Abstract
Dual-phase (DP) steels have received widespread attention for their low density and high strength. This low density is of value to the automotive industry for the weight reduction it offers and the attendant fuel savings and emission reductions. Recent studies on developing DP steels showed that the combination of strength/ductility could be significantly improved when changing the volume fraction and grain size of phases in the microstructure depending on microstructure properties. Consequently, DP steel manufacturers are interested in predicting microstructure properties and in optimizing microstructure design. In this work, a microstructure-based approach using representative volume elements (RVEs) was developed. The approach examined the flow behavior of DP steels using virtual tension tests with an RVE to identify specific mechanical properties. Microstructures with varied martensite and ferrite grain sizes, martensite volume fractions, carbon content, and morphologies were studied in 3D RVE approaches. The effect of these microstructure parameters on a combination of strength/ductility of DP steels was examined numerically using the finite element method by implementing a dislocation density-based elastic-plastic constitutive model, and a Response surface methodology to determine the optimum conditions for a required combination of strength/ductility. The results from the numerical simulations are compared with experimental results found in the literature. The developed methodology proves to be a powerful tool for studying the effect and interaction of key microstructural parameters on strength and ductility and thus can be used to identify optimum microstructural conditions.
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The authors would like to acknowledge the Libyan Ministry of Higher Education and Scientific Research and Mrs. Cassandra Radigan, Educational Program Manager at MSC Software.
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Manuscript submitted March 23, 2017.
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Belgasam, T.M., Zbib, H.M. Microstructure Optimization of Dual-Phase Steels Using a Representative Volume Element and a Response Surface Method: Parametric Study. Metall Mater Trans A 48, 6153–6177 (2017). https://doi.org/10.1007/s11661-017-4351-z
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DOI: https://doi.org/10.1007/s11661-017-4351-z