Implementation of nucleation in cellular automaton simulation of microstructural evolution during additive manufacturing of Al alloys

Mohebbi, Mohammad Sadegh; Ploshikhin, Vasily

doi:10.1016/j.addma.2020.101726

Cited by 41 publications

(37 citation statements)

References 60 publications

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“…The development of polycrystalline modeling of material behavior allows fully multiscale predictive models in which the purpose is capturing the fundamental aspects of material behavior under heterogeneous deformation [66]. In multi-scale modeling, the finite element method is coupled with discrete methods, such as the phase-field approach, Cellular Automata (CA) [67,68], Digital Material Representation (DMR) [69], Multi-resolution Models (MRM) [70], Molecular Dynamics (MD) [71], or the Monte Carlo (MC) [72,73]. The CA lattice of cells usually represents a 3D microstructure and reproduces topological relations between grain structures.…”

Section: Finite Element Methodsmentioning

confidence: 99%

Multiphysics Modeling and Numerical Simulation in Computer-Aided Manufacturing Processes

Trzepieciński

Dell’Isola

Lemu

2021

Metals

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The concept of Industry 4.0 is defined as a common term for technology and the concept of new digital tools to optimize the manufacturing process. Within this framework of modular smart factories, cyber-physical systems monitor physical processes creating a virtual copy of the physical world and making decentralized decisions. This article presents a review of the literature on virtual methods of computer-aided manufacturing processes. Numerical modeling is used to predict stress and temperature distribution, springback, material flow, and prediction of phase transformations, as well as for determining forming forces and the locations of potential wrinkling and cracking. The scope of the review has been limited to the last ten years, with an emphasis on the current state of knowledge. Intelligent production driven by the concept of Industry 4.0 and the demand for high-quality equipment in the aerospace and automotive industries forces the development of manufacturing techniques to progress towards intelligent manufacturing and ecological production. Multi-scale approaches that tend to move from macro- to micro- parameters become very important in numerical optimization programs. The software requirements for optimizing a fully coupled thermo-mechanical microstructure then increase rapidly. The highly advanced simulation programs based on our knowledge of physical and mechanical phenomena occurring in non-homogeneous materials allow a significant acceleration of the introduction of new products and the optimization of existing processes.

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Section: Finite Element Methodsmentioning

confidence: 99%

Multiphysics Modeling and Numerical Simulation in Computer-Aided Manufacturing Processes

Trzepieciński

Dell’Isola

Lemu

2021

Metals

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“…Bulk nucleation occurs on the top side of the melt pool and at the head of a solidification front [88] . Nuclei also form from the partially melted powder in the melt pool [89] , and they can survive given a sufficient volume of surrounding undercooled liquid metal [90] . These formed grains then assume an equiaxed morphology due to the low G/R ratio on the top side of the melt pool [91] .…”

Section: Microstructure Evolutionmentioning

confidence: 99%

Microstructure evolution in laser powder bed fusion-built Fe-Mn-Si shape memory alloy

2023

Microstructures

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The need for specialty powder composition limits the processing of a wide range of alloy products via the laser powder bed fusion (LPBF) technique. This work extends the adaptability of the LPBF technique by fabricating the first-ever Fe-30Mn-6Si (wt.%) product for potential use as a biodegradable shape memory alloy (SMA). Different LPBF processing parameters were assessed by varying the laser power, scan speed, and the laser re-scan strategy to achieve a fully dense part. The microstructure was found to respond to the processing conditions. For example, the microstructure of the parts produced by the high linear energy density (LED) had a columnar and strong crystallographic texture, while in the low LED, the parts were almost equiaxed and had a weak texture. To explain the evolved microstructure, the thermal history of the LPBF products was computed using the finite element analysis (FEA) of the melt pool gathered from a single-track laser scan experiment. The FEA results showed a varying temperature gradient, cooling and solidification rates, and temperature profile as a function of LED. Then, the relationship of hardness between grain size, phases present, and crystallographic misorientation of the LPBFbuilt alloy was analysed with reference to a control alloy of similar composition but prepared by arc melting. This study validates the LPBF processability of Fe-Mn-Si SMA and provides a new insight into the influence of processing parameters on the formed microstructure and hardness.

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“…Mohebbi et al [64] developed a new approach to integrate a particle-based (seed crystals) nucleation mechanism into the CA simulation of powder-bed laser beam melting. The model aims to reflect two features observed in the microstructures of additive manufactured Al alloys: the fusion boundary nucleation, which violates the principle of common bulk nucleation, favored under high solidification rates and low thermal gradients, and the epitaxial growth at the melt-pool bottom as observed in the microstructure of AlSi10Mg alloy.…”

Section: Modeling For Solidification Microstructure Evolution Under Different Calculation Scalesmentioning

confidence: 99%

A review on metal additive manufacturing: modeling and application of numerical simulation for heat and mass transfer and microstructure evolution

Liu

Gao

et al. 2021

China Foundry

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Metal additive manufacturing technology has been widely used in prototyping, parts manufacturing and repairing. Metal additive manufacturing is a multi-scale and multi-physical coupling process with complex physical phenomena of heat and mass transfer and microstructure evolution. It is hard to directly observe the dynamic behavior and microstructure evolution of molten pool during additive manufacturing. Therefore, numerical simulation of additive manufacturing process is significant since it can efficiently and pertinently predict and analyze the physical phenomena in the process of metal additive manufacturing, and provide a reference for technological parameters selection. In this review, the research progress of numerical simulation of metal additive manufacturing is discussed. Various aspects of numerical simulation models are reviewed, including: (1) Introduction of basic control method and physical description of numerical simulation models;(2) Comparison of various heat and mass transfer models based on different physical assumptions (heat conduction model; heat flux coupling model; discrete powder particle heat flux coupling model); (3) Applications of various microstructure evolution models [phase field (PF), cellular automata (CA), and Monte Carlo (MC)]. Finally, the development trend of numerical simulation of metal additive manufacturing, including the thermal-flow-solid coupling model and deep learning for numerical model, is analyzed.

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Implementation of nucleation in cellular automaton simulation of microstructural evolution during additive manufacturing of Al alloys

Cited by 41 publications

References 60 publications

Multiphysics Modeling and Numerical Simulation in Computer-Aided Manufacturing Processes

Multiphysics Modeling and Numerical Simulation in Computer-Aided Manufacturing Processes

Microstructure evolution in laser powder bed fusion-built Fe-Mn-Si shape memory alloy

A review on metal additive manufacturing: modeling and application of numerical simulation for heat and mass transfer and microstructure evolution

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