A High-Temperature Strain-Compensated Arrhenius-Type Constitutive Model and an Improved Avrami-Type Dynamic Recrystallization Model of 40CrNiMo
Source abstract
Abstract
The flow stress of a metallic material is one of the important parameters to measure the plastic deformability of a material. The quality of the microstructure reflects the forming quality and reliability of a part. Therefore, a high-quality flow stress and microstructure models are very important for the optimization of the process parameters. The flow stress and dynamic recrystallization (DRX) law of the 40CrNiMo axle steel were obtained by performing a thermal simulation compression test and metallography examination. The effects of deformation temperatures, strain rates, and initial grain sizes on the DRX and flow curves were discussed. A strain-compensated Arrhenius-type flow stress equation was established. Considering the influence of the deformation temperatures, strain rates, and initial grain sizes on DRX, a kinetic model and an average grain size evolution model for DRX were established. Statistical and finite element (FE) simulation methods were used to verify the predictability and validity of the flow stress and the microstructure models, which provides an important basis for the study of hot forming of the 40CrNiMo steel.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Metallurgy and Material Forming · Metal Alloys Wear and Properties · Microstructure and Mechanical Properties of Steels
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (32)
Show source-provided references
1. A. Natasha, J. Ghani, C.C. Haron, and J. Syarif, The influence of machining condition and cutting tool wear on surface roughness of AISI 4340 steel, in Paper presented at IOP Conference Series: Materials Science and Engineering, 2018.10.1088/1757-899X/290/1/012017 ↗
2. E. Alibeikia and J. Rajabib, Investigation of Flow Stress Behavior of AISI 4340 Steel in Thermomechanical Process, Jurnal Kejuruteraan., 2020, 32, p 25–30.10.17576/jkukm-2020-32(1)-04 ↗
3. D.J. Kong and L. Zhang, Effects of Laser Quenching on Impact Toughness and Fracture Morphologies of 40CrNiMo High Strength Steel, J. Mater. Eng. Perform., 2014, 23, p 3695–3702.10.1007/s11665-014-1164-8 ↗
4. J. Li, A.X. Feng, and J.Z. Zhou et al., High-Temperature Wear Properties and Microstructural Characterization of 40CrNiMo Structural Steel Treated by Cryogenic Laser Peening, Vacuum, 2018, 157, p 320–323.10.1016/j.vacuum.2018.08.051 ↗
5. H. Chen, A.X. Feng, J. Li, T.D. Jia, and Y. Liu, Effects of Multiple Laser Peening impacts on Mechanical Properties and Microstructure Evolution of 40CrNiMo Steel, J. Mater. Eng. Perform., 2019, 28, p 2522–2529.10.1007/s11665-019-04034-x ↗
6. W. Wang, R. Ma, and L.P. Li et al., Constitutive Analysis and Dynamic Recrystallization Behavior of As-Cast 40CrNiMo Alloy Steel During Isothermal Compression, J. Mater. Res. Technol., 2020, 9, p 1929–1940.10.1016/j.jmrt.2019.12.025 ↗
7. R.X. Zhai, W. Wang, and R. Ma et al., Hot Deformation Behavior and Processing Map of As-Cast 40CrNiMo Alloy Steel, J. Mater. Eng. Perform., 2020, 29, p 964–974.10.1007/s11665-020-04596-1 ↗
8. Y.C. Lin, D.X. Wen, Y.C. Huang, X.M. Chen, and X.W. Chen, A Unified Physically Based Constitutive Model for Describing Strain Hardening Effect and Dynamic Recovery Behavior of a Ni-Based Superalloy, J. Mater. Res., 2015, 30, p 3784–3794.10.1557/jmr.2015.368 ↗
9. C.-Q. Huang, J. Deng, S.-X. Wang, and L.-l Liu, A Physical-Based Constitutive Model to Describe the Strain-Hardening and Dynamic Recovery Behaviors of 5754 Aluminum Alloy, Mater Sci Eng A, 2017, 699, p 106–113.10.1016/j.msea.2017.04.086 ↗
10. W.A. Johnson and R.F. Maehl, Reaction Kinetics in Processes of Nucleation and Growth. Trans. Am. Inst. Min. Met. Eng., 1939 135, p 416-442
11. M. Avrami, Kinetics of Phase Change. II Transformation-Time Relations for Random Distribution of Nuclei, J. Chem. Phys., 1940, 8, p 212–224.10.1063/1.1750631 ↗
