Evaluation on prediction abilities of constitutive models considering FEA application

Tong Wen , Lan-tao Liu , Qian Huang , Xia Chen , Ji-zhao Fang

Journal of Central South University ›› 2018, Vol. 25 ›› Issue (6) : 1251 -1262.

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Journal of Central South University ›› 2018, Vol. 25 ›› Issue (6) : 1251 -1262. DOI: 10.1007/s11771-018-3822-8
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Evaluation on prediction abilities of constitutive models considering FEA application

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Abstract

Constitutive model plays an important role in the numerical simulations of metal forming. However, the influence of the models on the calculation is vague. Based on the stress-strain data of Al 7050 and Ti-6Al-4V alloys generated by isothermal compressive tests, the Johnson-Cook (JC) and Arrhenius-type (A-type) hyperbolic sine models were fitted to obtain the constants. Flow stresses directly calculated by the equations were compared with the experiment results, and rigid-plastic finite element analyses (FEA) utilizing these models were employed to simulate the same compression processes. The results show that A-type model has higher accuracy in the direct prediction of flow stress, even outside of the fit domain. The simulation results using A-type model also have higher agreement with the experiment; however, the suitability is affected by the referential parameters employed in the regression process. In terms of the overall deformation and strain distributions, there are slight differences among the simulation results using these two models.

Keywords

constitutive model / metal forming / numerical simulation / performance / isothermal compression

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Tong Wen, Lan-tao Liu, Qian Huang, Xia Chen, Ji-zhao Fang. Evaluation on prediction abilities of constitutive models considering FEA application. Journal of Central South University, 2018, 25(6): 1251-1262 DOI:10.1007/s11771-018-3822-8

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References

[1]

WenT, YueY-w, LiuL-t, YuJ-ming. Evaluation and prediction of hot rheological properties of Ti-6Al-4V in dual-phase region using processing map and artificial neural network [J]. Indian Journal of Engineering & Materials Sciences, 2014, 21(12): 647-656

[2]

LiangR, KhanA S. A critical review of experimental results and constitutive models for BCC and FCC metals over a wide range of strain rates and temperatures [J]. International Journal of Plasticity, 1999, 15(9): 963-980

[3]

SchulzeV, VöhringerO. A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures [C]. Proceedings of the 7th International Symposium on Ballistics, 19834147

[4]

PrawotoY, FanoneM, ShahediS, IsmailM S, WanN W B. Computational approach using Johnson-Cook model on dual phase steel [J]. Computational Materials Science, 2012, 54(3): 48-55

[5]

ZerilliF J, ArmstrongR W. Dislocationmechanics-based constitutive relations for material dynamics calculations [J]. Journal of Applied Physics, 1987, 61(5): 1816-1825

[6]

LiH Y, WangX F, LiuJ J, WuY. A comparative study on modified Johnson Cook, modified Zerilli-Armstrong and Arrhenius-type constitutive models to predict the hot deformation behavior in 28CrMnMoV steel [J]. Materials & Design, 2013, 49(8): 493-501

[7]

SamantarayD, MandalS, BorahU, BhaduriA K, SivaprasadP V. A thermo-viscoplastic constitutive model to predict elevated-temperature flow behaviour in a titanium-modified austenitic stainless steel [J]. Materials Science and Engineering A, 2009, 526(12): 1-6

[8]

SungJ H, KimJ H, WagonerR H. A plastic constitutive equation incorporating strain, strain-rate, and temperature [J]. International Journal of Plasticity, 2010, 26(12): 1746-1771

[9]

ParsaM H, OhadiD. A constitutive equation for hot deformation range of 304 stainless steel considering grain sizes [J]. Materials & Design, 2013, 52(12): 412-421

[10]

KocksU F. Realistic constitutive relations for metal plasticity [J]. Materials Science and Engineering A, 2001, 317(1): 181-187

[11]

ZhouM, ClodeM P. Constitutive equations for modelling flow softening due to dynamic recovery and heat generation during plastic deformation [J]. Mechanics of Materials, 1998, 27(2): 63-76

[12]

CaiM C, NiuL S, MaX F, ShiH J. A constitutive description of the strain rate and temperature effects on the mechanical behavior of materials [J]. Mechanics of Materials, 2010, 42(8): 774-781

[13]

GuptaA K, KrishnamurthyH N, SinghY, PrasadK M, SinghS K. Development of constitutive models for dynamic strain aging regime in Austenitic stainless steel 304 [J]. Materials & Design, 2013, 45(3): 616-627

[14]

