A Numerical Model for the Prediction of Microstructure Distribution across the Thickness of Quenched Steel Plates

Abstract:

In this work we apply a numerical inverse analysis procedure based on the ICME framework to ensure a required microstructure and combination of properties in the quenched plate. The microstructure is decided first, and the cooling profile needed to obtain such microstructure is then calculated using the CALPHAD approach. Subsequently, an inverse analysis of the heat transfer problem provides the description of the convection mechanism in quenching that results in the demanded cooling profile. An additional constraint is set on the through-thickness thermal gradient to achieve a homogeneous microstructure. Finally, the resultant microstructure is computed. By means of the proposed model we are able to retrieve the necessary quenching process parameters and to quantify the influence of these parameters on the temperature and microstructure distribution within the plate after the quenching.

• Periodical: Materials Science Forum (Volume 949)
• Pages: 32-39
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.949.32
• Online since: March 2019
• Authors: Jerzy Gawad, Ilaria Iaconeta, Sai Pavan Bhogireddy, Philippe Hernaut, Aleksandr Lebedev, Gijsbert Wierink, Bruno Charles de Cooman
• Keywords: Inverse Analysis, Material Property Optimization, Numerical Simulation, Plate Quenching

References

[1] Rajeev PT, jin L, Farris TN, Chandrasekar S, Modeling of Q&T Indiced Phase Transformations in Steels, Journal of ASTM International 6, 1-19 (2009).

DOI: 10.1520/jai102095

[2] Jin L. Simulation of Q&T steels, Purdue University, (2001).

[3] Xiaohu Deng, Dongying Ju, Modeling and Simulation of Quenching and Tempering Process in steels, Physics Procedia, pp.368-374 (2013).

DOI: 10.1016/j.phpro.2013.11.057

[4] EN10025-6 Technical delivery conditions for flat products of high yield strength structural steels in the quenched and tempered condition.

DOI: 10.3403/03153116

[5] JMatPro, available on http://www.sentesoftware.co.uk.

[6] J. F. Banka, Z. Li, B. L. Ferguson, and M. Aronov, CFD and FEA Used to Improve the Quenching Process, Heat Treating Progress, 2008, p.50–56.

[7] M. N. Özisik and H.R.B. Orlande, Inverse heat transfer fundamentals and applications, Taylor and Francis, New York, (2000).

[8] M. J. Colaço, H. R. B. Orlande and G. S. Dulikravich, Inverse and Optimization Problems in Heat Transfer, J. of the Braz. Soc. of Mech. Sci. & Eng., 28, No.1, (2006).

DOI: 10.1590/s1678-58782006000100001

[9] O.C. Zienkiewicz and R.L. Taylor and J.Z. Zhu, The Finite Element Method: its Basis and Fundamentals, Butterworth-Heinemann, Oxford, (2013).

[10] Ansys Mechanical User Manual, ver. 19.1 (2017).

[11] E. Acar, Various Approaches for Constructing an Ensemble of Metamodels Using Local Measure, Struct. Multidisc. Opti., 42, No. 6, 2010, pp.879-896.

DOI: 10.1007/s00158-010-0520-z

[12] Ansys DesignXplorer User Reference Manual (2018).

[13] K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II". IEEE Transactions on Evolutionary Computation. 6 (2002) 182.

DOI: 10.1109/4235.996017

[14] NLMK Clabecq internal report (2015).