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Can I read Relating Martensite variant selection with prior austenite microstructure: A coupled study of experiments and pixel-by-pixel reconstruction on EtoBox?
Relating Martensite variant selection with prior austenite microstructure: A coupled study of experiments and pixel-by-pixel reconstruction by S. Kumar; S. Manda; S.K. Giri; S. Kundu; S. Karagadde; R. Balamuralikrishnan; S.V.S.N. Murty; C.R. Anoop; I. Samajdar is a Engineering article available to read on EtoBox.
What is Relating Martensite variant selection with prior austenite microstructure: A coupled study of experiments and pixel-by-pixel reconstruction about?
A high strength low alloy (HSLA) steel was subjected to uniaxial compression followed by controlled cooling. These experiments, conducted in the austenite (γ) phase with a thermomechanical simulator, provided samples with differences in mechanical behavior. The mechanical anisotropy, in particular, originated from the variant selection and texturing in the martensite phase. It was hence decided to explore the origin of variant selection through careful pixel-by-pixel reconstruction of the parent γ. Three parameters of reconstructed prior austenite (γ) grains (grain size (dγ), transformation strain (Tγ), and grain average misorientation (GAMγ)) were related to the statistical measures of variant selection, quantified as number of variants (Nv) and variant selection index(VSI). Regression analysis plus artificial neural network were then used, along with a statistical (first-order variance based) sensitivity analysis. It was shown, with ∼640 randomly selected reconstructed γ grains, that the variant selection was dominated, phenomenologically but statistically, by dγ and Tγ. GAMγ appeared to have a relatively insignificant effect.
Who reads Relating Martensite variant selection with prior austenite microstructure: A coupled study of experiments and pixel-by-pixel reconstruction?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- S. Kumar; S. Manda; S.K. Giri; S. Kundu; S. Karagadde; R. Balamuralikrishnan; S.V.S.N. Murty; C.R. Anoop; I. Samajdar
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Engineering (Physical Sciences)