Abstract
The constitutive model and its material parameters largely determine the effectiveness and accuracy of the finite element (FE) simulation for metal cutting processes. However, even for the same workpiece material, there are multiple constitutive models with different predictive abilities that are applicable to the cutting simulation. Therefore, a method for evaluating the constitutive models based on the coupled Eulerian-Lagrangian (CEL) orthogonal cutting model incorporating the experimentally determined Coulomb friction coefficient is proposed. The evaluation method can effectively avoid the influences of chip separation criteria, damage models, and adaptive remeshing on the evaluation results with the ability to simulate material side flow. This paper evaluates Johnson-Cook (JC) and Zerilli-Armstrong (ZA) constitutive models, which are often applied in cutting simulations. Material parameters for these constitutive models are identified from the constitutive data of the primary or secondary shear zone in cutting tests. A series of FE simulations for orthogonal cutting of 42CrMo4 steel is carried out under various cutting conditions using different constitutive models. The simulated cutting forces, chip thickness, and average temperature over the tool-chip interface are compared with experimental results under the same cutting conditions. The conclusion is that no constitutive model is the most accurate for all predictions. Nevertheless, for 42CrMo4 steel, the ZA model with material parameters identified from constitutive data of the secondary shear zone has the best comprehensive predictive performance. The evaluation method contributes to selecting the most suitable constitutive model and conducting efficient cutting simulations. Furthermore, several feasible approaches for improving the constitutive models are presented through error analysis.
Similar content being viewed by others
Data availability
The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.
Code availability
Not applicable.
References
Liu H, Xu X, Zhang J, Liu Z, He Y, Zhao W, Liu Z (2022) The state of the art for numerical simulations of the effect of the microstructure and its evolution in the metal-cutting processes. Int J Mach Tools Manuf 177:103890. https://doi.org/10.1016/j.ijmachtools.2022.103890
Zhu B, Xiao YMH, Wan X, Xiong L (2020) Theoretical modeling and experimental verification of chip flow angle catastrophe in double-edged cutting considering non-linear effects. Int J Mech Sci 172:105394105394. https://doi.org/10.1016/j.ijmecsci.2019.105394
Li B, Zhang S, Zhang Q, Li L (2019) Simulated and experimental analysis on serrated chip formation for hard milling process. J Manuf Process 44:337–348. https://doi.org/10.1016/j.jmapro.2019.06.018
Özel T (2006) The influence of friction models on finite element simulations of machining. Int J Mach Tools Manuf 46(5):518–530. https://doi.org/10.1016/j.ijmachtools.2005.07.001
Li A, Pang J, Zhao J, Zang J, Wang F (2017) FEM-simulation of machining induced surface plastic deformation and microstructural texture evolution of Ti-6Al-4V alloy. Int J Mech Sci 123:214–223. https://doi.org/10.1016/j.ijmecsci.2017.02.014
Arrazola PJ, Özel T (2010) Investigations on the effects of friction modeling in finite element simulation of machining. Int J Mech Sci 52(1):31–42. https://doi.org/10.1016/j.ijmecsci.2009.10.001
Ducobu F, Rivière-Lorphèvre E, Filippi E (2016) Application of the coupled Eulerian-Lagrangian (CEL) method to the modeling of orthogonal cutting. Eur J Mech A-Solids 59:58–66. https://doi.org/10.1016/j.euromechsol.2016.03.008
Zhang L (1999) On the separation criteria in the simulation of orthogonal metal cutting using the finite element method. J Mater Process Technol 89:273–278. https://doi.org/10.1016/S0924-0136(99)00023-0
Liu J, Bai Y, Xu C (2014) Evaluation of ductile fracture models in finite element simulation of metal cutting processes. J Manuf Sci Eng 136(1):011010. https://doi.org/10.1115/1.4025625
Atlati S, Moufki A, Nouari M, Haddag B (2017) Interaction between the local tribological conditions at the tool–chip interface and the thermomechanical process in the primary shear zone when dry machining the aluminum alloy AA2024–T351. Tribol Int 105:326–333. https://doi.org/10.1016/j.triboint.2016.10.006
Haglund AJ, Kishawy HA, Rogers RJ (2008) An exploration of friction models for the chip–tool interface using an arbitrary Lagrangian-Eulerian finite element model. Wear 265(3–4):452–460. https://doi.org/10.1016/j.wear.2007.11.025
Bil H, Kılıç SE, Tekkaya AE (2004) A comparison of orthogonal cutting data from experiments with three different finite element models. Int J Mach Tools Manuf 44(9):933–944. https://doi.org/10.1016/j.ijmachtools.2004.01.016
Vaz M, Owen DRJ, Kalhori V, Lundblad M, Lindgren LE (2007) Modelling and simulation of machining processes. Arch Comput Method Eng 14(2):173–204. https://doi.org/10.1007/s11831-007-9005-7
