Numerical simulation for dendrite growth in directional solidification using LBM-CA (cellular automata) coupled method

Lee, Wonjoo; Jeong, Yuhyeong; Lee, Jae‐Wook; Lee, Howon; Kang, Seong-Hoon; Kim, Young‐Min; Yoon, Jonghun

doi:10.1016/j.jmst.2020.01.047

Cited by 24 publications

(6 citation statements)

References 54 publications

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“…Low-carbon steel is widely manufactured into a variety of building components 1,2 , containers, sheets, bars, etc. Because of its good cold formability and excellent welding performance, low-carbon steel occupies a large proportion of many steel products.…”

mentioning

confidence: 99%

Corrosion behavior and cellular automata simulation of carbon steel in salt-spray environment

Qin,

Liu,

Shao

et al. 2024

npj Mater Degrad

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Scanning electron microscope (SEM) and X-ray diffraction (XRD) were used to discuss the corrosion loss and morphology of the pit and rust layer of carbon steel. It was found that the corrosion process is largely influenced by the cyclic shedding of surface corrosion products, in addition to being controlled by the mechanism of oxide film shedding and pit evolution. A corrosion mechanism (the mechanism of rust layer shedding) is proposed. As a result, in this paper, the corrosion process of the test steel is simulated by the cellular automata. It was set up that the mechanism of oxide film shedding, the mechanism of pit evolution, and the mechanism of rust layer shedding in Cellular Automata Simulation. The optimal time ratio and simulation parameters were found, and a predictable cellular automata corrosion simulation model was built, providing a solution for carbon steel’s service life prediction.

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mentioning

confidence: 99%

Corrosion behavior and cellular automata simulation of carbon steel in salt-spray environment

Qin,

Liu,

Shao

et al. 2024

npj Mater Degrad

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“…At present, some researchers have carried out corrosion simulation research on other kinds of steel and obtained good results. For example, Keekeun Kim et al [1] predicted the Life of Plasma Sprayed Thermal Barrier Coating Systems, And Wonjoo Lee et al [2], The Lattice Boltzmann Method (LBM) was used to simulate mass transport by diffusion and convection during solidification, providing a simulation of physical parameters such as flow and heat transfer within the melt, and the Cellular Automata (CA) model was used to determine the phase transition process and to simulate the growth and interaction of dendritic crystals. In the current corrosion simulation study, the focus of the study is mainly on the growth process of corrosion pits.…”

Section: Research Backgroundmentioning

confidence: 99%

Corrosion Behavior and Cellular Automata Simulation of Carbon Steel in Salt-Spray Environment

Teng,

Qing,

Liu

et al. 2023

Preprint

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Scanning electron microscope (SEM) and X-ray diffraction (XRD) were used to discuss the corrosion loss and morphology of the pit and rust layer of carbon steel. It was found that the corrosion process is largely influenced by the cyclic shedding of surface corrosion products, in addition to being controlled by the mechanism of oxide film shedding and pit evolution. A new corrosion mechanism (the mechanism of rust layer shedding) is proposed. As a result, in this paper, the corrosion process of the test steel is simulated by the cellular automata. It was set up that the mechanism of oxide film shedding, the mechanism of pit evolution, and the mechanism of rust layer shedding in Cellular Automata Simulation. The optimal time ratio and simulation parameters were found, and a predictable cellular automata corrosion simulation model was built, providing a solution for carbon steel's service life prediction.

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“…Ci et al devel numerical model to predict the evolution of PDAS with additional manufacturing eters and accurately predict the evolution of PDAS under pulsed laser process para [21]. Lee et al proposed a coupled lattice Boltzmann method (LBM) cellular automa model that describes different types of dendrite formation under different solidifi conditions (e.g., temperature gradients and growth rates) and can display dendrit phology and quantitatively predict primary dendrite arm spacing [22]. Xue et al pr a coupled lattice Boltzmann method (LBM) cellular automata model that describes ent types of dendrite formation under different solidification conditions (e.g., temp gradients and growth rates) and can display dendrite morphology and quantitative The contrast of low magnification images is usually low, using the traditional histogram equalization method and Laplace algorithm to enhance dendrite images, for which the results are shown in Figure 1b,c; due to the small difference in grayscale between the dendrite region and the dendrite arm region, some of the dendrite information is lost in the enhanced image, it is difficult to identify the dendrite structures, and it takes a lot of time to measure manually [19].…”

Section: Introductionmentioning

confidence: 99%

“…Ci et al developed a numerical model to predict the evolution of PDAS with additional manufacturing parameters and accurately predict the evolution of PDAS under pulsed laser process parameters [21]. Lee et al proposed a coupled lattice Boltzmann method (LBM) cellular automata (CA) model that describes different types of dendrite formation under different solidification conditions (e.g., temperature gradients and growth rates) and can display dendrite morphology and quantitatively predict primary dendrite arm spacing [22]. Xue et al proposed a coupled lattice Boltzmann method (LBM) cellular automata model that describes different types of dendrite formation under different solidification conditions (e.g., temperature gradients and growth rates) and can display dendrite morphology and quantitatively predict primary dendrite arm spacing.…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Cast Billet Dendrite Based on Improved Hough Transform

Wang,

He,

Xie

2024

Crystals

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Primary dendrite information is one of the most important metrics to measure the quality of continuous cast slabs. The contrast of low magnification images is very low under the influence of illumination and sampling devices, so the traditional dendrite detection method has the problem of missed detections. We propose an automatic dendrite detection method based on an improved Hough transform, which effectively improves the accuracy and efficiency of primary dendrite detection. By using the local grayscale features of the image, a genetic algorithm-based local contrast enhancement algorithm is proposed. Compared with the traditional contrast enhancement algorithm, it can retain all the information of the dendrites. Combined with the image binarization method based on Hessian matrix, we can obtain more detailed information about the dendrites. According to the continuity and solidification characteristics of dendrites, the Hough transform is improved to extract dendrite information, which effectively reduces the computational cost of the Hough transform. The experimental results show that the method of this paper has versatility, and the error is four pixels compared with the manual method, which can provide a reliable basis for the subsequent judgement of the quality of cast billets.

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Numerical simulation for dendrite growth in directional solidification using LBM-CA (cellular automata) coupled method

Cited by 24 publications

References 54 publications

Corrosion behavior and cellular automata simulation of carbon steel in salt-spray environment

Corrosion behavior and cellular automata simulation of carbon steel in salt-spray environment

Corrosion Behavior and Cellular Automata Simulation of Carbon Steel in Salt-Spray Environment

Automatic Detection of Cast Billet Dendrite Based on Improved Hough Transform

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