Numerical Prediction and Reduction of Hat-Shaped Part Springback Made of Dual-Phase AHSS Steel

Mulidrán, Peter; Spišák, Emil; Tomáš, Miroslav; Slota, Ján; Majerníková, Janka

doi:10.3390/met10091119

Cited by 12 publications

(9 citation statements)

References 33 publications

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“…Today it is feasible to use finite element analysis for a more accurate prediction of the springback effect [11,12]. The finite element analysis (FEA) is a modern tool that can help to achieve more accurate springback predictions [13,14]. Several authors conducted experiments and simulations regarding springback investigation.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Material Models in the Fem Simulation on the Springback Prediction of the Trip Steel

Mulidrán

Spišák²,

Tomáš³

et al. 2021

Acta Metall Slovaca

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In this work, the influence of material models used in the FEM simulation on the springback prediction is investigated. The interest of this paper is to extend the knowledge base regarding springback predictions in numerical simulation. The springback effect of a V-shaped sheet metal part made of TRIP steel, with a thickness of 0.75 mm was investigated. The bending angle was set to 90°. In the numerical simulation, Hill48 and Barlat yield criteria were used in combination with Ludwik's and Swift's hardening models. Achieved data from the numerical simulations were compared and evaluated with experimental test results. The experimental results showed the relation between springback and calibration force. The effect of specimen cut direction on the springback was smaller in comparison with the calibration force. The numerical results of the springback were not identical with the experimentally achieved springback values in most cases. Particularly, when a calibration force of 1 800 N was used in the simulation. The simulation results showed a good correlation between experimental and numerical results, when Hill48 and Barlat yield criteria were used in combination with Ludwik hardening law and calibration force F with the value 900 N was applied.

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Section: Introductionmentioning

confidence: 99%

The Effect of Material Models in the Fem Simulation on the Springback Prediction of the Trip Steel

Mulidrán

Spišák²,

Tomáš³

et al. 2021

Acta Metall Slovaca

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“…The numerical results showed that the hardening law has a substantial impact on the results of the bulge test simulation, and thickness prediction of the bulge test specimen. The hardening model describes the development of the plasticity surface during deformation/forming (changes in its size, shape, and/or its displacement) [ 4 ]. The calculations indicate a higher correlation of the Hollomon hardening law with the experimental results when the Hill48 yield criterion is also used in the simulation ( Table 5 and Table 6 ).…”

Section: Discussionmentioning

confidence: 99%

“…Car body weight reduction requirements reduce fuel consumption and thus reduce CO 2 emissions. It is for the above-mentioned reasons that steel sheets with higher strength properties, which are characterized by good plasticity, have been widely used in recent years in the production of car bodies [ 1 , 2 , 3 , 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Experimental and Numerical Thickness Analysis of TRIP Steel under Various Degrees of Deformation in Bulge Test

et al. 2022

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To design a reliable forming process it is necessary to determine the mechanical and formability properties of the processed material, which are used as input parameters for forming simulations. High-strength steel is irreplaceable as a material for producing the deformation zones of current automobiles. This type of steel can be processed by conventional or unconventional forming methods. In the sheet forming process, the material is usually under uniaxial and biaxial stress. The bulge test is utilized for determination of biaxial stress–strain curves, which are often used as input material data for forming simulations. In this work, numerical simulations of bulge tests using TRIP RAK 40/70 steel were performed to study the impact of yield criteria and hardening laws on the accuracy of thickness prediction of the deformed steel sheet. Additionally, the impact of different solvers and integration schemes on the thickness prediction was tested. Furthermore, the impact of various degrees of deformation (various dome heights) on thickness prediction accuracy was evaluated. Numerical results showed a good correlation with experimental data. When the Hill90 yield criterion was used, the software with implicit solver was more accurate in predicting thickness compared to software with explicit integration scheme, in most cases. In addition, the thickness prediction of parts with lower deformation was more accurate compared to parts with greater deformation (higher dome height).

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“…That is why quite a lot of papers deal with the effect of these parameters on the springback prediction. Mulidrán et al [43,44] combined different yield criterions and hardening laws to determine the accuracy of springback prediction, in these cases for DP steel and aluminium alloy AA6451, respectively. Trzepiecinski and Lemu [45] studied the springback behaviour of steel DC04 under the different input parameters (geometry, conditions and material) for FEA (here, Abaqus).…”

Section: Introductionmentioning

confidence: 99%

Effect of the Computational Model and Mesh Strategy on the Springback Prediction of the Sandwich Material

2022

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The effect of the computational model and mesh strategy on the springback prediction of the thin sandwich material made of micro-alloyed steel was investigated in this paper. To verify the chosen computational strategy, a comparison of the experimentally obtained specimen (U-bending) with the FEA result was performed. The Vegter yield criterion combined both with the isotropic and kinematic hardening law was used for the calculation. In addition, the effect of the deformation mesh element (surface and volume) on the accuracy of the springback prediction was investigated. It was concluded that the choice of the volume deformation mesh does not significantly improve the accuracy of the results. Moreover, it is quite a time-consuming approach. The much greater influence was monitored by concerning the selection of hardening law, where the anisotropic one was more suitable to be used on the springback prediction of a given sandwich material.

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Numerical Prediction and Reduction of Hat-Shaped Part Springback Made of Dual-Phase AHSS Steel

Cited by 12 publications

References 33 publications

The Effect of Material Models in the Fem Simulation on the Springback Prediction of the Trip Steel

The Effect of Material Models in the Fem Simulation on the Springback Prediction of the Trip Steel

Experimental and Numerical Thickness Analysis of TRIP Steel under Various Degrees of Deformation in Bulge Test

Effect of the Computational Model and Mesh Strategy on the Springback Prediction of the Sandwich Material

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