Mabrouki T, Courbon C, Zhang Y, Rech J, Nélias D, Asad M, Hamdi H, Belhadi S, Salvatore F (2016) Some insights on the modelling of chip formation and its morphology during metal cutting operations. C R Mec 344(4–5):335–354. https://doi.org/10.1016/j.crme.2016.02.003
Zhu B, Xiong L, Xu M (2022) Double-edged cutting simulation with a new combined constitutive model for AISI 1045 steel. J Mater Process Technol 302:117496117496. https://doi.org/10.1016/j.jmatprotec.2022.117496
Kushner V, Storchak M (2017) Modelling the material resistance to cutting. Int J Mech Sci 126:44–54. https://doi.org/10.1016/j.ijmecsci.2017.03.024
Melkote SN, Grzesik W, Outeiro J, Rech J, Schulze V, Attia H, Arrazola P-J, M’Saoubi R, Saldana C (2017) Advances in material and friction data for modelling of metal machining. CIRP Ann 66(2):731–754. https://doi.org/10.1016/j.cirp.2017.05.002
Liu R, Melkote S, Pucha R, Morehouse J, Man X, Marusich T (2013) An enhanced constitutive material model for machining of Ti–6Al–4V alloy. J Mater Process Technol 213(12):2238–2246. https://doi.org/10.1016/j.jmatprotec.2013.06.015
Gurusamy M, Palaniappan K, Murthy H, Rao BC (2021) A finite element study of large strain extrusion machining using modified Zerilli-Armstrong constitutive relation. J Manuf Sci Eng 143(10):101004. https://doi.org/10.1115/1.4050652
Seif CY, Hage IS, Hamade RF (2020) Incorporating dual BCC/FCC Zerilli-Armstrong and blue brittleness constitutive material models into Oxley’s machining shear zone theory. J Manuf Process 50:663–675. https://doi.org/10.1016/j.jmapro.2019.09.036
Cheng C, Mahnken R (2021) A modified Zerilli-Armstrong model as the asymmetric visco-plastic part of a multi-mechanism model for cutting simulations. Arch Appl Mech 91(9):3869–3888. https://doi.org/10.1007/s00419-021-01982-6
Yaich M, Ayed Y, Bouaziz Z, Germain G (2016) Numerical analysis of constitutive coefficients effects on FE simulation of the 2D orthogonal cutting process: application to the Ti6Al4V. Int J Adv Manuf Technol 93(1–4):283–303. https://doi.org/10.1007/s00170-016-8934-4
Laakso SVA, Niemi E (2017) Using FEM simulations of cutting for evaluating the performance of different johnson cook parameter sets acquired with inverse methods. Robot Comput-Integr Manuf 47:95–101. https://doi.org/10.1016/j.rcim.2016.10.006
Ebrahimi SM, Araee A, Hadad M (2019) Investigation of the effects of constitutive law on numerical analysis of turning processes to predict the chip morphology, tool temperature, and cutting force. Int J Adv Manuf Technol 105(10):4245–4264. https://doi.org/10.1007/s00170-019-04502-7
Shi J, Liu CR (2004) The influence of material models on finite element simulation of machining. J Manuf Sci Eng 126(4):849–857. https://doi.org/10.1115/1.1813473
Xie Z, Xu D, Cui Z, Li M (2019) Evaluation of a cutting simulation using a cupronickel B10 constitutive model considering the deformation temperature. J Mech Sci Technol 33(3):1349–1356. https://doi.org/10.1007/s12206-019-0235-z
Ducobu F, Rivière-Lorphèvre E, Filippi E (2016) Material constitutive model and chip separation criterion influence on the modeling of Ti6Al4V machining with experimental validation in strictly orthogonal cutting condition. Int J Mech Sci 107:136–149. https://doi.org/10.1016/j.ijmecsci.2016.01.008
Gurusamy MM, Rao BC (2017) On the performance of modified Zerilli-Armstrong constitutive model in simulating the metal-cutting process. J Manuf Process 28:253–265. https://doi.org/10.1016/j.jmapro.2017.06.011
Gurusamy M, Rao BC (2021) A modified Zerilli-Armstrong constitutive model for simulating severe plastic deformation of a steel alloy. Proc Inst Mech Eng Part B 236(8):1022–1036. https://doi.org/10.1177/09544054211060914
Li J, Huang Z, Liu G, An Q, Chen M (2021) An experimental and finite element investigation of chip separation criteria in metal cutting process. Int J Adv Manuf Technol 116(11):3877–3889. https://doi.org/10.1007/s00170-021-07461-0
Wright PK, Robinson JL (2013) Material behaviour in deformation zones of machining operation. Met Technol 4(1):240–248. https://doi.org/10.1179/030716977803292042
Pujana J, Arrazola PJ, M’Saoubi R, Chandrasekaran H (2007) Analysis of the inverse identification of constitutive equations applied in orthogonal cutting process. Int J Mach Tools Manuf 47(14):2153–2161. https://doi.org/10.1016/j.ijmachtools.2007.04.012
M’Saoubi R, Chandrasekaran H (2004) Investigation of the effects of tool micro-geometry and coating on tool temperature during orthogonal turning of quenched and tempered steel. Int J Mach Tools Manuf 44(2–3):213–224. https://doi.org/10.1016/j.ijmachtools.2003.10.006
Agmell M, Johansson D, Laakso SVA, Ahadi A, Ståhl J-E (2017) The influence the uncut chip thickness has on the stagnation point in orthogonal cutting. Proced CIRP 58:13–18. https://doi.org/10.1016/j.procir.2017.03.183
