2016
DOI: 10.1590/1679-78252916
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Parameters Determination of Yoshida Uemori Model Through Optimization Process of Cyclic Tension-Compression Test and V-Bending Springback

Abstract: In recent years, the studies on the enhancement of the prediction capability of the sheet metal forming simulations have increased remarkably. Among the used models in the finite element simulations, the yield criteria and hardening models have a great importance for the prediction of the formability and springback. The required model parameters are determined by using the several test results, i.e. tensile, compression, biaxial stretching tests (bulge test) and cyclic tests (tension-compression). In this stud… Show more

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Cited by 12 publications
(7 citation statements)
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References 29 publications
(22 reference statements)
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“…Elastic deformation occurs if the yield function f(σ , x, p) < 0, while the plastic flow takes place for f = 0 [28,29]. The effective plastic strain is described by the following formula (2) [30]:…”
Section: Combined Hardening: Problem Formulationmentioning
confidence: 99%
“…Elastic deformation occurs if the yield function f(σ , x, p) < 0, while the plastic flow takes place for f = 0 [28,29]. The effective plastic strain is described by the following formula (2) [30]:…”
Section: Combined Hardening: Problem Formulationmentioning
confidence: 99%
“…Based on the Bron-Besson yield function and the Y-U hardening model, the anisotropy hardening behavior of mild steel DC04 and dual phase steel DP500 is described with work-hardening stagnation in the reversed strain path [7]. A sequential response surface built on the Y-U hardening model by Toros et al [8] showed the same high accuracy in the cyclic stress-strain of several aluminum alloys. In different combinations of yield functions and hardening models, the Y-U hardening model predicts the U-bending springback of DP780 steel with a higher accuracy [9].…”
Section: Introductionmentioning
confidence: 98%
“…Here, the proposed two surface plasticity model by Yoshida et al [6] combines the strain dependent change of Young's modulus, the kinematic hardening, transient softening and the Bauschinger effect. This model improves accuracy of springback prediction, but the parameter identification requires an increased testing and determining effort [7].…”
Section: Introductionmentioning
confidence: 99%