Low Cycle Fatigue Behaviour of DP Steels: Micromechanical Modelling vs. Validation

Moeini, Ghazal; Ramazani, Ali; Myslicki, Sebastian; Sundararaghavan, Veera; Könke, Carsten

doi:10.3390/met7070265

Cited by 10 publications

(9 citation statements)

References 49 publications

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“…They used these kinematic approaches to simulate the micromechanical behavior of the selected material. Moeini et al [17] used the Chaboche model [5] to predict the low cyclic behavior of dual-phase steel. The selected kinematic hardening model provided good agreement with experimental results.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Strain-Range Dependent Cyclic Hardening of SS304 and 08Ch18N10T Stainless Steel with a Memory Surface

Halama

Fumfera

Gál

et al. 2019

Metals

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This paper deals with the development of a cyclic plasticity model suitable for predicting the strain range dependent behavior of austenitic steels. The proposed cyclic plasticity model uses the virtual back-stress variable corresponding to a cyclically stable material under strain control. This new internal variable is defined by means of a memory surface introduced in the stress space. The linear isotropic hardening rule is also superposed. First, the proposed model was validated on experimental data published for the SS304 material (Kang et al. Constitutive modeling of strain range dependent cyclic hardening. Int J Plast 19 (2003) 1801–1819). Subsequently, the proposed cyclic plasticity model was applied to own experimental data from uniaxial tests realized on 08Ch18N10T at room temperature. The new cyclic plasticity model can be calibrated by the relatively simple fitting procedure that is described in the paper. A comparison between the results of a numerical simulation and the results of real experiments demonstrates the robustness of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Modeling the Strain-Range Dependent Cyclic Hardening of SS304 and 08Ch18N10T Stainless Steel with a Memory Surface

Halama

Fumfera

Gál

et al. 2019

Metals

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“…Moeini et al [32,33] used the Chaboche material model to predict the micromechanical response in dual phase (DP) steels and identified material parameters with three back stress terms leading to the conclusion that strain accumulates in soft ferrite. They further used a 2D representative volume element (RVE) to predict the LCF behaviour of DP steels using micromechanical modelling.…”

Section: Introductionmentioning

confidence: 99%

Modelling Cyclic Behaviour of Martensitic Steel with J2 Plasticity and Crystal Plasticity

et al. 2019

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In order to capture the stress-strain response of metallic materials under cyclic loading, it is necessary to consider the cyclic hardening behaviour in the constitutive model. Among different cyclic hardening approaches available in the literature, the Chaboche model proves to be very efficient and convenient to model the kinematic hardening and ratcheting behaviour of materials observed during cyclic loading. The purpose of this study is to determine the material parameters of the Chaboche kinematic hardening material model by using isotropic J2 plasticity and micromechanical crystal plasticity (CP) models as constitutive rules in finite element modelling. As model material, we chose a martensitic steel with a very fine microstructure. Thus, it is possible to compare the quality of description between the simpler J2 plasticity and more complex micromechanical material models. The quality of the results is rated based on the quantitative comparison between experimental and numerical stress-strain hysteresis curves for a rather wide range of loading amplitudes. It is seen that the ratcheting effect is captured well by both approaches. Furthermore, the results show that concerning macroscopic properties, J2 plasticity and CP are equally suited to describe cyclic plasticity. However, J2 plasticity is computationally less expensive whereas CP finite element analysis provides insight into local stresses and plastic strains on the microstructural length scale. With this study, we show that a consistent material description on the microstructural and the macroscopic scale is possible, which will enable future scale-bridging applications, by combining both constitutive rules within one single finite element model.

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“…The Yld2000-2d yield function [6] has eight parameters (α [1][2][3][4][5][6][7][8] ) that require eight mechanical properties (σ 0 , σ 45 , σ 90 , σ b , r 0 , r 45 , r 90 , r b ). The m value is suggested as six for BCC and eight for FCC metal.…”

Section: Appendix Amentioning

confidence: 99%

“…In this work, we investigate the application of advanced high-strength steels (AHSSs), with good strength and formability, in automotive parts. The demand for automotive parts made of AHSSs is based on their excellent impact resistance, which is an asset for the reinforcement of the car body structure, and which depends on their high strength [3][4][5][6][7]. However, along with their high strength and low thickness, the AHSSs exhibit anisotropic properties and large springback recovery after forming [8,9].…”

Section: Introductionmentioning

confidence: 99%

Anisotropic Hardening Behaviour and Springback of Advanced High-Strength Steels

Jung

Jun

Lee³

et al. 2017

Metals

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Advanced high-strength steels (AHSSs) exhibit large, and sometimes anisotropic, springback recovery after forming. Accurate description of the anisotropic elasto-plastic behaviour of sheet metals is critical for predicting their anisotropic springback behaviour. For some materials, the initial anisotropy is maintained while hardening progresses. However, for other materials, anisotropy changes with hardening. In this work, to account for the evolution of anisotropy of a dual-phase steel, an elastoplastic material constitutive model is developed. In particular, the combined isotropic-kinematic hardening model was modified. Tensile loading-unloading, uniaxial and biaxial tension, and tension-compression tests were conducted along the rolling, diagonal, and transverse directions to measure the anisotropic properties, and the parameters of the proposed constitutive model were determined. For validation, the proposed model was applied to a U-bending process, and the measured springback angles were compared to the predicted ones.

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Low Cycle Fatigue Behaviour of DP Steels: Micromechanical Modelling vs. Validation

Cited by 10 publications

References 49 publications

Modeling the Strain-Range Dependent Cyclic Hardening of SS304 and 08Ch18N10T Stainless Steel with a Memory Surface

Modeling the Strain-Range Dependent Cyclic Hardening of SS304 and 08Ch18N10T Stainless Steel with a Memory Surface

Modelling Cyclic Behaviour of Martensitic Steel with J2 Plasticity and Crystal Plasticity

Anisotropic Hardening Behaviour and Springback of Advanced High-Strength Steels

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