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

Abstract

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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“…However, the results of the analysis and discussion with several respondents revealed that there is still a need for teachers and lecturers to be given training on the product development process, in particular for the virtual science laboratory, so they can minimize the difficulties encountered in the development of learning products. According to Ma et al (2022), virtual laboratories are easily accessible and become a versatile tool for advanced students. Then in testing the research by Sriadhi et al (2019) shows high feasibility in design, representation of user needs, reliability, system security, and ease of use.…”

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“…Today's fast progress in alloy design is stipulated by powerful computational tools using theoretical assessments and empirical statistical data to predict various physical phenomena determining the structure and properties of alloys. [44][45][46] Understanding interconnections between chemical composition, microstructure, and materials processing technology is crucial in their properties improving. The knowledge of phase formation order at various temperatures and elements' content helps to improve the melting routes and overcome potential problems during their manufacturing and applications.…”