Transactions of Materials and Heat Treatment

Title：Hot deformation behavior and comparison of three rheological stress models on AerMet100 ultra-high strength steel

Authors： Liu Kezhuo1 Huang Liang1 Su Yang1 Zhao Mingjie1 2 Sun Chaoyuan3 Li Pengchuan3 Li Jianjun1

Unit： 1. State Key Laboratory of Materials Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology 2. School of Aeronautical Manufacturing Engineering Nanchang Hangkong University 3.China National Erzhong Group Deyang Wanhang Die Forging Co. Ltd.

KeyWords： AerMet100 ultra-high strength steel hot deformation behavior rheological stress constitutive model BP neural network

ClassificationCode：TG115.53

year,vol(issue):pagenumber：2024,49(10):209-220

Abstract：

The hot compression tests of AerMet100 ultra-high strength steel samples were carried out at the deformation temperature of 1173-1473 K, the strain rate of 0.01-10 s-1 and the deformation amount of 60%. The results show that with the increasing of strain, the true stress of AerMet100 ultra-high strength steel samples first rapidly increases, and then the growth rate decreases until it tends to be dynamically stable. Under the deformation conditions of the test, the true stress-true strain curve exhibits two kinds of curve types wit dynamic recovery type and dynamic recrystallization type. Based on the test results, the strain-compensated Arrhenius constitutive model, the optimized Johnson-Cook model and the BP neural network model are constructed respectively, and the prediction accuracy of the three models on the high temperature deformation behavior of AerMet100 ultra-high strength steel were analyzed and compared. The linear correlation coefficients R of the three models are 0.99461, 0.98694 and 0.99998, respectively, and the average relative error absolute values AARE are 3.029%, 5.220% and 0.129%, respectively. Among them, the BP neural network model predicts the highest linear correlation strength of rheological stress and the highest prediction accuracy.

Funds：

国家重点研发计划(2022YFB3706901，2022YFB3706903)

作者简介：刘可卓（2000-），男，硕士研究生,E-mail：kzliu2022@hust.edu.cn;通信作者：黄亮（1981-），男，博士，教授,E-mail：huangliang@hust.edu.cn

Reference：

[1]Shi X H, Zeng W D, Zhao Q Y, et al. Study on the microstructure and mechanical properties of Aermet100 steel at the tempering temperature around 482 ℃[J]. Journal of Alloys and Compounds, 2016, 679: 184-190.

[2]Ji G L, Li F G, Li Q H, et al. Research on the dynamic recrystallization kinetics of Aermet100 steel [J]. Materials Science and Engineering: A, 2010, 527(9): 2350-2355.

[3]Li J H, Zhan D P, Jiang Z H, et al. Progress on improving strength-toughness of ultra-high strength martensitic steels for aerospace applications: A review [J]. Journal of Materials Research and Technology, 2023, 23: 172-190.

[4]Shi L Q, Ran X Z, Zhai Y M, et al. Influence of isothermal tempering on microstructures and hydrogen-environmentally embrittlement susceptibility of laser additively manufactured ultra-high strength AerMet100 steel [J]. Materials Science and Engineering: A, 2023, 876: 145167.

[5]李超群,张立文,李飞,等. 10钢热变形过程动态再结晶行为[J]. 锻压技术,2022,47(2):207-212.

Li C Q，Zhang L W，Li F，et al. Dynamic recrystallization behavior for 10 steel during thermal deformation process[J]. Forging & Stamping Technology,2022,47(2):207-212.

[6]Huang L, Li C M, Li C L, et al. Research progress on microstructure evolution and hot processing maps of high strength β titanium alloys during hot deformation [J]. Transactions of Nonferrous Metals Society of China, 2022, 32(12): 3835-3859.

[7]Xu L, Chen L, Chen G J, et al. Hot deformation behavior and microstructure analysis of 25Cr3Mo3NiNb steel during hot compression tests [J]. Vacuum, 2018, 147: 8-17.

[8]Zeng R, Huang L, Li J J, et al. Quantification of multiple softening processes occurring during multi-stage thermoforming of high-strength steel [J]. International Journal of Plasticity, 2019, 120: 64-87.

[9]Ashitiani H R R, Parsa M H, Bisadi H. Constitutive equations for elevated temperature flow behavior of commercial purity aluminum [J]. Materials Science and Engineering: A, 2012, 545: 61-67.

[10]Huh H, Lee H J, Song J H. Dynamic hardening equation of the auto-body steel sheet with the variation of temperature [J]. International Journal of Automotive Technology, 2012, 13(1): 43-60.

[11]Huang Y C, Lin Y C, Deng J, et al. Hot tensile deformation behaviors and constitutive model of 42CrMo steel [J]. Materials & Design, 2014, 53: 349-356.

[12]Vilamosa V, Clausen A H, Borvik T, et al. A physically-based constitutive model applied to AA6082 aluminium alloy at large strains, high strain rates and elevated temperatures [J]. Materials & Design, 2016, 103: 391-405.

[13]Haghdad N, Martin D, Hodgson P. Physically-based constitutive modelling of hot deformation behavior in a LDX 2101 duplex stainless steel[J]. Materials & Design, 2016, 106: 420-427.

