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Prediction of microstructure evolution during hot forging using grain aggregate model for dynamic recrystallization

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Abstract

In this study, dynamic recrystallization during nonisothermal hot compression test was numerically simulated by finite element analysis using new grain aggregate model for dynamic recrystallization. This model was developed based on mean field approach by assuming grain aggregate as representative element. For each grain aggregate, changes of state variables were calculated using three sub-models for work hardening, nucleation, and nucleus growth. A conventional single parameter dislocation density model was used to calculate change of dislocation density in grains. For modeling nucleation, constant nucleation rate and nucleation criterion developed by Roberts and Ahlblom were used. It was assumed that the nucleation occurs when the dislocation density of certain grain reaches a critical nucleation criterion. Conventional rate theory was used to model nucleus growth. The developed dynamic recrystallization model was validated by comparing with isothermal hot compression of pure copper. Then, the finite element analysis was conducted to predict the local changes of microstructure and average grain size by using the grain aggregate model. The predicted results were compared with nonisothermal hot compression results. The simulation results were in reasonably good agreement with experimentally obtained microstructures and the calculation time was much shorter than cellular automata-finite element method.

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Authors and Affiliations

  1. Materials Deformation Department, Korea Institute of Materials Science, 797 Changwondaero, Seongsan-gu, Changwon, South Korea, 642-831

    Ho Won Lee, Seong-Hoon Kang & Youngseon Lee

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  1. Ho Won Lee
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  2. Seong-Hoon Kang
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  3. Youngseon Lee
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Correspondence to Seong-Hoon Kang.

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Lee, H.W., Kang, SH. & Lee, Y. Prediction of microstructure evolution during hot forging using grain aggregate model for dynamic recrystallization. Int. J. Precis. Eng. Manuf. 15, 1055–1062 (2014). https://doi.org/10.1007/s12541-014-0436-4

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  • DOI: https://doi.org/10.1007/s12541-014-0436-4

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