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A study on the constitutive equation of HC420LA steel subjected to high strain rates

Published online by Cambridge University Press:  23 January 2019

Junjia Cui Open the ORCID record for Junjia Cui [Opens in a new window] ,
Qiong Wang ,
Dongying Dong ,
Hao Jiang ,
Xu Zhang Open the ORCID record for Xu Zhang [Opens in a new window]  and
Guangyao Li
Junjia Cui
Affiliation:
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
Qiong Wang
Affiliation:
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
Dongying Dong
Affiliation:
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
Hao Jiang
Affiliation:
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
Xu Zhang
Affiliation:
College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China
Guangyao Li*
Affiliation:
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
*
a)Address all correspondence to this author. e-mail: [email protected]
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Abstract

In this paper, the influence of strain rate on the mechanical behavior of high-strength low-alloy (HC420LA) steel were studied. Quasi-static and dynamic tensile experiments were performed with strain rates ranging from 0.001 to 500 s−1 at room temperature. The digital image correlation technique was used to obtain the full-field strain. The experimental results showed that HC420LA steel exhibited positive strain rate sensitivity. Based on experimental results, the modified Johnson–Cook (J–C) model was used to model the constitutive behavior of HC420LA steel. Predictions of the standard and modified J–C models were compared using standard statistical parameters. The modified J–C model showed better agreement with the experimental data. Then, numerical simulation of the representative tensile test at a strain rate of 100 s−1 was performed using the finite element code LS-DYNA. Good correlation between the experimental and numerical simulation results was achieved.

Keywords

high strain ratedigital image correlationstrain distributionconstitutive modelingfinite element simulation
Type
Article
Information
Journal of Materials Research , Volume 34 , Issue 6 , 28 March 2019 , pp. 1034 - 1042
Copyright
Copyright © Materials Research Society 2019 