MirzadehH, CabreraJ M, NajafizadehA. Constitutive relationships for hot deformation of austenite [J]. Acta Materialia, 2011, 59(16): 6441-6448

[15]

LinY C, ChenM S, ZhongJ. Effect of temperature and strain rate on the compressive deformation behavior of 42CrMo steel [J]. Journal of Materials Processing Technology, 2008, 205(1): 308-315

[16]

LinY C, ChenX M. A combined Johnson-Cook and Zerilli-Armstrong model for hot compressed typical high-strength alloy steel [J]. Computational Materials Science, 2010, 49(3): 628-633

[17]

SalemA A, KalidindiS R, SemiatinS L. Strain hardening due to deformation twinning in a-titanium: Constitutive relations and crystal-plasticity modeling [J]. Metallurgical & Materials Transactions A, 2006, 37(1): 259-268

[18]

GuptaA K, AnirudhV K, SinghS K. Constitutive models to predict flow stress in Austenitic Stainless Steel 316 at elevated temperatures [J]. Materials & Design, 2013, 43(1): 410-418

[19]

RohrI, NahmeH, ThomaK, AndersonC E. Material characterisation and constitutive modelling of a tungsten-sintered alloy for a wide range of strain rates [J]. International Journal of Impact Engineering, 2008, 35(8): 811-819

[20]

WuH Y, YangJ C, ZhuF J, WuC T. Hot compressive flow stress modeling of homogenized AZ61 Mg alloy using strain-dependent constitutive equations [J]. Materials Science and Engineering A, 2013, 574(7): 17-24

[21]

ChangizianP, Zarei-HanzakiA, RoostaeiA A. The high temperature flow behavior modeling of AZ81 magnesium alloy considering strain effects [J]. Materials & Design, 2012, 39(8): 384-389

[22]

RoyM J, MaijerD M, DancoineL. Constitutive behavior of as-cast A356 [J]. Materials Science and Engineering A, 2012, 548(6): 195-205

[23]

SunC, LiuG, ZhangQ, LiR, WangL. Determination of hot deformation behavior and processing maps of IN 028 alloy using isothermal hot compression test [J]. Materials Science and Engineering A, 2014, 595(2): 92-98

[24]

WangL, LiuF, ZuoQ, ChenC F. Prediction of flow stress for N08028 alloy under hot working conditions [J]. Materials & Design, 2013, 47(5): 737-745

[25]

SamantarayD, MandalS, BhaduriA K. A comparative study on Johnson-Cook, modified Zerilli-Armstrong and Arrhenius-type constitutive models to predict elevated temperature flow behaviour in modified 9Cr-1Mo steel [J]. Computational Materials Science, 2009, 47(2): 568-576

[26]

HeA, XieG, ZhangH, WangX. A comparative study on Johnson-Cook, modified Johnson-Cook and Arrhenius-type constitutive models to predict the high temperature flow stress in 20CrMo alloy steel [J]. Materials & Design, 2013, 52(12): 677-685

[27]

JiG, LiF, LiQ, LiH, LiZ. A comparative study on Arrhenius-type constitutive model and artificial neural network model to predict high-temperature deformation behaviour in Aermet100 steel [J]. Materials Science and Engineering A, 2011, 528(1314): 4774-4782

[28]

LiH Y, WangX F, WeiD D, HuJ D, LiY H. A comparative study on modified Zerilli-Armstrong, Arrhenius-type and artificial neural network models to predict high-temperature deformation behavior in T24 steel [J]. Materials Science and Engineering A, 2012, 536(2): 216-222

[29]

GuptaA K, SinghS K, ReddyS, HariharanG. Prediction of flow stress in dynamic strain aging regime of austenitic stainless steel 316 using artificial neural network [J]. Materials & Design, 2012, 35(3): 589-595

[30]

MandalS, RakeshV, SivaprasadP V, VenugopalS, KasiviswanathanK V. Constitutive equations to predict high temperature flow stress in a Ti-modified austenitic stainless steel [J]. Materials Science and Engineering A, 2009, 500(12): 114-121

[31]

TianY, HuangL, MaH, LiJ. Establishment and comparison of four constitutive models of 5A02 aluminium alloy in high-velocity forming process [J]. Materials & Design, 2014, 54(2): 587-597

[32]

HosfordW F, CaddellR MMetal forming-Mechanics and Metallurgy [M], 2007, New York, Cambridge University Press

[33]

LinY C, ChenM S, ZhongJ. Numerical simulation for stress/strain distribution and microstructural evolution in 42CrMo steel during hot upsetting process [J]. Computational Materials Science, 2008, 43(4): 1117-1122

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