Finite element simulation of sheet forming based on a planar anisotropic strain-rate potential

Chung, Kwansoo; Lee, S.Y.; Barlat, Frédéric; Keum, Y.T.; Park, J.M.

doi:10.1016/s0749-6419(95)00046-1

Cited by 71 publications

(33 citation statements)

References 18 publications

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“…Bourne and Hill [37] observed that the angular positions, α, of the ears of various mild steel sheets correspond to the maxima of r(π/2-α) and to the minima of σ(π/2-α). Hosford and Caddell [38] and Chung et al [24] provided a quantitative trend between r-value anisotropy and possible earing profiles in a mild steel and an aluminum alloy, respectively. In a different approach, Barlat et al [22,39] attempted to correlate the yield stress anisotropy (not r-values) to the earing trends.…”

Section: Introductionmentioning

confidence: 99%

“…In a different approach, Barlat et al [22,39] attempted to correlate the yield stress anisotropy (not r-values) to the earing trends. More quantitative evaluations of the cup heights have been proposed by Yoon et al [11], based on an analytical approach considering the r-value directionality as a main contributor to the earing profile derived from the work of Chung et al [24].…”

Section: Introductionmentioning

confidence: 99%

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Numerical simulation of sheet metal forming using anisotropic strain-rate potentials

Rabahallah¹,

Bouvier²,

Balan³

et al. 2009

Materials Science and Engineering: A

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For numerical simulation of sheet metal forming, more and more advanced phenomenological functions are used to model the anisotropic yielding. The latter can be described by an adjustment of the coefficients of the yield function or the strain rate potential to the polycrystalline yield surface determined using crystal plasticity and X-ray measurements. Several strain rate potentials were examined by the present authors and compared in order to analyse their ability to model the anisotropic behaviour of materials using the methods described above to determine the material parameters. Following that, a specific elastic-plastic time integration scheme was developed and the strain rate potentials were implemented in the FE code. Comparison of the previously investigated potentials is continued in this paper in terms of numerical predictions of cup drawing, for different bcc and fcc materials. The identification procedure is shown to have an important impact on the accuracy of the FE predictions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical simulation of sheet metal forming using anisotropic strain-rate potentials

Rabahallah¹,

Bouvier²,

Balan³

et al. 2009

Materials Science and Engineering: A

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“…The normalized yield stresses and r-values (either experimentally (AA 2090-T3) determined or obtained from Taylor method (DC06)) are presented in Tables 1 and 2, respectively. The experimental data for AA2090-T3 are given in (Chung et al, 1996; for details at Yoon et al, 2000). Parameter identification was performed using an inverse approach and the technique presented in the work of Yoon et al (2004).…”

Section: Prediction Of Anisotropymentioning

confidence: 99%

Study on the definition of equivalent plastic strain under non-associated flow rule for finite element formulation

Safaei

Yoon

Waele

2014

International Journal of Plasticity

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a b s t r a c tAs opposed to associated flow rule (AFR) in which yield function and plastic potential are equal, the different definitions for them is an inherent characteristic of non-associated flow rule (non-AFR). This imposes a specific relation (but not equality) between equivalent plastic strain and plastic compliance factor. Unavoidably, this leads to a laborious effort for FE implementation of non-associated constitutive model specifically when several internal variables (such as kinematic hardening or damage parameters) are involved. This paper is mainly devoted to studying the conditions at which the non-AFR approach can be simplified so that the numerical implementation scheme is more convenient without loss of accuracy. It will be shown that by scaling the plastic potential function, the equality of equivalent plastic strain and compliance factor can be reserved. The effect of scaling of the non-AFR based on Barlat et al.'s (2003) anisotropic model (called Yld2000-2d) is comprehensively studied with FE simulation of tensile loading under uniaxial tensions along the different orientations as well as balanced biaxial stress condition. A fully implicit return-mapping scheme was introduced for stress integration of the constitutive model in a User-defined MATerial subroutine (UMAT). Cup drawing simulations of a highly textured aluminum alloy 2090-T3 were performed using simplified and original approaches. The results prove that the proposed simplified technique is a reliable alternative for the full expression.

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“…However, the reliability of these simulations, mostly performed using the finite element (FE) method, is closely linked to the accuracy of the constitutive laws employed to describe the plastic behavior of the stamped material [2]. The most popular experimental test used to characterize sheet metal plastic anisotropy is the uniaxial tensile test performed along the directions at 0°, 45° and 90° from the rolling direction.…”

Section: Introductionmentioning

confidence: 99%

Mixed experimental-numerical analysis for identifying sheet-metal anisotropic yield surfaces

Teaca¹,

Charpentier²,

Martiny³

et al. 2009

Int J Mater Form

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The plastic behavior of anisotropic sheet steels and aluminum alloys is identified by combining the results of classical uniaxial tensile tests and of heterogeneous biaxial tensile tests on cruciform specimens. The 8-parameter anisotropic yield function proposed by Ferron et al.[1] is used to this end. Uniaxial tensile tests allow the identification of strain-hardening and of yield function parameters related to transverse strain anisotropy (angular variation of the anisotropy coefficient R) and stress anisotropy (angular evolution of the yield stress σ ). Strain fields measured in the biaxial tests by means of an image correlation method are used as input data in an optimization procedure that consists of fitting numerical fields with experimental ones, in order to determine the material parameters describing the shape of the yield surface in the expansion range. Finally, simulations of the cup drawing test are performed to check the validity of the identification.

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Finite element simulation of sheet forming based on a planar anisotropic strain-rate potential

Cited by 71 publications

References 18 publications

Numerical simulation of sheet metal forming using anisotropic strain-rate potentials

Numerical simulation of sheet metal forming using anisotropic strain-rate potentials

Study on the definition of equivalent plastic strain under non-associated flow rule for finite element formulation

Mixed experimental-numerical analysis for identifying sheet-metal anisotropic yield surfaces

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