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References

Oyyaravelu, R., Kuppan, P., and Arivazhagan, N.: Metallurgical and mechanical properties of laser welded high strength low alloy steel. J. Adv. Res. 7, 463 (2016).CrossRefGoogle ScholarPubMed
Han, G., Xie, Z.J., Xiong, L., Shang, C.J., and Misra, R.D.K.: Evolution of nano-size precipitation and mechanical properties in a high strength-ductility low alloy steel through intercritical treatment. Mater. Sci. Eng., A 705, 89 (2017).CrossRefGoogle Scholar
Macwan, A., Kumar, A., and Chen, D.L.: Ultrasonic spot welded 6111-T4 aluminum alloy to galvanized high-strength low-alloy steel: Microstructure and mechanical properties. Mater. Des. 113, 284 (2017).CrossRefGoogle Scholar
Li, Y., Wan, X.L., Lu, W.Y., Shirzadi, A.A., Isayev, O., Hress, O., and Wu, K.M.: Effect of Zr–Ti combined deoxidation on the microstructure and mechanical properties of high-strength low-alloy steels. Mater. Sci. Eng., A 659, 179 (2016).CrossRefGoogle Scholar
Khan, A.S., Baig, M., Choi, S.H., Yang, H.S., and Sun, X.: Quasi-static and dynamic responses of advanced high strength steels: Experiments and modeling. Int. J. Plast. 30–31, 1 (2012).Google Scholar
Kim, J.H., Kim, D., Han, H.N., Barlat, F., and Lee, M.G.: Strain rate dependent tensile behavior of advanced high strength steels: Experiment and constitutive modeling. Mater. Sci. Eng., A 559, 222 (2013).CrossRefGoogle Scholar
Wang, W., Li, M., He, C., Wei, X., Wang, D., and Du, H.: Experimental study on high strain rate behavior of high strength 600–1000 MPa dual phase steels and 1200 MPa fully martensitic steels. Mater. Des. 47, 510 (2013).CrossRefGoogle Scholar
Qin, J., Chen, R., Wen, X., Lin, Y., Liang, M., and Lu, F.: Mechanical behaviour of dual-phase high-strength steel under high strain rate tensile loading. Mater. Sci. Eng., A 586, 62 (2013).CrossRefGoogle Scholar
Singh, N.K., Cadoni, E., Singha, M.K., and Gupta, N.K.: Dynamic tensile behavior of multi phase high yield strength steel. Mater. Des. 32, 5091 (2011).CrossRefGoogle Scholar
Fathi, H., Emadoddin, E., and Mohammadian Semnani, H.R.: Simulation and experimental investigation of strain rate impact on martensitic transformation in 304L steel through dome test. J. Mater. Res. 31, 2136 (2016).CrossRefGoogle Scholar
Smith, G.M., Higgins, O., and Sampath, S.: In situ observation of strain and cracking in coated laminates by digital image correlation. Surf. Coat. Technol. 328, 211 (2017).CrossRefGoogle Scholar
Valeri, G., Koohbor, B., Kidane, A., and Sutton, M.A.: Determining the tensile response of materials at high temperature using DIC and the virtual fields method. Optic Laser. Eng. 91, 53 (2017).CrossRefGoogle Scholar
Flores, M., Mollenhauer, D., Runatunga, V., Beberniss, T., Rapking, D., and Pankow, M.: High-speed 3D digital image correlation of low-velocity impacts on composite plates. Composites, Part B 131, 153 (2017).CrossRefGoogle Scholar
Tarigopula, V., Hopperstad, O.S., Langseth, M., Clausen, A.H., and Hild, F.: A study of localisation in dual-phase high-strength steels under dynamic loading using digital image correlation and FE analysis. Int. J. Solids Struct. 45, 601 (2008).CrossRefGoogle Scholar
Wu, D.J., Mao, W.G., Zhou, Y.C., and Lu, C.: Digital image correlation approach to cracking and decohesion in a brittle coating/ductile substrate system. Appl. Surf. Sci. 257, 6040 (2011).CrossRefGoogle Scholar
Chen, X., Niu, C., Lian, C., and Lin, J.: The evaluation of formability of the 3rd generation advanced high strength steels QP980 based on digital image correlation method. Procedia Eng. 207, 556 (2017).CrossRefGoogle Scholar
Kammers, A.D., Wongsangam, J., Langdon, T.G., and Daly, S.: The microstructure length scale of strain rate sensitivity in ultrafine-grained aluminum. J. Mater. Res. 30, 981 (2015).CrossRefGoogle Scholar
Peirs, J., Verleysen, P., Paepegem, W.V., and Degrieck, J.: Determining the stress–strain behaviour at large strains from high strain rate tensile and shear experiments. Int. J. Impact Eng. 38, 406 (2011).CrossRefGoogle Scholar
Zhao, Y., Sun, J., Li, J., Yan, Y., and Wang, P.: 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. 723, 179 (2017).CrossRefGoogle Scholar
Chang, L., Zhou, C., Peng, J., Li, J., and He, X.: Fields–Backofen and a modified Johnson–Cook model for CP-Ti at ambient and intermediate temperature. Rare Met. Mater. Eng. 46, 1803 (2017).Google Scholar
Sahu, S., Mondal, D.P., Goel, M.D., Ansari, M.Z., and Ansari, Z.: Finite element analysis of AA1100 elasto-plastic behaviour using Johnson–Cook model. Mater. Today 5, 5349 (2018).Google Scholar
Chen, J., Li, J., and Li, Z.: Experiment research on rate-dependent constitutive model of Q420 steel. Constr. Build. Mater. 153, 816 (2017).CrossRefGoogle Scholar
Gurusamy, M.M. and Rao, B.C.: On the performance of modified Zerilli–Armstrong constitutive model in simulating the metal-cutting process. J. Manuf. Process. 28, 253 (2017).CrossRefGoogle Scholar
Sabokpa, O., Zarei-Hanzaki, A., Abedi, H.R., and Haghdadi, N.: Artificial neural network modeling to predict the high temperature flow behavior of an AZ81 magnesium alloy. Mater. Des. 39, 390 (2012).CrossRefGoogle Scholar
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