Modeling material behavior of AA5083 aluminum alloy sheet using biaxial tensile tests and its application in numerical simulation of deep drawing

Prakash, Ved; Kumar, Deepak; Horn, Alexander; Hagenah, Hinnerk; Merklein, Marion

doi:10.1007/s00170-019-04587-0

Cited by 10 publications

(2 citation statements)

References 28 publications

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“…The equivalent strain is determined using Hill's 1948 anisotropic material behavior. To extrapolate the uniaxial stress-strain curve, the biaxial stress strain curve is scaled by a factor obtained from the plastic work principle [16]. The transformed equivalent stress -equivalent strain curve is referred to as HBT-ISO curve in this work.…”

Section: Prediction Of Flow Stress Modelmentioning

confidence: 99%

Deep drawing simulation of dual phase steel using hardening curves and anisotropic parameters from uniaxial and biaxial tensile tests

Shrivastava,

Kumar

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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Among the various factors, the accuracy of the predictions from the numerical simulation of sheet metal forming processes depends on the material model used to define the mechanical behavior of the blank material. The coefficients of the hardening model to define the flow curve and the plastic strain ratios are commonly determined using the uniaxial tensile tests. The advanced anisotropic yield criteria incorporate material flow behaviour and plastic strain ratio in equi-biaxial tension. In this work, deep drawing of a flat bottom cylindrical cup has been simulated using dual-phase steel (DP600) sheets. The biaxial material properties obtained by conducting hydraulic bulge test and cruciform specimen test are used in the anisotropic yield criteria in the simulations. The hardening curves are extrapolated using different hardening laws in which the coefficients are determined from the stress-strain curves obtained from both uniaxial tensile and hydraulic bulge tests. The predicted peak drawing load and thickness variation in the drawn cups are compared with the experimental results of deep drawing.

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Section: Prediction Of Flow Stress Modelmentioning

confidence: 99%

Deep drawing simulation of dual phase steel using hardening curves and anisotropic parameters from uniaxial and biaxial tensile tests

Shrivastava,

Kumar

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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“…Although there is a vast number of constitutive models and equations, its selection for a specific material and process usually requires high expertise, an exhaustive investigation and mechanical experimentation. Most of the authors have been comparing different models with experimental data to determine which is more adequate for a specific material and process mainly based on geometrical measurements [1,[10][11][12][13][14] and stress-strain curves, or load-displacement curves and yield loci [1,[11][12][13][14][15]. Yet, this comparison can be time-consuming since it starts with several mechanical experiments for the identification of different models' parameters, the accurate calibration of the latter and the simulation and validation of the analyzed mechanical process.…”

Section: Introductionmentioning

confidence: 99%

Process-informed material model selection

Conde

2023

Materials Research Proceedings

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Abstract. The efficient development of metal products with high quality usually requires realistic numerical simulations before the manufacturing procedure. The choice of the constitutive model has a considerable influence on the predicted material behavior’s description. Several material constitutive models have been proposed to describe different mechanical phenomena. However, its selection is a labored task that requires expertise. This lack of knowledge can lead to errors in the numerical predictions and, consequently, large costs and delays in the manufacturing procedure. To overcome this problem, an automatic material model selection tool is necessary. This work aims to compare the impact of different constitutive models and their features on the simulation of a forming process and develop a rational and systematic strategy for model selection. The approach focuses on the study of a hole expansion test using Abaqus and a statistical analysis of variance (ANOVA). It was possible to establish a ranking for the importance of the types of models that can help with model selection decision-making and efficient parameter calibration for accurate predictions.

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Experimental and Finite Element-Based Analyses of FLCs for AA5052 and AA5083 Alloys

Shahin

Tathavadkar

Alankar

et al. 2022

The Minerals, Metals &Amp; Materials Series

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Modeling material behavior of AA5083 aluminum alloy sheet using biaxial tensile tests and its application in numerical simulation of deep drawing

Cited by 10 publications

References 28 publications

Deep drawing simulation of dual phase steel using hardening curves and anisotropic parameters from uniaxial and biaxial tensile tests

Deep drawing simulation of dual phase steel using hardening curves and anisotropic parameters from uniaxial and biaxial tensile tests

Process-informed material model selection

Experimental and Finite Element-Based Analyses of FLCs for AA5052 and AA5083 Alloys

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