journal article·2025-01

A Modified Johnson–Cook Model for Modeling AA6061-T6 under Different Temperatures Considering Ductile Fracture

Hangyu Wu, Haiyan Yu

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Abstract

An accurate constitutive model is a prerequisite for formability simulation analysis. In the study, the mechanical properties of AA6061-T6 at 20-450 °C conditions was investigated. The original Johnson–Cook (J–C) model was not suitable for predicting the flow behavior over the wide range of temperature. A modified segmented J–C model was proposed and aimed to accurately reflect the trend of flow stress–strain at various temperature. To improve the prediction accuracy of the constitutive model, the model parameters were calibrated using a genetic algorithm. The damage values of Ayada criterion were calculated at different temperatures and fitted with an exponential function. Subsequently, the segmented J–C model and modified Ayada criterion were written in the VUMAT subroutine to simulate the quasi-static uniaxial tension of AA6061-T6 at elevated temperature. The results indicated that there was a significant difference in the flow behavior of AA6061-T6 below 300 and above 300 °C. The modified segmented J–C model could better predict the flow stress of AA6061-T6 at various temperatures and the genetic algorithm could effectively improve the fitting accuracy compared to the traditional fitting method. The simulation results showed that the modified Ayada criterion could predict the AA6061-T6 ductile fracture at elevated temperature. It further proved that the accuracy of the segmented J–C model and modified Ayada criterion.
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Research context

OpenAlex topics: Metal Forming Simulation Techniques · Metallurgy and Material Forming · High-Velocity Impact and Material Behavior

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References (41)