12. L. Liu, Y. X. Wu, H. Gong, F. Dong, and A. S. Ahmad, Modified Kinetic Model for Describing Continuous Dynamic Recrystallization Behavior of Al 2219 Alloy During Hot Deformation Process. J. Alloys Compds., 2020, 817.10.1016/j.jallcom.2019.153301 ↗
13. Y. Bai and T. Wierzbicki, A Comparative Study of Three Groups of Ductile Fracture Loci in the 3D Space, Eng. Fract. Mech., 2015, 135, p 147–167.10.1016/j.engfracmech.2014.12.023 ↗
14. X. Quelennec and J.J. Jonas, Simulation of Austenite Flow Curves under Industrial Rolling Conditions Using a Physical Dynamic Recrystallization Model, ISIJ Int., 2012, 52, p 1145–1152.10.2355/isijinternational.52.1145 ↗
15. 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, p 6980–6986.10.1016/j.msea.2010.07.061 ↗
16. M.-S. Chen, Y. Lin, and X.-S. Ma, The Kinetics of Dynamic Recrystallization of 42CrMo Steel, Mater. Sci. Eng. A, 2012, 556, p 260–266.10.1016/j.msea.2012.06.084 ↗
17. G. Chen, L. Chen, G. Zhao, C. Zhang, and W. Cui, Microstructure Analysis of an Al-Zn-Mg Alloy During Porthole Die Extrusion Based on Modeling of Constitutive Equation and Dynamic Recrystallization, J. Alloy. Compd., 2017, 710, p 80–91.10.1016/j.jallcom.2017.03.240 ↗
18. M.J. Wang, C.Y. Sun, M.W. Fu, Z.L. Liu, and L.Y. Qian, Study on the Dynamic Recrystallization Mechanisms of Inconel 740 Superalloy During Hot Deformation. J. Alloys Compds. 2020, 82010.1016/j.jallcom.2019.153325 ↗
19. X. Gao, H.B. Wu, M. Liu, Y.X. Zhang, and X.D. Zhou, Dynamic Recovery and Recrystallization Behaviors of C71500 Copper-Nickel Alloy Under Hot Deformation, J. Mater. Eng. Perform., 2020, 29, p 7678–7692.10.1007/s11665-020-05221-x ↗
20. J. Zeng, F. Wang, S. Dong, X. Nie, Y. Fan, and J. Dong, A New Dynamic Recrystallization Kinetics Model of Cast-Homogenized Magnesium Alloys, Metall. Mater. Trans. A., 2021, 52, p 316–331.10.1007/s11661-020-06064-w ↗
21. P. Ei and J. Jj, Initiation of Dynamic Recrystallization in Constant Strain Rate Hot Deformation, ISIJ Int., 2003, 43, p 684–691.10.2355/isijinternational.43.684 ↗
22. S. Mandal, P.V. Sivaprasad, and R.K. Dube, Modeling Microstructural Evolution During Dynamic Recrystallization of Alloy D9 Using Artificial Neural Network, J. Mater. Eng. Perform., 2007, 16, p 672–679.10.1007/s11665-007-9098-z ↗
23. Y. Zhu, Y. Cao, and C. Liu et al., Dynamic Behavior and Modified Artificial Neural Network Model for Predicting Flow Stress During Hot Deformation of Alloy 925, Mater. Today Commun., 2020, 25, p 101329.10.1016/j.mtcomm.2020.101329 ↗
24. C.M. Sellars and W.J.M. Tegart, Hot Workability, Metall. Rev., 1972, 17, p 1–24.10.1179/095066072790137765 ↗
25. C. Zener and J.H. Hollomon, Effect of Strain Rate Upon Plastic Flow of Steel, J. Appl. Phys., 1944, 15, p 22–32.10.1063/1.1707363 ↗
26. H. Mirzadeh and A. Najafizadeh, Prediction of the Critical Conditions for Initiation of Dynamic Recrystallization, Mater. Des., 2010, 31, p 1174–1179.10.1016/j.matdes.2009.09.038 ↗
27. G.-B. Tang, Z.-d Liu, and H. Dong et al., Numerical Simulation of Austenite Recrystallization in CSP Hot Rolled C-Mn Steel Strip, J. Iron Steel Res. Int., 2007, 14, p 49–55.10.1016/S1006-706X(07)60057-0 ↗
28. P. Zhou and Q.X. Ma, Dynamic Recrystallization Behavior and Constitutive Modeling of As-Cast 30Cr2Ni4MoV Steel Based on Flow Curves, Met. Mater. Int., 2017, 23, p 359–368.10.1007/s12540-017-6538-7 ↗
29. Y. Lin and M.-S. Chen, Study of Microstructural Evolution During Static Recrystallization in a Low Alloy Steel, J. Mater. Sci., 2009, 44, p 835–842.10.1007/s10853-008-3120-1 ↗
30. H.R.R. Ashtiani, P. Shahsavari, A Comparative Study on the Phenomenological and Artificial Neural Network Models to Predict Hot Deformation Behavior of AlCuMgPb Alloy. J. Alloys Compds., 2016, 687.10.1016/j.jallcom.2016.04.300 ↗
31. M.A. Mostafaei, Serrated Yielding Behavior After Cold and Hot Rolling of a High Mg Content Al-Mg Alloy, J. Alloys Compds., 2019, 811, p 811.10.1016/j.jallcom.2019.151997 ↗
32. J. Bai, Y. Huo, and T. He, et al., Comparison of five different models predicting the hot Deformation Behavior of EA4T Steel. J. Mater. Eng. Perform., 2022, p 1–1410.1007/s11665-022-06828-y ↗