[14]赵杰. TA15钛合金板材高温变形行为及变速率热态气压成形研究 [D]. 哈尔滨: 哈尔滨工业大学, 2020.

Zhao J. Research on Hot Deformation Behavior and Variable-rate Hot Gas Forming of TA15 Titanium Sheet [D]. Harbin: Harbin Institute of Technology, 2020.

[15]Huang C Q, Jia X D, Zhang Z W. A modified back propagation artificial neural network model based on genetic algorithm to predict the flow behavior of 5754 aluminum alloy [J]. Materials, 2018, 11(5): 855.

[16]Shu X Y, Lu S Q, Wang K L, et al. A comparative study on constitutive equations and artificial neural network model to predict high-temperature deformation behavior in nitinol 60 shape memory alloy [J]. Journal of Materials Research, 2015, 30(12): 1988-1998.

[17]Ashtiani H R R, Shahsavari P. A comparative study on the phenomenological and artificial neural network models to predict hot deformation behavior of AlCuMgPb alloy [J]. Journal of Alloys and Compounds, 2016, 687: 263-273.

[18]Sellar C M, Mctegart W J. On the mechanism of hot deformation [J]. Acta Metallurgica, 1966, 14(9): 1136-1138.

[19]王俊, 王克鲁, 鲁世强, 等. TA5钛合金热变形行为及本构模型 [J]. 塑性工程学报, 2022, 29(5): 153-160.

Wang J, Wang K L, Lu S Q, et al. Hot deformation behavior and constitutive model of TA5 titanium alloy [J]. Journal of Plasticity Engineering, 2022, 29(5): 153-160.

[20]章晓婷, 黄亮, 李建军, 等. 300M高强钢高温流变行为及本构方程 [J]. 中南大学学报(自然科学版), 2017, 48(6): 1439-1447.

Zhang X T, Huang L, Li J J, et al. Flow behaviors and constitutive model of 300M high strength steel at elevated temperature [J]. Journal of Central South University (Science and Technology), 2017, 48(6): 1439-1447.

[21]Zhao M J, Huang L, Li C M, et al. Evaluation of the deformation behaviors and hot workability of a high-strength low-alloy steel [J]. Materials Science and Engineering: A, 2021, 810: 141031.

[22]Lin Y C, Chen X M, Liu G. A modified Johnson-Cook model for tensile behaviors of typical high-strength alloy steel [J]. Materials Science and Engineering: A, 2010, 527(26): 6980-6986.

[23]Kotkunde N, Deole A D, Gupta A K, et al. Comparative study of constitutive modeling for Ti-6Al-4V alloy at low strain rates and elevated temperatures [J]. Materials & Design, 2014, 55: 999-1005.

[24]刘玉冰, 管延锦, 丁慧莹, 等. 模具钢的高温变形行为及本构模型的建立 [J]. 锻压技术, 2023, 48(9): 220-229.

Liu Y B, Guan Y J, Ding H Y, et al. Deformation behavior at high temperature and establishment of constitutive model for die steel [J]. Forging & Stamping Technology, 2023, 48(9): 220-229.

[25]Jarugla R, Aravid U, Meena B S, et al. High temperature deformation behavior and constitutive modeling for flow behavior of alloy 718 [J]. Journal of Materials Engineering and Performance, 2020, 29(7): 4692-4707.

[26]Adarsh S H, Sampath V. Prediction of high temperature deformation characteristics of an Fe-based shape memory alloy using constitutive and artificial neural network modelling [J]. Materials Today Communications, 2020, 22: 100841.

[27]Wen D X, Yue T X, Xiong Y B, et al. High-temperature tensile characteristics and constitutive models of ultrahigh strength steel [J]. Materials Science and Engineering: A, 2021, 803: 140491.

[28]Shokry A, Gowid S, Kharmanda G, et al. Constitutive models for the prediction of the hot deformation behavior of the 10%Cr steel alloy [J]. Materials, 2019, 12(18): 2873.

[29]Sakai T, Belyakov A, Kaibyshe R, et al. Dynamic and post-dynamic recrystallization under hot, cold and severe plastic deformation conditions [J]. Progress in Materials Science, 2014, 60: 130-207.

[30]Jonas J J, Quelennec X, Jiang L, et al. The Avrami kinetics of dynamic recrystallization [J]. Acta Materialia, 2009, 57(9): 2748-2756.

[31]Johnson G R, Cook W H. A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures [J]. Seventh International Symposium on Ballistics, the Hague, the Netherlands, 1983, 21: 541-548.

[32]Chao Z L, Jiang L T, Chen G Q, et al. A modified Johnson-Cook model with damage degradation for B4Cp/Al composites [J]. Composite Structures, 2022, 282: 115029.

[33]石旭. 300M超高强钢高温本构模型的研究 [D]. 哈尔滨: 哈尔滨理工大学, 2015.

Shi X. Research on the High Temperature Constitutive Model of 300M Ultrahigh Strength Steel [D]. Harbin: Harbin Institute of Technology, 2015.

Service：

【This site has not yet opened Download Service】【Add Favorite】