Show source-provided references
1. W. Zhang and J. Xu, Advanced Lightweight Materials for Automobiles: A Review, Mater. Design, 2022, 221, p 110994. https://doi.org/10.1016/j.matdes.2022.11099410.1016/j.matdes.2022.110994 ↗
2. F. Czerwinski, Current Trends in Automotive Lightweighting Strategies and Materials, Materials (Basel), 2021, 14(21), p 6631–6657. https://doi.org/10.3390/ma1421663110.3390/ma14216631 ↗
3. Y. Choi, J. Lee, S.S. Panicker, H.-K. Jin, S.K. Panda, and M.-G. Lee, Mechanical Properties, Springback, and Formability of W-Temper and Peak Aged 7075 Aluminum Alloy Sheets: Experiments and Modeling, Int. J. Mech. Sci., 2020, 170, p 105344. https://doi.org/10.1016/j.ijmecsci.2019.10534410.1016/j.ijmecsci.2019.105344 ↗
4. D. Raja Satish and D. Ravi Kumar, Formability of AA6061 Alloy Sheets in Warm Forming Temperature Range, Proc. Inst. Mech. Eng. Part L: J. Mater. Design Appl., 2019 https://doi.org/10.1177/146442071982950710.1177/1464420719829507 ↗
5. A. Rudnytskyj, P. Simon, M. Jech, and C. Gachot, Constitutive Modelling of the 6061 Aluminium Alloy under Hot Rolling Conditions and Large Strain Ranges, Mater. Design, 2020, 190, p 108568. https://doi.org/10.1016/j.matdes.2020.10856810.1016/j.matdes.2020.108568 ↗
6. Q. Guo, W. Yao, W. Li, and N. Gupta, Constitutive Models for the Structural Analysis of Composite Materials for the Finite Element Analysis: A Review of Recent Practices, Compos. Struct., 2021, 260, p 113267. https://doi.org/10.1016/j.compstruct.2020.113267,10.1016/jcompstruct2020113267 ↗
7. R. Motallebi, Z. Savaedi, and H. Mirzadeh, Additive Manufacturing – A Review of Hot Deformation Behavior and Constitutive Modeling of Flow Stress, Curr. Opin. in Solid State Mater. Sci., 2022, 26(3), p 100992. https://doi.org/10.1016/j.cossms.2022.10099210.1016/j.cossms.2022.100992 ↗
8. N. Nguyen and A. Hosseini, Direct Calculation of Johnson–Cook Constitutive Material Parameters for Oblique Cutting Operations, J. Manuf. Process., 2023, 92, p 226–237. https://doi.org/10.1016/j.jmapro.2023.02.03210.1016/j.jmapro.2023.02.032 ↗
9. H.R. Rezaei Ashtiani and P. Shahsavari, Constitutive Modeling of flow Behavior of Precipitation-Hardened AA7022-T6 Aluminum Alloy at Elevated Temperature, Trans. Nonferrous Metals Soc. China, 2020, 30(11), p 2927–2940. https://doi.org/10.1016/s1003-6326(20)65432-210.1016/s1003-6326(20)65432-2 ↗
10. P. Geng, G. Qin, J. Zhou, and Z. Zou, Hot Deformation Behavior and Constitutive Model of GH4169 Superalloy for Linear Friction Welding Process, J. Manuf. Process., 2018, 32, p 469–481. https://doi.org/10.1016/j.jmapro.2018.03.01710.1016/j.jmapro.2018.03.017 ↗
11. F. Li, C. Zhu, S. Li, H. Jiang, P. Zhang, R. Yang, and S. Zhao, A Comparative Study on Modified and Optimized Zerilli–Armstrong and Arrhenius-type Constitutive Models to Predict the Hot Deformation Behavior in 30Si2MnCrMoVE steel, J. Market. Res., 2022, 20, p 3918–3929. https://doi.org/10.1016/j.jmrt.2022.08.13410.1016/j.jmrt.2022.08.134 ↗
12. M. Razavipour and B. Jodoin, Material Model for Predicting Dynamic Response of Copper and Nickel at Very High Strain Rates Under Cold Spray Conditions, J. Therm. Spray Technol., 2021, 30(1–2), p 324–343. https://doi.org/10.1007/s11666-020-01137-z10.1007/s11666-020-01137-z ↗
13. P. Promoppatum and A.D. Rollett, Physics-Based and Phenomenological Plasticity Models for Thermomechanical Simulation in Laser Powder Bed Fusion Additive Manufacturing: A Comprehensive Numerical Comparison, Mater. Design, 2021, 204, p 109658. https://doi.org/10.1016/j.matdes.2021.10965810.1016/j.matdes.2021.109658 ↗
