4.5 Article

Micromechanical Modeling of Strain-Hardening Behavior in Dual-Phase Steels

Journal

STEEL RESEARCH INTERNATIONAL
Volume 94, Issue 8, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/srin.202300141

Keywords

dual-phase steels; flow stress; micromechanical modeling; strain-hardening rate

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In this study, a mathematical model is developed to investigate the influence of microstructural parameters on the flow stress and strain-hardening behavior of dual-phase microstructure. The model takes into account the volume fraction and average particle size of martensite, as well as other factors such as martensite carbon content, geometrically necessary dislocations, and strain accommodation at the ferrite-martensite interface. The proposed model shows good predictive capabilities and can identify strain-hardening stages and estimate the inverse of the strain-hardening exponent.
A mathematical model is developed to consider the impact of microstructural parameters, including the volume fraction and the average particle size of martensite, on the flow stress and strain-hardening behavior of dual-phase microstructure. In this regard, the micromechanical approach is applied for partitioning the stress and strain in ferrite and martensite. Martensite carbon content and geometrically necessary dislocations, generated from austenite-to-martensite transformation, and strain accommodation at the ferrite-martensite interface, are involved to modify the partitioned stress of martensite and ferrite, respectively. Having partitioned stress in each phase, the global stress is estimated as the function of steel chemical composition, ferrite grain size, martensite particle size, aspect ratio, and volume fraction. To evaluate the applicability of the proposed model, four dual-phase steels containing 12, 25, 34, and 48% volume fractions of martensite are prepared from the intermediate quenching process, and then after the strain-hardening stages are investigated. Comparing the experimental result and model output reveals that the presented model shows good predictive capabilities to identify strain-hardening stages and estimate the inverse of the strain-hardening exponent.

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