Skip to main content
Log in

Predicting the Johnson Cook constitutive model constants using temperature rise distribution in plane strain machining

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Johnson-Cook (JC) constitutive material model is the most common, yet simplest, model to describe the material behavior in machining that involves high strain and high strain rates accompanied with high temperature rise. Many studies have tried to predict JC model constants using computational and analytical procedures. However, these approaches are limited by computational costs and experimental restrictions. In this study, an original approach to determine the JC material model constants is proposed using the effects imposed by strain hardening, strain rate hardening, and thermal softening. An analytical approach is established upon the chip formation model in orthogonal cutting—plane strain machining—where the JC model is applied to calculate cutting energy due to plasticity and friction which ultimately involves temperature rise. Temperature is calculated at primary shear zone and secondary deformation zone using Oxley and modified Hahn’s models, which are dependent on material behavior and five JC constants. JC constants are calculated by performing a multi-objective optimization algorithm that searches for the minimum differences between the calculated temperature in the chip and the experimental results of temperature for different cutting conditions. The obtained JC constants are compared with the literature and close agreements are achieved. The appeal of the proposed methodology is in its low computational time, low experimental complexity, and low mathematical complexity. Finally, JC constants were used in finite element simulation of PSM to verify the model’s robustness and accuracy via comparing the cutting force, temperature distribution, and subgrain size of the chip for different cutting conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Priyadarshini A, Pal SK, Samantaray AK (2010) Influence of the johnson cook material model parameters and friction models on simulation of orthogonal cutting process. Journal of Machining and Forming Technologies 4 (1-2):59–83

    Google Scholar 

  2. Salonitis K, Stavropoulos P, Stournaras A, Chryssolouris G (2007) Finite element modeling of grind hardening process. In: 10th CIRP international workshop on modeling of machining operations (Calabria, Italy), pp 117–123

  3. Rodríguez JM, Jonsén P, Svoboda A (2017) Simulation of metal cutting using the particle finite-element method and a physically based plasticity model. Computational Particle Mechanics 4(1):35–51

    Article  Google Scholar 

  4. Bhadeshia H (2004) 39 - modelling and simulation. Smithells metals reference book (eighth edition), pp 1–11

  5. Zhou Z, Chen D, Xie SS (2007) Springer series in advanced manufacturing

  6. Ducobu F, Arrazola PJ, Rivière-Lorphèvre E, Filippi E (2015) Comparison of several behaviour laws intended to produce a realistic Ti6Al4V chip by finite elements modelling. Key Engineering Materials

  7. Ducobu F, Rivière-Lorphèvre E, Filippi E (2016) Application of the coupled Eulerian-Lagrangian (CEL) method to the modeling of orthogonal cutting. European Journal of Mechanics, A/Solids

    Article  Google Scholar 

  8. Chen G, Ren C, Yang X, Jin X, Guo T (2011) Finite element simulation of high-speed machining of titanium alloy (Ti-6Al-4V) based on ductile failure model. International journal of advanced manufacturing technology

  9. Zhang YC, Mabrouki T, Nelias D, Gong YD (2011) Chip formation in orthogonal cutting considering interface limiting shear stress and damage evolution based on fracture energy approach. Finite elements in analysis and design

  10. Miguélez MH, Soldani X, Molinari A (2013) Analysis of adiabatic shear banding in orthogonal cutting of Ti alloy. International journal of mechanical sciences

  11. Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains high strain rates and high temperatures

  12. Hernandez C, Maranon A, Ashcroft IA, Casas-Rodriguez JP (2013) A computational determination of the Cowper-Symonds parameters from a single Taylor test. Appl Math Model 37(7):4698–4708

    Article  MathSciNet  Google Scholar 

  13. Tounsi N, Vincenti J, Otho A, Elbestawi MA (2002) From the basic mechanics of orthogonal metal cutting toward the identification of the constitutive equation. Int J Mach Tools Manuf 42(12):1373–1383

    Article  Google Scholar 

  14. Shrot A, Bäker M (2012) Determination of Johnson–Cook parameters from machining simulations. Comput Mater Sci 52(1):298–304

    Article  Google Scholar 

  15. Ning J (2018) Inverse determination of Johnson-Cook model constants of ultra-fine-grained titanium based on chip formation model and iterative gradient search

  16. Karkalos NE, Markopoulos AP (2018) Determination of Johnson-Cook material model parameters by an optimization approach using the fireworks algorithm. Procedia Manufacturing 22:107–113

