A novel cellular automaton for simulating static recrystallization of aluminum alloys incorporating both solute drag and particle effects

Ruxue Liu; Zhiwu Zhang; Guowei Zhou; Zhihong Jia; Dongnan Huang; Dayong Li

doi:10.1007/s40436-025-00578-5

Advances in Manufacturing ›› :1 -24. DOI: 10.1007/s40436-025-00578-5

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A novel cellular automaton for simulating static recrystallization of aluminum alloys incorporating both solute drag and particle effects

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¹Department of Structural Materials, Suzhou Laboratory, 215123, Suzhou, China

²State Key Laboratory of Mechanical Systems and Vibration, Shanghai Jiao Tong University, 200240, Shanghai, China

³School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China

⁴Key Laboratory for Light-weight Materials, Nanjing Tech University, 210009, Nanjing, China

⁵, Chinalco Materials Application Research Institute Co., Ltd, 102209, Beijing, China

^a dongnan_2000@163.com

^b dyli@sjtu.edu.cn

Ruxue Liu

Ruxue Liu Doctor, Assistant Research Fellow in Department of Structural Materials, Suzhou Laboratory, Suzhou, China. He received a Ph.D. degree in Mechanical Engineering from Shanghai Jiao Tong University in 2025. His main research interest focuses on the multi-scale modeling of hot forming process for aluminum alloys.

Zhiwu Zhang

Zhiwu Zhang Doctor degree candidate in School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. His main research interest focuses on the extrusion process for aluminum alloys.

Guowei Zhou

Guowei Zhou Doctor, Associate Professor, Doctoral Supervisor in School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, China. He received a Ph.D. degree in Mechanical Engineering from Shanghai Jiao Tong University in 2016. The main research interests include modeling crystal plasticity in metallic materials, mechanical multiscale modeling of material deformation behavior and data-driven material modeling.

Zhihong Jia

Zhihong Jia Doctor, Professor, Doctoral Supervisor in Advanced Lightweight and High-Performance Materials Research Center, Nanjing Tech University, Nanjing, China. The main research interests include basic and applied research on high-performance aluminum alloys for automotive and aerospace applications, correlation between microstructure and properties, advanced electron microscopy techniques.

Dongnan Huang

Dongnan Huang Professor, Special (Chief) Researcher of Chinalco Group, Chinalco Materials Application Research Institute Co., LTD, Beijing, China. The main research interests include the development of simulation software for the preparation and processing of non-ferrous metal materials, industrial big data modeling technology, and the construction of decision-making systems for intelligent manufacturing equipment.

Dayong Li

Dayong Li Doctor, Professor, Doctoral Supervisor in School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. He received a Ph.D. degree in Mechanical Engineering from Jilin University of Technology in 2000. The main research interests include elastic-plastic finite element method, CAD/CAE techniques in mechanical design and forming process and plastic forming theory and simulation technology.

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Abstract

Microstructure and mechanical properties of aluminum alloys evolve sensitively with containing solute and second-phase particles as well as temperature variation during post-deformation annealing process. In this paper, a novel cellular automaton-based static recrystallization model for aluminum alloys was developed, which incorporated both the solute drag and double-edge effects of second-phase particles, namely particle-stimulated nucleation and Smith–Zener pinning resistance. By integrating both oriented nucleation and oriented growth theories, the orientations of recrystallized nuclei have been determined probabilistically in this model. The recrystallization behaviors and microstructure evolution of cold-rolled Al-Mn alloys with different states of solute content and particles during annealing are simulated. The model demonstrates predictive capability not only for grain size and recrystallization kinetics, but also for grain morphology evolution and texture component development. The successful reproduction of recrystallized microstructures under various conditions demonstrates that the proposed method provides an effective way for both explaining and predicting complex microstructural behaviors during static recrystallization. This can enable precise control over post-rolling annealing processes to tailor aluminum alloys' microstructure and thus mechanical properties.

Keywords

Cellular automaton / Nucleation / Recrystallization texture / Solute drag / Particle effect

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Ruxue Liu, Zhiwu Zhang, Guowei Zhou, Zhihong Jia, Dongnan Huang, Dayong Li. A novel cellular automaton for simulating static recrystallization of aluminum alloys incorporating both solute drag and particle effects. Advances in Manufacturing 1-24 DOI:10.1007/s40436-025-00578-5

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