCXJH(2019)013)

摘要

力学行为是塑性变形微观过程的宏观表现,早期的金属切削理论模型没有考虑微观结构对切削力的影响。在考虑热力耦合效应的基础上建立了基于位错密度材料模型的6061-T6铝合金直角切削力预测模型,分析了不同切削参数下基于位错运动的塑性变形机制对切削力的影响。结合等分剪切区和非等分剪切区模型,构建了第一变形区多物理场计算方法,提出一种切屑形成过程中由塑性变形引起的微观结构演化解析模型。通过测量切削力和切屑内晶粒尺寸对模型的可行性进行了初步验证。结果表明:剪切区长度变长引起参与位错滑移的材料增多是切削深度增大导致切削力增大的主要原因。增大切削速度导致切削力的降低不是单一变量影响的结果,而是应变降低引起位错增殖数量减少和温度升高引起位错湮灭作用增加的共同作用结果。非等分剪切区模型正确反映了第一变形区温度和应力的分布特征,且与二维有限元模型分布相一致,建立的第一变形区微观结构演化解析模型能够预测切屑内位错密度和晶粒尺寸。

本文引用格式

周滔 , 何林 , 田鹏飞 , 杜飞龙 , 吴锦行 . 直角切削6061-T6铝合金剪切区力学行为及微观结构演化预测[J]. 航空学报, 2021 , 42(3) : 423975 -423975 . DOI: 10.7527/S1000-6893.2020.23975

Abstract

Mechanical behavior is the macroscopic expression of the microscopic process of plastic deformation. Early metal cutting theoretical models did not consider the effect of microstructure on the cutting force. Based on the dislocation density material model, a 6061-T6 aluminum alloy orthogonal cutting force prediction model is established, and the influence of dislocation motion based plastic deformation mechanism on the cutting force with different cutting parameters is analyzed. By combining the model of equal division shear zones and unequal division shear zones, we construct a multi-physics field calculation method for the first deformation zone, and propose an analytical model of microstructure evolution caused by plastic deformation during chip formation. The feasibility of the model is preliminarily verified by measuring the cutting force and the size of grain in the chip. The results show that the material increase involved in the dislocation slip caused by the length of the shear zone is the main reason for the increase of the feed rate, which further leads to the increase of the cutting force. The decrease in the cutting force caused by the increasing cutting speed is not the result of a single variable, but the joint effect of the number reduction of dislocations induced by the strain reduction and the annihilation increase resulted from temperature increase. The non-divided shear zone model correctly reflects the temperature and stress distribution characteristics of the first deformation zone, and is consistent with the two-dimensional finite element model. The analytical model of the microstructure evolution of the first deformation zone can predict the dislocation density and grain size in the chip.