    Article  Google Scholar 

  17. Shrot A, Bäker M (2011) How to identify johnson-cook parameters from machining simulations. AIP Conf Proc 1353(1):29–34

    Article  Google Scholar 

  18. Ducobu F, Rivière-Lorphèvre E, Filippi E (2017) On the importance of the choice of the parameters of the Johnson-Cook constitutive model and their influence on the results of a Ti6Al4V orthogonal cutting model. Int J Mech Sci 122(September 2016):143–155

    Article  Google Scholar 

  19. Umbrello D, M’Saoubi R, Outeiro JC (2007) The influence of Johnson-Cook material constants on finite element simulation of machining of AISI 316L steel. Int J Mach Tools Manuf 47(3-4):462–470

    Article  Google Scholar 

  20. Ning J, Liang S (2018) Prediction of temperature distribution in orthogonal machining based on the mechanics of the cutting process using a constitutive model. Journal of Manufacturing and Materials Processing 2(2):37

    Article  Google Scholar 

  21. Khan AS, Suh YS, Kazmi R (2004) Quasi-static and dynamic loading responses and constitutive modeling of titanium alloys. International journal of plasticity

  22. Milani AS, Dabboussi W, Nemes JA, Abeyaratne RC (2009) An improved multi-objective identification of Johnson-Cook material parameters. International journal of impact engineering

  23. Majzoobi GH, Freshteh-Saniee F, Faraj Zadeh Khosroshahi S, Beik Mohammadloo H (2010) Determination of materials parameters under dynamic loading. Part I: experiments and simulations. Computational materials science

  24. Lei S, Shin YC, Incropera FP (2008) Material constitutive modeling under high strain rates and temperatures through orthogonal machining tests. Journal of manufacturing science and engineering

  25. Dorogoy A, Rittel D (2009) Determination of the Johnson-Cook material parameters using the SCS specimen. Experimental mechanics

  26. Klocke F, Lung D, Buchkremer S (2013) Inverse identification of the constitutive equation of inconel 718 and AISI 1045 from FE machining simulations. In: Procedia CIRP

  27. Oxley P (1961) Mechanics of metal cutting. International Journal of Machine Tool Design and Research 1 (1-2):89–97

    Article  Google Scholar 

  28. Naik P, Naik A (2015) Determination of flow stress constants by Oxley’s theory. Ijltemas IV(X):110–116

    Google Scholar 

  29. Ozel T, Zeren E (2006) A methodology to determine work material flow stress and tool-chip interfacial friction properties by using analysis of machining. J Manuf Sci Eng 128(1):119

    Article  Google Scholar 

  30. Ning J (2018) Model-driven determination of Johnson-Cook material constants using temperature and force measurements. Int J Adv Manuf Technol, pp 1053–1060

    Article  Google Scholar 

  31. Lalwani DI, Mehta NK, Jain PK (2009) Extension of Oxley’s predictive machining theory for Johnson and Cook flow stress model. J Mater Process Technol 209(12-13):5305–5312

    Article  Google Scholar 

  32. Komanduri R, Hou ZB (2000) Thermal modeling of the metal cutting process Part I - temperature rise distribution due to shear plane heat source. Int J Mech Sci

  33. Komanduri R, Hou ZB (2001) Thermal modeling of the metal cutting process - Part III: Temperature rise distribution due to the combined effects of shear plane heat source and the toolchip interface frictional heat source. Int J Mech Sci

  34. Komanduri R, Hou ZB (2001) Thermal modeling of the metal cutting process - Part II: Temperature rise distribution due to frictional heat source at the tool-chip interface. Int J Mech Sci

  35. Abolghasem S, Basu S, Shekhar S, Cai J, Shankar MR (2012) Mapping subgrain sizes resulting from severe simple shear deformation. Acta Mater 60(1):376–386

    Article  Google Scholar 

  36. Basu S, Abolghasem S, Shankar MR (2013) Mechanics of intermittent plasticity punctuated by fracture during shear deformation of Mg alloys at near-ambient temperatures. Metall Mater Trans A 44(10):4558–4566

    Article  Google Scholar 

  37. Shaw MC (2005) Second Edition

  38. Zhang D, Zhang XM, Ding H (2016) A study on the orthogonal cutting mechanism based on experimental determined displacement and temperature fields. Procedia CIRP 46:35–38

    Article  Google Scholar 

  39. Karas A, Bouzit M, Belarbi M (2013) Development of a thermal model in the metal cutting process for prediction of temperature distributions at the Tool-Chip-Workpiece interface. J Theor Appl Mech 51(3):553–567