14. K. Li, Q. Pan, R. Li, S. Liu, Z. Huang, and X. He, Constitutive Modeling of the Hot Deformation Behavior in 6082 Aluminum Alloy, J. Mater. Eng. Perform., 2019, 28(2), p 981–994. https://doi.org/10.1007/s11665-019-3873-510.1007/s11665-019-3873-5 ↗
15. F. Masi, I. Stefanou, P. Vannucci, and V. Maffi-Berthier, Thermodynamics-Based Artificial Neural Networks for Constitutive Modeling, J. Mech. Phys. Solids, 2021, 147, p 104277. https://doi.org/10.1016/j.jmps.2020.10427710.1016/j.jmps.2020.104277 ↗
16. S. Xin Liu, F.T. Tian, and Y. Wenbin, A Review of Artificial Neural Networks in the Constitutive Modeling of Composite Materials, Compos. Part B Eng., 2021, 224, p 109152. https://doi.org/10.1016/j.compositesb.2021.10915210.1016/j.compositesb.2021.109152 ↗
17. A. Shokry, S. Gowid, H. Mulki, and G. Kharmanda, On the Prediction of the Flow Behavior of Metals and Alloys at a Wide Range of Temperatures and Strain Rates Using Johnson–Cook and Modified Johnson–Cook -Based Models: A Review, Materials (Basel), 2023, 16(4), p 1574. https://doi.org/10.3390/ma1604157410.3390/ma16041574 ↗
18. M.E. Korkmaz, Verification of Johnson–Cook Parameters of Ferritic Stainless Steel by Drilling Process: Experimental and Finite Element Simulations, J. Mater. Res. Technol., 2020, 9(3), p 6322–6330. https://doi.org/10.1016/j.jmrt.2020.03.04510.1016/j.jmrt.2020.03.045 ↗
19. D.C.C. MagalhÃEs, Andrea Madeira Kliauga, Vitor Luiz Sordi, Flow behavior and fracture of Al−Mg−Si alloy at cryogenic temperatures, Trans. Nonferrous Metals Soc. China, 2021, 31(3), p 595–608. https://doi.org/10.1016/s1003-6326(21)65522-x10.1016/s1003-6326(21)65522-x ↗
20. L. Niu, M. Cao, Z. Liang, B. Han, and Q. Zhang, A Modified Johnson–Cook Model Considering Strain Softening of A356 Alloy, Mater. Sci. Eng. A, 2020, 789, p 139612. https://doi.org/10.1016/j.msea.2020.13961210.1016/j.msea.2020.139612 ↗
21. S. Li, J. Sui, F. Ding, W. Shixiong, W. Chen, and C. Wang, Optimization of Milling Aluminum Alloy 6061–T6 using Modified Johnson–Cook Model, Simulat. Modell. Pract. Theory, 2021, 111, p 102330. https://doi.org/10.1016/j.simpat.2021.10233010.1016/j.simpat.2021.102330 ↗
22. A.H. Sajad Rasaee and D.A. Mirzaei, Constitutive Modelling of Al7075 Using the Johnson–Cook Model, Bull. Mater. Sci., 2019, 43(1), p 23. https://doi.org/10.1007/s12034-019-1987-x10.1007/s12034-019-1987-x ↗
23. R. Bobbili and V. Madhu, A Modified Johnson–Cook Model for FeCoNiCr High Entropy Alloy Over a Wide Range of Strain Rates, Mater. Lett., 2018, 218, p 103–105. https://doi.org/10.1016/j.matlet.2018.01.16310.1016/j.matlet.2018.01.163 ↗
24. J. He, F. Chen, B. Wang, and L.B. Zhu, A Modified Johnson–Cook Model for 10%Cr Steel at Elevated Temperatures and a Wide Range of Strain Rates, Mater. Sci. Eng. A, 2018, 715, p 1–9. https://doi.org/10.1016/j.msea.2017.10.03710.1016/j.msea.2017.10.037 ↗
25. A. Shokry, A Modified Johnson–Cook Model for Flow Behavior of Alloy 800H at Intermediate Strain Rates and High Temperatures, J. Mater. Eng. Perform., 2017, 26(12), p 5723–5730. https://doi.org/10.1007/s11665-017-3076-x10.1007/s11665-017-3076-x ↗
26. M. Murugesan and D.W. Jung, Johnson Cook Material and Failure Model Parameters Estimation of AISI-1045 Medium Carbon Steel for Metal Forming Applications, Materials (Basel), 2019, 12(4), p 609. https://doi.org/10.3390/ma1204060910.3390/ma12040609 ↗
27. Y. Wang, X. Zeng, H. Chen, X. Yang, F. Wang, and L. Zeng, Modified Johnson–Cook Constitutive Model of Metallic Materials under a Wide Range of Temperatures and Strain Rates, Results Phys., 2021, 27, p 104498. https://doi.org/10.1016/j.rinp.2021.10449810.1016/j.rinp.2021.104498 ↗
28. J. Kreyca and E. Kozeschnik, Temperature-Dependent Strain Hardening, Precipitation and Deformation-Induced Microstructure Evolution in AA 6061, Mater. Sci. Eng. A, 2017, 708, p 411–418. https://doi.org/10.1016/j.msea.2017.10.02710.1016/j.msea.2017.10.027 ↗
