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Simulating the deformation and recrystallization of aluminum bicrystals

    Research output: Contribution to journalArticlepeer-review

    13 Scopus citations

    Abstract

    To understand the formation of the deformation substructure and its evolution during annealing to produce unique microstructures and textures in aluminum alloys, the development and coupling of physically based models spanning different length scales is necessary. Under hot deformation conditions, the deformation substructure is a collection of cells/subgrains of different sizes and orientations. Recrystallization following hot deformation occurs by the heterogeneous evolution of the subgrain structure, the kinetics of which is controlled by variations in driving forces and boundary properties at the microstructural length scale. This article describes a mesoscale approach for modeling the microstructure and texture evolution during recrystallization following hot deformation. A Monte Carlo simulation technique is used to evolve the substructure and texture during recrystallization. The simulations are applied to the deformation and recrystallization of aluminum bicrystals with specific combinations of crystallographic orientations. The simulation result are compared with experimental results.

    Original languageEnglish
    Pages (from-to)55-62
    Number of pages8
    JournalJOM
    Volume56
    Issue number4
    DOIs
    StatePublished - Apr 2004

    Funding

    Science and Engineering, U.S. Department of Energy, under contract DE-AC05-00OR22725 with UT-Battelle, LLC. The submitted manuscript has been authored by a contractor of the U.S. Government under contract No. DE-AC05-00OR22725. Accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes. This research is sponsored by the Division of Materials Sciences and Engineering, U.S. Department of Energy (DOE), under contract DE-AC05- 00OR22725 with UT-Battelle, LLC. The authors also acknowledge the collaboration/coordination supported by the Computational Materials Science Network, a program of the DOE Office of Science.

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