Kong J, Zhang T, Du D, Wang F, Jiang F, Huang W (2021) The development of FEM based model of orthogonal cutting for pure iron. J Manuf Process 64:674–683. https://doi.org/10.1016/j.jmapro.2021.01.044
Lu M (2018) A numerical platform for the identification of dynamical non-linear constitutive laws using multiple impact test: application to metal forming and machining in Université de Toulouse
Zha X, Jiang F, Xu X (2017) Investigation of modelling and stress distribution of a coating/substrate system after an indentation test. Int J Mech Sci 134:1–141. https://doi.org/10.1016/j.ijmecsci.2017.10.002
Johnson GR, Cook WH (1983) A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. In: The 7th International Symposium on Ballistics, pp 541–547
Zerilli FJ, Armstrong RW (1987) Dislocation-mechanics-based constitutive relations for material dynamics calculations. J Appl Phys 61(5):1816–1825. https://doi.org/10.1063/1.338024
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 42:1373–1383. https://doi.org/10.1016/S0890-6955(02)00046-9
Guo YB (2003) An integral method to determine the mechanical behavior of materials in metal cutting. J Mater Process Technol 142(1):72–81. https://doi.org/10.1016/s0924-0136(03)00462-x
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. https://doi.org/10.1016/j.jmatprotec.2014.02.004
Yaich M, Gavrus A (2020) New phenomenological material constitutive models for the description of the Ti6Al4V titanium alloy behavior under static and dynamic loadings. In: 23rd International Conference on Material Forming, vol 47, pp 1496–1503. https://doi.org/10.1016/j.promfg.2020.04.336
Xu X, Outeiro J, Zhang J, Xu B, Zhao W, Astakhov V (2021) Machining simulation of Ti6Al4V using coupled Eulerian-Lagrangian approach and a constitutive model considering the state of stress. Simul Model Pract Theory 110:102312. https://doi.org/10.1016/j.simpat.2021.102312
Ambrosio D, Tongne A, Wagner V, Dessein G, Cahuc O (2022) A new damage evolution criterion for the coupled Eulerian-Lagrangian approach: application to three-dimensional numerical simulation of segmented chip formation mechanisms in orthogonal cutting. J Manuf Process 73:149–163. https://doi.org/10.1016/j.jmapro.2021.10.062
Zerilli FJ (2004) Dislocation mechanics-based constitutive equations. Metall Mater Trans A 35(9):2547–2555. https://doi.org/10.1007/s11661-004-0201-x
Shaw C (2005) M, Metal Cutting Principles. Oxford University Press, New York
Weng J, Saelzer J, Berger S, Zhuang K, Bagherzadeh A, Budak E, Biermann D (2023) Analytical and experimental investigations of rake face temperature considering temperature-dependent thermal properties. J Mater Process Technol 314:117905117905. https://doi.org/10.1016/j.jmatprotec.2023.117905
Wang B, Liu Z, Song Q, Wan Y, Ren X (2019) A modified Johnson-Cook constitutive model and its application to high speed machining of 7050–T7451 aluminum alloy. J Manuf Sci Eng 141(1):011012. https://doi.org/10.1115/1.4041915
Calamaz M, Coupard D, Girot F (2010) Numerical simulation of titanium alloy dry machining with a strain softening constitutive law. Mach Sci Technol 14(2):244–257. https://doi.org/10.1080/10910344.2010.500957
Rinaldi S, Umbrello D, Melkote SN (2021) Modelling the effects of twinning and dislocation induced strengthening in orthogonal micro and macro cutting of commercially pure titanium. Int J Mech Sci 190:106045. https://doi.org/10.1016/j.ijmecsci.2020.106045
Rotella G, Del Prete A (2022) Development of customized physics-based predictive models for improved performance in turning of Ti6Al4V. J Manuf Process 81:727–737. https://doi.org/10.1016/j.jmapro.2022.07.013
Acknowledgements
The authors are grateful to J. Pujana and his collaborators for their works on orthogonal cutting experiments and material parameter identification.
Funding
This research was supported by the National Natural Science Foundation of China (No. 52375432).
Author information
Authors and Affiliations
Contributions
Baoyi Zhu: methodology, investigation, software, formal analysis, validation, visualization, writing—original draft.
Liangshan Xiong: conceptualization, resources, supervision, project administration, writing—review and editing.
Yuhai Chen: investigation, writing—review and editing.
Corresponding author
Ethics declarations
Ethics approval
The authors obliged all the rules regarding the ethic in publication.
Consent to participate
All authors were fully involved in the study and preparation of the manuscript; each of the authors has read and concurred with the content in the final manuscript.
Consent for publication
All authors consent to publish the content in the final manuscript.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhu, B., Xiong, L. & Chen, Y. Evaluation of constitutive models used in orthogonal cutting simulation based on coupled Eulerian–Lagrangian formulation. Int J Adv Manuf Technol 131, 183–199 (2024). https://doi.org/10.1007/s00170-024-13104-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-024-13104-x