Recent research progress on the phase-field model of microstructural evolution during metal solidification

Wang, Kaiyang; Lv, Shaojie; Wu, Honghui; Wu, Guilin; Wang, Shuize; Gao, Junheng; Zhu, Jiaming; Yang, Xusheng; Mao, Xinping

doi:10.1007/s12613-023-2710-x

Cited by 5 publications

(2 citation statements)

References 94 publications

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“…The MC method, which falls under the category of stochastic statistical mathematics, is particularly well-suited for simulating two-dimensional or three-dimensional grain growth [13], and it also models grain topology and growth kinetics effectively [14]. The fundamental principle of the PF method is to use a continuous field to describe interfaces, making it especially appropriate for microstructure simulation such as metal solidification and dendritic growth [15].…”

Section: Ca Characteristics and Modeling Steps For Microstructure Sim...mentioning

confidence: 99%

Review on Cellular Automata for Microstructure Simulation of Metallic Materials

Zhi,

Jiang,

et al. 2024

Materials

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The cellular automata (CA) method has played an important role in the research and development of metallic materials. CA can interpret the microstructure changes of materials and obtain more abundant, accurate and intuitive information of microstructure evolution than conventional methods. CA can visually represent the process of grain formation, growth, development and change to us in a graphical way, which can assist us in analysis, thinking and solving problems. In the last five years, the application of CA in materials research has been rapidly developed, and CA has begun to occupy an increasingly important position in the simulation research of metallic materials. After introducing the advantages and limitations of CA compared to other widely used simulation methods, the purpose of this paper is to review the recent application progress on the microstructure simulation of metallic materials using CA, such as solidification, recrystallization, phase transformation and carbide precipitation occurring during forming and heat treatment. Specifically, recent research advances on microstructure simulation by CA in the fields of additive manufacturing, welding, asymmetrical rolling, corrosion prevention, etc., are also elaborated in this paper. Furthermore, this paper points out the future work direction of CA simulation in the research of metallic materials, especially in the simulation of the crystal structure, the prediction of mechanical properties, CA simulation software and rule systems, etc. These are expected to attract wide attention of researchers in the field of metallic materials and promote the development of CA in materials research.

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Section: Ca Characteristics and Modeling Steps For Microstructure Sim...mentioning

confidence: 99%

Review on Cellular Automata for Microstructure Simulation of Metallic Materials

Zhi,

Jiang,

et al. 2024

Materials

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show abstract

“…Generally, A356 aluminum alloy has a wide solidification range. During solidification, grains form and gradually grow from the liquid phase [15]. The grain growth rate is influenced by solidification temperature and alloy chemical composition [16].…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Lost-Foam Casting for Key Components of A356 Aluminum Alloy in New Energy Vehicles

Sun,

Cao,

Jin

et al. 2024

Materials

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The intricate geometry and thin walls of the motor housing in new energy vehicles render it susceptible to casting defects during conventional casting processes. However, the lost-foam casting process holds a unique advantage in eliminating casting defects and ensuring the strength and air-tightness of thin-walled castings. In this paper, the lost-foam casting process of thin-walled A356 alloy motor housing was simulated using ProCAST software (2016.0). The results indicate that the filling process is stable and exhibits characteristics of diffusive filling. Solidification occurs gradually from thin to thick. Defect positions are accurately predicted. Through analysis of the defect volume range, the optimal process parameter combination is determined to be a pouring temperature of 700 °C, an interfacial heat transfer coefficient of 50, and a sand thermal conductivity coefficient of 0.5. Microscopic analysis of the motor housing fabricated using the process optimized through numerical simulations reveals the absence of defects such as shrinkage at critical locations.

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Phase field modeling of grain stability of nanocrystalline alloys by explicitly incorporating mismatch strain

Zhou,

Wu,

et al. 2024

Rare Met.

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Recent research progress on the phase-field model of microstructural evolution during metal solidification

Cited by 5 publications

References 94 publications

Review on Cellular Automata for Microstructure Simulation of Metallic Materials

Review on Cellular Automata for Microstructure Simulation of Metallic Materials

Numerical Simulation of Lost-Foam Casting for Key Components of A356 Aluminum Alloy in New Energy Vehicles

Phase field modeling of grain stability of nanocrystalline alloys by explicitly incorporating mismatch strain

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