The modeling scheme to evaluate the influence of microstructure features on microcrack formation of DP-steel: The artificial microstructure model and its application to …
N Vajragupta, P Wechsuwanmanee, J Lian… - Computational materials …, 2014 - Elsevier
Computational materials science, 2014•Elsevier
Due to the existence of constituents with strong distinction in mechanical properties, dual
phase steels exhibit remarkably high-energy absorption along with excellent combination of
strength and ductility. Furthermore, these constituents also affect deformation and
microcrack formation in which various mechanisms can be observed. Thus, a reliable
microstructure-based simulation approach for describing these deformations and microcrack
initiation is needed. Under this framework of modeling scheme development, several work …
phase steels exhibit remarkably high-energy absorption along with excellent combination of
strength and ductility. Furthermore, these constituents also affect deformation and
microcrack formation in which various mechanisms can be observed. Thus, a reliable
microstructure-based simulation approach for describing these deformations and microcrack
initiation is needed. Under this framework of modeling scheme development, several work …
Abstract
Due to the existence of constituents with strong distinction in mechanical properties, dual phase steels exhibit remarkably high-energy absorption along with excellent combination of strength and ductility. Furthermore, these constituents also affect deformation and microcrack formation in which various mechanisms can be observed. Thus, a reliable microstructure-based simulation approach for describing these deformations and microcrack initiation is needed. Under this framework of modeling scheme development, several work packages have been carried out. These work packages includes algorithm to generate the artificial microstructure model, a procedure to derive plasticity parameters for each constituent, and characterization of the microcrack formation and initiation criteria determination. However, due to the complexity of topic and in order to describe each work package in detail, this paper focused only on the approach to generate the artificial microstructure model and its application to predict the strain hardening behavior. The approach was based on the quantitative results of metallographic microstructure analysis and their statistical representation. The dual phase steel was first characterized by EBSD analysis to identify individual phase grain size distribution functions. The results were then input into a multiplicatively weighted Voronoi tessellation based algorithm to generate artificial microstructure geometry models. Afterwards, nanoindentation was performed to calibrate crystal plasticity parameters of ferrite and empirical approach based on local chemical composition was used to approximate flow curve of martensite. By assigning the artificial microstructure model with plasticity description of each constituent, strain-hardening behavior of DP-steel was then predicted.
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