Simple shear tests: Experimental techniques and characterization of the plastic anisotropy of rolled sheets at large strains

Bouvier, Salima; Haddadi, H.; Levée, P.; Teodosiu, Cristian

doi:10.1016/j.jmatprotec.2005.09.003

Cited by 189 publications

(111 citation statements)

References 9 publications

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“…To characterize the behaviour of deep drawing quality metals, the most widely experimental tests used are tensile, shear and equibiaxial tensile tests. In case of constitutive laws involving kinematic hardening, reverse strain paths have to be taken into account, such as tension-compression tests [30], bending-unbending tests [31,32] or planar Bauschinger shear tests [33,34]. The mechanical behaviour of a material is then modelled, for use in numerical simulations of the forming process, by means of the parameters identified from the available experimental data.…”

Section: Parameter Identificationmentioning

confidence: 99%

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Chaparro¹,

Thuillier²,

Menezes³

et al. 2008

Computational Materials Science

194

102

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a b s t r a c tThis paper presents two procedures for the identification of material parameters, a genetic algorithm and a gradient-based algorithm. These algorithms enable both the yield criterion and the work hardening parameters to be identified. A hybrid algorithm is also used, which is a combination of the former two, in such a way that the result of the genetic algorithm is considered as the initial values for the gradient-based algorithm. The objective of this approach is to improve the performance of the gradient-based algorithm, which is strongly dependent on the initial set of results. The constitutive model used to compare the three different optimization schemes uses the Barlat'91 yield criterion, an isotropic Voce type law and a kinematic Lemaitre and Chaboche law, which is suitable for the case of aluminium alloys. In order to analyse the effectiveness of this optimization procedure, numerical and experimental results for an EN AW-5754 aluminium alloy are compared.

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Section: Parameter Identificationmentioning

confidence: 99%

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Chaparro¹,

Thuillier²,

Menezes³

et al. 2008

Computational Materials Science

194

102

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“…During a simple shear test, studied for instance by Bouvier et al (2005), the shear component ζ 12 is not alone, both σ 11 and ζ 22 components are non-negligible (see Fig. 5).…”

Section: Introductionmentioning

confidence: 99%

Model identification and FE simulations: Effect of different yield loci and hardening laws in sheet forming

Flores

Duchêne

Bouffioux

et al. 2007

International Journal of Plasticity

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“…The dimensions of foam specimen are 75×30×40 mm 3 in length, height and depth, respectively. These dimensions do not guarantee pure shear test as mentioned by Bouvier et al [10]. Indeed, some flexural phenomena occur at both side of the specimen and can not be neglected.…”

Section: Discussion About Specimen Dimensionsmentioning

confidence: 92%

Multiaxial behavior of foams – Experiments and modeling

Mahéo

Guérard

Rio

et al. 2015

EPJ Web of Conferences

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Abstract. Cellular materials are strongly related to pressure level inside the material. It is therefore important to use experiments which can highlight (i) the pressure-volume behavior, (ii) the shear-shape behavior for different pressure level. Authors propose to use hydrostatic compressive, shear and combined pressure-shear tests to determine cellular materials behavior. Finite Element Modeling must take into account these behavior specificities. Authors chose to use a behavior law with a Hyperelastic, a Viscous and a Hysteretic contributions. Specific developments has been performed on the Hyperelastic one by separating the spherical and the deviatoric part to take into account volume change and shape change characteristics of cellular materials.

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Simple shear tests: Experimental techniques and characterization of the plastic anisotropy of rolled sheets at large strains

Cited by 189 publications

References 9 publications

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Model identification and FE simulations: Effect of different yield loci and hardening laws in sheet forming

Multiaxial behavior of foams – Experiments and modeling

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