Advances in Manufacturing ›› 2019, Vol. 7 ›› Issue (4): 364-373.doi: 10.1007/s40436-019-00276-z
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Xiao-Guang Guo, Ming Li, Zhi-Gang Dong, Rui-Feng Zhai, Zhu-Ji Jin, Ren-Ke Kang
Received:2019-03-30
Revised:2019-07-01
Online:2019-12-25
Published:2019-12-26
Contact:
Ming Li, Zhi-Gang Dong
E-mail:lmzdg@mail.dlut.edu.cn;dongzg@dlut.edu.cn
Supported by:Xiao-Guang Guo, Ming Li, Zhi-Gang Dong, Rui-Feng Zhai, Zhu-Ji Jin, Ren-Ke Kang. Smooth particle hydrodynamics modeling of cutting force in milling process of TC4[J]. Advances in Manufacturing, 2019, 7(4): 364-373.
| 1. Gangwar K, Ramulu M (2018) Friction stir welding of titanium alloys:a review. Mater Des 141:230-255 2. Ma AM, Liu DX, Tang CB et al (2018) Influence of glow plasma Co-based alloying layer on sliding wear and fretting wear resistance of titanium alloy. Tribol Int 125:85-94 3. Conradie P, Dimitrov D, Oosthuizen G (2016) A cost modelling approach for milling titanium alloys. Procedia CIRP 46:412-415 4. Yang P, Yao CF, Xie SH et al (2016) Effect of tool orientation on surface integrity during ball end milling of titanium alloy TC17. Procedia CIRP 56:143-148 5. Chen Y, Li H, Wang J (2018) Predictive modelling of cutting forces in end milling of titanium alloy Ti6Al4V. Proc Inst Mech Eng B:J Eng Manuf 232(9):1523-1534 6. Chen Y, Li H, Wang J (2015) Analytical modelling of cutting forces in near-orthogonal cutting of titanium alloy Ti6Al4V. Proc Inst Mech Eng C:J Mech Eng Sci 229(6):1122-1133 7. Wu HB, Zhang SJ (2014) 3D FEM simulation of milling process for titanium alloy Ti6Al4V. Int J Adv Manuf Technol 71(5-8):1319-1326 8. Thepsonthi T, Özel T (2015) 3-D finite element process simulation of micro-end milling Ti-6Al-4V titanium alloy:experimental validations on chip flow and tool wear. J Mater Process Tech 221:128-145 9. Ji CH, Li YH, Qin XD et al (2015) 3D FEM simulation of helical milling hole process for titanium alloy Ti-6Al-4V. Int J Adv Manuf Technol 81(9-12):1733-1742 10. Sui XL, Zhang SG, Guan Y et al (2016) 3-D finite element simulation analysis of milling titanium alloy using different cutting edge radius. In:Sixth international conference on intelligent systems design & engineering applications. IEEE, 2016 11. Wu HB, Zhang SJ (2015) Effects of cutting conditions on the milling process of titanium alloy Ti6Al4V. Int J Adv Manuf Technol 77(9/12):2235-2240 12. Özel T, Olleak A, Thepsonthi T (2017) Micro milling of titanium alloy Ti-6Al-4V:3-D finite element modeling for prediction of chip flow and burr formation. Prod Eng 11(4/5):435-444 13. Yang Y, Zhu WW (2014) Study on cutting temperature during milling of titanium alloy based on FEM and experiment. Int J Adv Manuf Technol 73(9/12):1511-1521 14. Mamedov A, Lazoglu I (2016) Thermal analysis of micro milling titanium alloy Ti-6Al-4V. J Mater Process Technol 229:659-667 15. Pang MH, Wang ZK, Jiao HW (2008) The contrastand analysis of SPH method and FEM method. Mach Des Manuf 2:36-38 16. Olleak AA, El-Hofy HA (2015) Prediction of cutting forces in high speed machining of Ti6Al4V using SPH method.In:ASME 2015 international manufacturing science and engineering conference, 2015 17. Xi Y, Bermingham M, Wang G et al (2014) SPH/FE modeling of cutting force and chip formation during thermally assisted machining of Ti6Al4V alloy. Comput Mater Sci 84(1):188-197 18. Demiral M (2014) Smoothed particle hydrodynamics modeling of vibro-assisted turning of Ti alloy:influence of vibration parameters. J Vibro Eng 16(6):2685-2694 19. Gasiorek D, Baranowski P, Malachowski J et al (2018) Modelling of guillotine cutting of multi-layered aluminum sheets. J Manuf Process 34:374-388 20. Wang Y, Wang S, Liu JG et al (2015) Dynamic simulation of single abrasive grain cutting TC4 based on SPH method. J Syst Simul 27(11):2865-2872 21. Xi Y, Zhan HY, Rahman Rashid RA et al (2014) Numerical modeling of laser assisted machining of a beta titanium alloy. Comput Mater Sci 92:149-156 22. Gingold RA, Monaghan JJ (1977) Smoothed particle hydrodynamics:theory and application to non-spherical stars. Mon Not R Astron Soc 181(3):375-389 23. He A, Xie GL, Zhang HL et al (2014) A modified Zerilli-Armstrong constitutive model to predict hot deformation behavior of 20CrMo alloy steel. Mater Des 56(4):122-127 24. Prawoto Y, Fanone M, Shahedi S et al (2012) Computational approach using Johnson-Cook model on dual phase steel. Comput Mater Sci 54(1):48-55 25. Liu XJ (2008) Analysis and experimental study on cutting force model of thin-walled parts machining. Dissertation, Nanjing University of Aeronautics and Astronautics |
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