29. B.K. Roy, Y.P. Korkolis, Y. Arai, W. Araki, T. Iijima, and J. Kouyama, Plastic Deformation of AA6061-T6 at Elevated Temperatures: Experiments and Modeling, Int. J. Mech. Sci., 2022, 216, p 106943. https://doi.org/10.1016/j.ijmecsci.2021.10694310.1016/j.ijmecsci.2021.106943 ↗
30. M. Scapin and A. Manes, Behaviour of Al6061-T6 Alloy at Different Temperatures and Strain-Rates: Experimental Characterization and Material Modelling, Mater. Sci. Eng. A, 2018, 734, p 318–328. https://doi.org/10.1016/j.msea.2018.08.01110.1016/j.msea.2018.08.011 ↗
31. H.-R. Zhang, H. Zhao, R. Wang, X.-X. Liang, and Y. Zhu, Coupling Influences of Elevated Temperature and Strain Rate on the Behaviour of 6061–T6 Aluminium Alloy Used as Construction Material, Structures, 2022, 40, p 596–606. https://doi.org/10.1016/j.istruc.2022.04.05210.1016/j.istruc.2022.04.052 ↗
32. Z. Chen, G. Fang, and J.-Q. Zhao, Formability Evaluation of Aluminum Alloy 6061–T6 Sheet at Room and Elevated Temperatures, J. Mater. Eng. Perform., 2017, 26(9), p 4626–4637. https://doi.org/10.1007/s11665-017-2895-010.1007/s11665-017-2895-0 ↗
33. G.R. Johnson and W.H. Cook, Fracture Characteristics of Three Metals Subjected to Various Strains, Strain Rates, Temperatures and Pressures, Eng. Fract. Mech., 1985, 21(1), p 31–48. https://doi.org/10.1016/0013-7944(85)90052-910.1016/0013-7944(85)90052-9 ↗
34. Q.-T. Pham, B.-H. Lee, K.-C. Park, and Y.-S. Kim, Influence of the Post-Necking Prediction of Hardening Law on the Theoretical Forming Limit Curve of Aluminium Sheets, Int. J. Mech. Sci., 2018, 140, p 521–536. https://doi.org/10.1016/j.ijmecsci.2018.02.04010.1016/j.ijmecsci.2018.02.040 ↗
35. X. Chen, Q. Liao, Y. Niu, W. Jia, Q. Le, C. Cheng, Yu. Fuxiao, and J. Cui, A Constitutive Relation of AZ80 Magnesium alloy during Hot Deformation Based on Arrhenius and Johnson–Cook Model, J. Market. Res., 2019, 8(2), p 1859–1869. https://doi.org/10.1016/j.jmrt.2019.01.00310.1016/j.jmrt.2019.01.003 ↗
36. Y.C. Lin, X.-M. Chen, and G. Liu, A Modified Johnson–Cook model for Tensile Behaviors of Typical High-Strength Alloy Steel, Mater. Sci. Eng. A, 2010, 527(26), p 6980–6986. https://doi.org/10.1016/j.msea.2010.07.06110.1016/j.msea.2010.07.061 ↗
37. S.E. Clift, P. Hartley, C.E.N. Sturgess, and G.W. Rowe, Fracture Prediction in Plastic Deformation Processes, Int. J. Mech. Sci., 1990, 32(1), p 1–17. https://doi.org/10.1016/0020-7403(90)90148-C10.1016/0020-7403(90)90148-C ↗
38. A. Heidari, A. Ghassemi, and A. Atrian, A Numerical and Experimental Investigation of Temperature Effects on the Formability of AA6063 Sheets Using Different Ductile Fracture Criteria, Int. J. Adv. Manufact. Technol., 2019, 106(5–6), p 2595–2611. https://doi.org/10.1007/s00170-019-04579-010.1007/s00170-019-04579-0 ↗
39. L. Ming and O. Pantalé, An Efficient and Robust VUMAT Implementation of Elastoplastic Constitutive Laws in Abaqus/Explicit Finite Element Code, Mech. Industry, 2018, 19(3), p 308. https://doi.org/10.1051/meca/201802110.1051/meca/2018021 ↗
40. Y. Bao, Dependence of Ductile Crack Formation in Tensile Tests on Stress Triaxiality, Stress and Strain Ratios, Eng. Fract. Mech., 2005, 72(4), p 505–522. https://doi.org/10.1016/j.engfracmech.2004.04.01210.1016/j.engfracmech.2004.04.012 ↗
41. Y. Zhao, J. Sun, J. Li, Y. Yan, and P. Wang, A comparative Study on Johnson–Cook and Modified Johnson–Cook Constitutive Material Model to Predict the Dynamic Behavior Laser Additive Manufacturing FeCr Alloy, J. Alloys Compd., 2017, 723, p 179–187. https://doi.org/10.1016/j.jallcom.2017.06.25110.1016/j.jallcom.2017.06.251 ↗