参考文献

[1] MERCHANT M E. Mechanics of the metal cutting process. I. orthogonal cutting and a type 2 chip[J]. Journal of Applied Physics, 1945, 16(5):267-275.
[2] HILL R. The mechanics of machining:A new approach[J]. Journal of the Mechanics and Physics of Solids, 1954, 3(1):47-53.
[3] LEE E. The theory of plasticity applied to a problem of machining[J]. Journal of Applied Mechanics, 1951, 18:405.
[4] LIU R, SALAHSHOOR M, MELKOTE S N, et al. A unified material model including dislocation drag and its application to simulation of orthogonal cutting of OFHC copper[J]. Journal of Materials Processing Technology, 2015, 216:328-338.
[5] PAN Z P, SHIH D S, TABEI A, et al. Modeling of Ti-6Al-4V machining force considering material microstructure evolution[J]. The International Journal of Advanced Manufacturing Technology, 2017, 91(5-8):2673-2680.
[6] WU H, MA J F, LEI S T. FEM prediction of dislocation density and grain size evolution in high-speed machining of Al6061-T6 alloy using microgrooved cutting tools[J]. The International Journal of Advanced Manufacturing Technology, 2018, 95(9-12):4211-4227.
[7] DING H T, SHEN N G, SHIN Y C. Modeling of grain refinement in aluminum and copper subjected to cutting[J]. Computational Materials Science, 2011, 50(10):3016-3025.
[8] BAMMANN D J, CHIESA M L, JOHNSON G C. Modeling large deformation and failure in manufacturing processes[J]. Theoretical and Applied Mechanics, 1996, 9:359-376.
[9] GUO Y B, WEN Q, WOODBURY K A. Dynamic material behavior modeling using internal state variable plasticity and its application in hard machining simulations[J]. Journal of Manufacturing Science and Engineering, 2006, 128(3):749-759.
[10] FOLLANSBEE P S, KOCKS U F. A constitutive description of the deformation of copper based on the use of the mechanical threshold stress as an internal state variable[J]. Acta Metallurgica, 1988, 36(1):81-93.
[11] DING H T, SHIN Y C. Multi-physics modeling and simulations of surface microstructure alteration in hard turning[J]. Journal of Materials Processing Technology, 2013, 213(6):877-886.
[12] TAO J F, QIN C J, XIAO D Y, et al. A pre-generated matrix-based method for real-time robotic drilling chatter monitoring[J]. Chinese Journal of Aeronautics, 2019, 32(12):2755-2764.
[13] ESTRIN Y, TOTH L S, MOLINARI A, et al. A dislocation-based model for all hardening stages in larges strain deformation[J]. Acta Materialia, 1998, 46(15):5509-5522.
[14] ARISOY Y M, ÖZEL T. Prediction of machining induced microstructure in Ti-6Al-4V alloy using 3-D FE-based simulations:Effects of tool micro-geometry, coating and cutting conditions[J]. Journal of Materials Processing Technology, 2015, 220:1-26.
[15] 杜茂华, 程正, 王神送,等. 损伤演化对Ti6Al4V高速切削仿真结果的影响[J]. 航空学报, 2019, 40(7):422787. DU M H, CHENG Z, WANG S S, et al. Effects of damage evolution on simulation results of hign speed maching TiAl4V[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(7):422787(in Chinese).
[16] JAFARIAN F, MASOUDI S, UMBRELLO D, et al. New strategies for improvement of numerical model accuracy in machining of nickel-based alloy[J]. Simulation Modelling Practice and Theory, 2019, 94:134-148.
[17] KOCKS U F. Laws for work-hardening and low-temperature creep[J]. Journal of Engineering Materials and Technology, 1976, 98(1):76-85.
[18] OXLEY P L B, SHAW M C. Mechanics of machining:an analytical approach to assessing machinability[M]. London:Ellis Horwood Limited, 1990.
[19] WANG Z G. High-speed milling of titanium alloys:Modeling and optimization[D]. Singapore:National University of Singapore, 2005.
[20] ALTINTAS Y, BER A A. Manufacturing automation:metal cutting mechanics, machine tool vibrations, and CNC design[M]. New York:Cambridge University Press, 2001.
[21] PANG L. Analytical modeling and simulation of metal cutting forces for engineering alloys[D]. Oshawa:University of Ontario Institute of Technology, 2012.
[22] WALDORF D J, DEVOR R E, KAPOOR S G. A slip-line field for ploughing during orthogonal cutting[J]. Journal of Manufacturing Science & Engineering, 1998, 120(4):693-699.
[23] SU J C. Residual stress modeling in machining processes[D]. Atlanta:Georgia Institute of Technology, 2006.
[24] ASTAKHOV V P, OSMAN M O M, HAYAJNEH M T. Re-evaluation of the basic mechanics of orthogonal metal cutting:velocity diagram, virtual work equation and upper-bound theorem[J]. International Journal of Machine Tools and Manufacture, 2001, 41(3):393-418.
[25] ZHOU F J, WANG X L, HU Y J, et al. Modeling temperature of non-equidistant primary shear zone in metal cutting[J]. International Journal of Thermal Sciences, 2013, 73:38-45.
[26] ATMANI Z, HADDAG B, NOUARI M, et al. Combined microstructure-based flow stress and grain size evolution models for multi-physics modelling of metal machining[J]. International Journal of Mechanical Sciences, 2016, 118:77-90.
[27] 余勇, 潘晓霞. Frank-Read位错源的细观级模拟[J]. 金属学报, 2009, 45(11):1309-1313. YU Y, PAN X X. Meso-scale simulation of frank-read dislocation sources[J]. Acta Metallurgica Sinica, 2009, 45(11):1309-1313(in Chinese).
[28] 刘具龙, 张璧, 白倩, 等. 钛合金铣削刀具/工件接触区域温度预测[J]. 航空学报, 2018, 39(12):422128. LIU J L, ZHAG B, BAI Q, et al. Temperature prediction of tool/workpiece contact zone in titanium milling[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(12):422128(in Chinese).
[29] SHAN C W, ZHANG X, SHEN B, et al. An improved analytical model of cutting temperature in orthogonal cutting of Ti6Al4V[J]. Chinese Journal of Aeronautics, 2019, 32(3):759-769.
[30] ORRA K, CHOUDHURY S K. Mechanistic modelling for predicting cutting forces in machining considering effect of tool nose radius on chip formation and tool wear land[J]. International Journal of Mechanical Sciences, 2018, 142:255-268.
[31] LI H Z, WANG H J, LIANG X P, et al. Hot deformation and processing map of 2519A aluminum alloy[J]. Materials Science and Engineering:A, 2011, 528(3):1548-1552.
[32] JAVIDIKIA M, SADEGHIFAR M, SONGMENE V, et al. On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6:An experimentally validated numerical study[J]. The International Journal of Advanced Manufacturing Technology, 2020, 106(9):4547-4565.
文章导航

/