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Simulation of Dynamic Recrystallization in 7075 Aluminum Alloy Using Cellular Automaton

  • Metallic Materials
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Abstract

The evolution of microstructure during hot deformation is key to achieving good mechanical properties in aluminum alloys. We have developed a cellular automaton (CA) based model to simulate the microstructural evolution in 7075 aluminum alloy during hot deformation. Isothermal compression tests were conducted to obtain material parameters for 7075 aluminum alloy, leading to the establishment of models for dislocation density, nucleation of recrystallized grains, and grain growth. Integrating these aspects with grain topological deformation, our CA model effectively predicts flow stress, dynamic recrystallization (DRX) volume fraction, and average grain size under diverse deformation conditions. A systematic comparison was made between electron back scattered diffraction (EBSD) maps and CA model simulated under different deformation temperatures (573 to 723 K), strain rates (0.001 to 1 s−1), and strain amounts (30% to 70%). These analyses indicate that large strain, high temperature, and low strain rate facilitate dynamic recrystallization and grain refinement. The results from the CA model show good accuracy and predictive capability, with experimental error within 10%.

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Authors and Affiliations

  1. School of Materials Science and Engineering, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Xiaodong Zhao  (赵晓东), Dongxing Shi, Yajie Li  (李亚杰), Fengming Qin, Zhibing Chu & Xiaorong Yang

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  1. Xiaodong Zhao  (赵晓东)
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  2. Dongxing Shi
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  3. Yajie Li  (李亚杰)
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  4. Fengming Qin
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  5. Zhibing Chu
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  6. Xiaorong Yang
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Corresponding author

Correspondence to Yajie Li  (李亚杰).

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Funded by the Central Government Guides Local Funds for Science and Technology Development (No.YDZJSX20231A045), and the Fundamental Research Program of Shanxi Province (Nos.202103021223288 and 202103021224282)

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Zhao, X., Shi, D., Li, Y. et al. Simulation of Dynamic Recrystallization in 7075 Aluminum Alloy Using Cellular Automaton. J. Wuhan Univ. Technol.-Mat. Sci. Edit. 39, 425–435 (2024). https://doi.org/10.1007/s11595-024-2898-2

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  • DOI: https://doi.org/10.1007/s11595-024-2898-2

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