A Review on Modelling and Simulation of Laser Additive Manufacturing: Heat Transfer, Microstructure Evolutions and Mechanical Properties

Zhang, Zhao; Wang, Yifei; Ge, P.

doi:10.3390/coatings12091277

Cited by 16 publications

(10 citation statements)

References 155 publications

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“…The mechanical properties of aluminum alloys are mainly influenced by solid solution atoms, precipitates, dislocations, and grains. [24][25][26][27] Precipitate strengthening plays a key role on mechanical properties. Typically, the main interaction mechanisms between dislocations and precipitates at room temperature are shearing and bypassing.…”

Section: Resultsmentioning

confidence: 99%

Molecular Dynamics Simulation of Interaction between Edge Dislocations and Stable β‐Phase Precipitates in Aluminum Alloy

Li,

Qiu,

Kong

et al. 2023

Physica Status Solidi (b)

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Stable precipitate takes the essential role for material strengthening in Al‐Mg‐Si alloys. To reveal how the stable precipitate works in material strengthening, a molecular dynamics model is carried out to show the interaction between the edge dislocations and the plate‐shaped β phase of Mg2Si. The critical resolved shear stress (CRSS) is related to the precipitate characteristics including sizes and thickness directions. The CRSS increases with the increase of the precipitate size. When the thickness direction of precipitate changes from [001] to [100], the CRSS increases from 326.76 MPa to 368.7 MPa. This phenomenon is mainly affected by the interaction length between dislocation and β phase. With the increase of interaction length, the interaction time for dislocation to overcome pinning increases. The critical bending angle of dislocation can be affected by the interaction time and shear strain rate. The relationship between the critical bending angle and the CRSS in Al‐Mg‐Si alloy is then established.This article is protected by copyright. All rights reserved.

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Section: Resultsmentioning

confidence: 99%

Molecular Dynamics Simulation of Interaction between Edge Dislocations and Stable β‐Phase Precipitates in Aluminum Alloy

Li,

Qiu,

Kong

et al. 2023

Physica Status Solidi (b)

Self Cite

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“…The Monte Carlo model is established following probabilistic strategic on selections of grain coarsening orientations, which makes it highly efficient for the problems related to multi-length and time scales [ 27 ]. When comparing the CA method with the MC method, CA has unparalleled advantages, including simpler algorithms and higher computational efficiency.…”

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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“…During the solidification process, the microstructure formation can estimate the final material properties. Numerical analysis can help in bridging the gap to predict final material properties depending on consolidation processes (Zhang et al , 2022a). To predict crystal growth and phase transformation, various theories such as cellular automata (CA), Monte-Carlo (MC) and phase-field (PF) are used.…”

Section: Digital Twinmentioning

confidence: 99%

“…In comparison to CA and PF models, MC model uses a probabilistic approach rather than a physics-based model (Zhang and Hu, 2018). The PF model can predict microstructure evolution at a much smaller scale but with more details compared to the CA model, involving more computational cost with a limited period in real time (Zhang et al , 2022a). The CA model can be used to predict grain growth with the potential to use at the part scale.…”

Section: Digital Twinmentioning

confidence: 99%

A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes

Tariq

Joy

et al. 2023

RPJ

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Purpose This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations. Design/methodology/approach This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques. Findings A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions. Originality/value Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

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A Review on Modelling and Simulation of Laser Additive Manufacturing: Heat Transfer, Microstructure Evolutions and Mechanical Properties

Cited by 16 publications

References 155 publications

Molecular Dynamics Simulation of Interaction between Edge Dislocations and Stable β‐Phase Precipitates in Aluminum Alloy

Molecular Dynamics Simulation of Interaction between Edge Dislocations and Stable β‐Phase Precipitates in Aluminum Alloy

Review on Cellular Automata for Microstructure Simulation of Metallic Materials

A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes

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