Development of Johnson Cook Model for Zircaloy-4 with Low Oxygen Content

Limbadri, K.; Hansoge, Nitin K.; Ram, A. Maruthi; Saibaba, N.; Rao, V. Venkateswara; Murthy, J.N.; Gupta, Amit Kumar; Singh, Swadesh Kumar

doi:10.1016/j.matpr.2017.01.108

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Sahu et al [11] established the J-C model of AA1100 aluminum alloy and simulated and analyzed it by finite element software, the results show that the prediction results have a better accuracy. Limbadri et al [12][13] predicted the effect of deformation conditions on the stress by using J-C model. Buzyurkin et al [14] calculated the parameters of J-C model of VT6, OT4 and OT4-0 titanium alloys, and established J-C model to calculate stress.…”

Section: -4nmentioning

confidence: 99%

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel During High Temperature Deformation

Li¹,

Ji²,

Cai³

et al. 2019

Preprint

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The Gleeble-1500D thermal simulation test machine was used to conduct the isothermal compression test on 21-4N at the strain rate ( ) of 0.01-10s-1, the deformation temperature (T) of 1273-1453K and the maximum deformation is 0.916. The data of the stress-strain ( - )were obtained. Based on the - data, the Johnson-Cook (J-C), modified J-C, Arrhenius and Back-Propagation Artificial Neural Network (BP-ANN) models were established. The accuracy of four models were verified, analyzed and compared. The results show that J-C model has a higher accuracy only under reference deformation conditions. When the deformation condition changes greatly, the accuracy of J-C model is significantly reduced. The coupling effect of T and of modified J-C model is considered, and the prediction accuracy is greatly improved The Arrhenius model introduces Zener-Hollomon (Z) to represent the coupling effect of T and , it has a fairly high prediction accuracy. And it can predict flow stress ( ) accurately at different conditions. The accuracy of BP-ANN model is the highest, but its learning rate is low, the learning and memory are unstable. It has no memory for the weights and thresholds of the completed training. So, there are certain limitations of it in use. Finally, a FEM of the isothermal compression experiment for four models were established, and the distribution of the equivalent stress field, equivalent strain field and temperature field with the deformation degree of 60% were obtained.

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Section: -4nmentioning

confidence: 99%

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel During High Temperature Deformation

Li¹,

Ji²,

Cai³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…) →is the strain hardening impact The selected reference strain rate and temperature for each alloy are presented in table 1. As in Johnson-cook model generally, the minimum experimental temperature is selected to be a reference temperature in such a way that TTref according to [42][43][44][45]. By the same way, the minimum experimental strain rate and temperature were considered as references strain rate and temperature for each alloy in this study.…”

Section: Mathematical Modelling With Consideration Of Microstructure mentioning

confidence: 99%

Modelling approach for predicting the superplastic deformation behaviour of titanium alloys with strain hardening/softening characterizations

Mosleh

Mestre-Rinn

Khalil

et al. 2019

Mater. Res. Express

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This paper introduces an approach for modelling the flow behaviour of different titanium alloys (VT6, OT4-1 and VT14 alloys by Russian specifications) in superplastic deformation temperature and strain rate ranges. The initial microstructure parameters (d V , , , a b a b ) before starting the deformation test were included in the constructed model for each alloy. The investigated alloys have different initial microstructures and flow behaviour characteristics. The isothermal uniaxial tensile deformation tests were performed at the superplastic deformation temperature and strain rate ranges of each alloy. The VT6, OT4-1 alloys were characterized by strain hardening effect during the deformation test, while VT14 alloy was characterized by strain softening effect. A comparison study between the experimental and modelled data was performed. The general equation of the constructed models was affected by the flow behaviour of the investigated alloys. The comparison results proved the good capability of the constructed models to predict the flow behaviour of the studied alloys. The correlation coefficient R was 0.98, 0.95 and 0.97 for VT6, OT4-1 and VT14, respectively. The predictability of the constructed model was assessed by the cross-validation technique, which ascertained the quality of the constructed model.

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“…Sahu et al [13] established the J-C model of AA1100 aluminum alloy and simulated and analyzed it by finite element software, the results show that the prediction results have a better accuracy. Limbadri et al [14,15] predicted the effect of deformation conditions on the stress by using J-C model. Buzyurkin et al [16] calculated the parameters of J-C model of VT6, OT4 and OT4-0 titanium alloys, and established J-C model to calculate stress.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel during High Temperature Deformation

Cai

et al. 2019

Materials

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The Gleeble-1500D thermal simulation test machine was used to conduct the isothermal compression test on 21-4N at the strain rate ( ε ˙ ) of 0.01–10 s−1, the deformation temperature (T) of 1273–1453 K and the maximum deformation is 0.916. The data of the stress-strain (σ-ε) were obtained. Based on the σ-ε data, the Johnson-Cook (J-C), modified J-C, Arrhenius and Back-Propagation Artificial Neural Network (BP-ANN) models were established. The accuracy of four models were verified, analyzed and compared. The results show that J-C model has a higher accuracy only under reference deformation conditions. When the deformation condition changes greatly, the accuracy of J-C model is significantly reduced. The coupling effect of T and ε ˙ of modified J-C model is considered, and the prediction accuracy is greatly improved The Arrhenius model introduces Zener-Hollomon (Z) to represent the coupling effect of T and ε ˙ , it has a fairly high prediction accuracy. And it can predict flow stress (σ) accurately at different conditions. The accuracy of BP-ANN model is the highest, but its learning rate is low, the learning and memory are unstable. It has no memory for the weights and thresholds of the completed training. So, there are certain limitations of it in use. Finally, a Finite Element Method (FEM) of the isothermal compression experiment for four models were established, and the distribution of the equivalent stress field, equivalent strain field and temperature field with the deformation degree of 60% were obtained.

show abstract

Development of Johnson Cook Model for Zircaloy-4 with Low Oxygen Content

Cited by 7 publications

References 10 publications

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel During High Temperature Deformation

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel During High Temperature Deformation

Modelling approach for predicting the superplastic deformation behaviour of titanium alloys with strain hardening/softening characterizations

Comparative Study on Constitutive Models for 21-4N Heat Resistant Steel during High Temperature Deformation

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