Estimation of Lankford Coefficients of Austenitic and Ferritic Stainless Steels using Mean Grain Orientations from Micro-texture Measurements

Kodukula, Suresh; Manninen, Timo; Porter, David

doi:10.2355/isijinternational.isijint-2020-256

Cited by 9 publications

(9 citation statements)

References 26 publications

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“…The threshold SF was set as 0.29 when the strain direction is along RD and TD, and as 0.22 for straining 45° to RD. 49) Figure 9 shows that the measured and calculated r-values are in good agreement for both the specimens and all test directions.…”

Section: R-value Calculationmentioning

confidence: 69%

Influence of Micro-texture Distribution and Straining Direction on the Ridging of Ferritic Stainless Steels

2021

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Ridging means the appearance of surface profile undulations, i.e. peaks and valleys, as a result of plastic strain. The reasons for the different ridging behaviour of industrially produced, stabilized ferritic stainless steel sheets (EN 1.4509) have been investigated after straining in the rolling and transverse directions with low and high resistance towards ridging. The evolution of macro-texture has been measured by X-ray diffraction (XRD) both before and after ridging tests in the rolling and transverse directions. The macro texture results showed that straining along the rolling direction strengthened the α fibre whereas the γ fibre was strengthened by grain rotations after straining along transverse direction. Electron backscatter diffraction (EBSD) imaging was used to establish the micro-textural variations over the thickness of the sheets among the high and low ridging materials. Mean orientations of individual grains determined from the EBSD data were utilized to calculate plastic strain ratio r-values by considering all slip systems weighted according to their Schmid factors. The calculated r-values were used to predict the ridging surface profile after straining along the rolling and transverse directions. The results demonstrated the influence of local variations in micro-texture on the severity of ridging.

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Section: R-value Calculationmentioning

confidence: 69%

Influence of Micro-texture Distribution and Straining Direction on the Ridging of Ferritic Stainless Steels

2021

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“…Moreover, the thermomechanical operations experienced by the as-received steel generally produce materials with non-uniform spatial distribution of texture. Indeed, texture gradients of both and texture fibers through thickness were commonly reported in cold-rolled and hot-rolled steel sheets 43 , 51 . As pointed out by Kodukula et al 43 , one of the key reasons for the large discrepancy between measured and calculated r -values of a BCC steel is the strong texture gradient through thickness.…”

Section: Resultsmentioning

confidence: 87%

“…Indeed, texture gradients of both and texture fibers through thickness were commonly reported in cold-rolled and hot-rolled steel sheets 43 , 51 . As pointed out by Kodukula et al 43 , one of the key reasons for the large discrepancy between measured and calculated r -values of a BCC steel is the strong texture gradient through thickness. Increasing the ratio of fiber to fiber can improve the r -value of BCC steel 52 , and this ratio was reported to decrease from the surface to the center of steel sheets 53 .…”

Section: Resultsmentioning

confidence: 87%

“…Unlike the FCC structure of the austenitic steel and aluminum alloy, the BCC structure of the ferritic and martensitic steels has no single family of high-density slip planes, which makes BCC metals generally have more complex plastic deformation than the FCC metals. Many researchers reported the good agreement between the predicted and measured r -values for FCC materials such as aluminum and austenitic steel, but poor for BCC carbon steel, ferritic stainless steel, and dual-phase steel 41 – 43 . Compared with the results obtained from mean-field CP simulations 43 , 44 , the results predicted by the proposed VL show a good agreement with the experimental data, as shown in Figs.…”

Section: Resultsmentioning

confidence: 99%

“…Many researchers reported the good agreement between the predicted and measured r -values for FCC materials such as aluminum and austenitic steel, but poor for BCC carbon steel, ferritic stainless steel, and dual-phase steel 41 – 43 . Compared with the results obtained from mean-field CP simulations 43 , 44 , the results predicted by the proposed VL show a good agreement with the experimental data, as shown in Figs. 8 and 9 .…”

Section: Resultsmentioning

confidence: 99%

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A virtual laboratory based on full-field crystal plasticity simulation to characterize the multiscale mechanical properties of AHSS

Zhang

et al. 2022

Sci Rep

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In this work, we proposed a virtual laboratory based on full-field crystal plasticity (CP) simulation to track plastic anisotropy and to calibrate yield functions for multiphase metals. The virtual laboratory, minimally, only requires easily accessible EBSD data for constructing the highly-resolved microstructural representative volume element and macroscopic flow stress data for identifying the micromechanical parameters of constituent phases. An inverse simulation method based on a global optimization scheme was developed to identify the CP parameters, and a nonlinear least-squares method was employed to calibrate yield functions. Mechanical tests of advanced high strength steel sheet under various loading conditions were conducted to validate the virtual laboratory. Three well-known yield functions, the quadratic Hill48 and non-quadratic Yld91 and Yld2004-18p yield functions, were selected as the validation benchmarks. All the studied functions, calibrated by numerous stress points of arbitrary loading conditions, successfully captured both the deformation and strength anisotropies. The full-field CP modeling correlated well the microscopic deformation mechanism and plastic heterogeneity with the macromechanical behavior of the sheet. The proposed virtual laboratory, which is readily extended with physically based CP models, could be a versatile tool to explore and predict the mechanical property and plastic anisotropy of advanced multiphase materials.

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A study on the parametric optimization of drawing metal stamping process for aluminum alloy tailgate parts using response surface methodology

Kim

Lee

2023

Materialwissenschaft Werkst

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The tailgate‐extension in a vehicle is a part that connects the upper and lower parts of the tailgate. Since this part does not require high strength, aluminum must be used in order to reduce the weight of the vehicle. However, when choosing aluminum, it is difficult to satisfy the shape quality with the existing manufacturing process. Therefore, this study was conducted for the purpose of optimizing the draw metal stamping process for the development of tailgate extensions for vehicles using aluminum. The response surface methodology was utilized to optimize the draw metal stamping process. The process design parameters were established as blank holding force, coefficient of friction and die speed. Finally, the reliability of the optimization process and finite element analysis was secured by conducting field experiments to review the derived optimal process conditions.

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Estimation of Lankford Coefficients of Austenitic and Ferritic Stainless Steels using Mean Grain Orientations from Micro-texture Measurements

Cited by 9 publications

References 26 publications

Influence of Micro-texture Distribution and Straining Direction on the Ridging of Ferritic Stainless Steels

Influence of Micro-texture Distribution and Straining Direction on the Ridging of Ferritic Stainless Steels

A virtual laboratory based on full-field crystal plasticity simulation to characterize the multiscale mechanical properties of AHSS

A study on the parametric optimization of drawing metal stamping process for aluminum alloy tailgate parts using response surface methodology

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