    Google Scholar 

  40. Madhavan V, Adibi-Sedeh AH (2005) Understanding of finite element analysis results under the framework of Oxley’s machining model. Mach Sci Technol 9(3):345–368

    Article  Google Scholar 

  41. Toropov A, Ko SL (2003) Prediction of tool-chip contact length using a new slip-line solution for orthogonal cutting. Int J Mach Tools Manuf 43(12):1209–1215

    Article  Google Scholar 

  42. Praça A (2014) Predictive analytical and numerical modeling for orthogonal cutting

  43. Kapoor SG (2016) A slip-line field for ploughing during orthogonal cutting 120(November 1998):693–699

  44. Kennedy FE (2001) Frictional heating and contact temperatures. Modern tribology handbook, pp 235–272

  45. Denguir LA, Outeiro JC, Rech J, Fromentin G, Vignal V, Besnard R (2017) Friction model for tool/work material contact applied to surface integrity prediction in orthogonal cutting simulation. Procedia CIRP 58:578–583

    Article  Google Scholar 

  46. Sasso M, Newaz G, Amodio D (2008) Material characterization at high strain rate by Hopkinson bar tests and finite element optimization. Materials Science and Engineering A

  47. Huh H, Ahn K, Lim JH, Kim HW, Park LJ (2014) Evaluation of dynamic hardening models for BCC , FCC, and HCP metals at a wide range of strain rates. J Mater Process Technol 214(7):1326–1340

    Article  Google Scholar 

  48. Outeiro JC, Campocasso S, Denguir LA, Fromentin G, Vignal V, Poulachon G (2015) Experimental and numerical assessment of subsurface plastic deformation induced by OFHC copper machining. CIRP Ann Manuf Technol 64(1):53–56

    Article  Google Scholar 

  49. Denguir LA, Outeiro JC, Fromentin G, Vignal V, Besnard R (2016) Orthogonal cutting simulation of OFHC copper using a new constitutive model considering the state of stress and the microstructure effects. Procedia CIRP 46:238–241

    Article  Google Scholar 

  50. Input P (2008) Marc 2008r1 volume c: program input, vol C

  51. Sadeghifar M, Sedaghati R, Jomaa W, Songmene V (2018) A comprehensive review of finite element modeling of orthogonal machining process: chip formation and surface integrity predictions. Int J Adv Manuf Technol 96(9-12):3747–3791

    Article  Google Scholar 

  52. Jomaa W, Mechri O, Lévesque J., Songmene V, Bocher P, Gakwaya A (2017) Finite element simulation and analysis of serrated chip formation during high–speed machining of AA7075–t651 alloy. J Manuf Process 26:446–458

    Article  Google Scholar 

  53. Ambati R, Yuan H (2011) FEM Mesh-dependence in cutting process simulations, pp 313–323

    Article  Google Scholar 

  54. Liu JF, Long Y, Ji C, Xu D, Xiang D, Song G (2017) Dynamic response and microstructure evolution of oxygen-free high-conductivity copper liner in explosively formed projectile. Latin American journal of solids and structures

  55. Adams R, Advani S, Alman DE (2001) ASM Handbook

  56. Marc MSC (2001) Volume D: user subroutines and special routines, vol D, pp 338

  57. Sakai T, Jonas JJ (1984) Overview no. 35 Dynamic recrystallization: mechanical and microstructural considerations. Acta Metallurgica

  58. Abolghasem S, Basu S, Shankar MR (2013) Quantifying the progression of dynamic recrystallization in severe shear deformation at high strain rates. J Mater Res 28(15):2056–2069

    Article  Google Scholar 

  59. Guo Y, Saldana C, Dale Compton W, Chandrasekar S (2011) Controlling deformation and microstructure on machined surfaces. Acta Materialia

Download references

Acknowledgements

The authors would like to thank Shashank Shekhar, Saurabh Basu, and Alejandro Marañon for the insightful advices and discussions on the development of this work.

Funding

In this study, we acknowledge the funding support from Colciencias grant code 120474557650 and the 2019 grant from Faculty of Engineering at Universidad de los Andes, Bogotá, Colombia.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sepideh Abolghasem.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Osorio-Pinzon, J.C., Abolghasem, S. & Casas-Rodriguez, J.P. Predicting the Johnson Cook constitutive model constants using temperature rise distribution in plane strain machining. Int J Adv Manuf Technol 105, 279–294 (2019). https://doi.org/10.1007/s00170-019-04225-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-019-04225-9

Keywords

Navigation