Modeling of Inclusion Behavior in an Aluminum Induction Furnace

Waz, Emmanuel; Bansal, Akshay; Chapelle, Pierre; Delannoy, Yves; Bellot, Jean‐Pierre; Brun, Pierre Le

doi:10.1007/978-3-319-48251-4_144

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…Depuis une quinzaine d'années, des modèles numériques de procédés de traitement du métal liquide couplent l'hydrodynamique polyphasique et les comportements inclusionnaires (Mirgaux et al, 2008et Waz et al, 2016pour les alliages d'aluminium, Daoud et al, 2011et Bellot et al, 2014 pour les aciers) à l'aide de bilans de populations. Ces modèles permettent de simuler des processus à l'échelle macroscopique des procédés métallurgiques, de l'ordre d'un à quelques mètres.…”

Section: Introductionunclassified

“…Control performance of these materials therefore requires control of the inclusion populations, requiring in particular a very good knowledge of the mechanisms which govern their evolution in number and size in refining reactors. Inclusive behaviors in supply chains steel and aluminum have already been the subject of numerical studies at the process scale (Bellot et al, 2014 ;Waz et al, 2016) in which the transport and agglomeration of inclusions are modelled. In order to improve the modelling of key phenomena such as the aggregation and capture of wall inclusions, local simulations, at the scale of an inclusion pair and a layer limit to the wall of a reactor, are carried out here using a lattice Boltzmann method (Sungkorn and Derksen, 2012).…”

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confidence: 99%

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Local behavior of inclusions in reactors metallurgical: Aggregation and deposition on the walls

et al. 2023

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Populations of inclusions conditioned very early in the alloy production process metals, during the refining and liquid metal treatment stages, are likely to drastically impact mechanical performance, especially fatigue resistance. Control performance of these materials therefore requires control of the inclusion populations, requiring in particular a very good knowledge of the mechanisms which govern their evolution in number and size in refining reactors. Inclusive behaviors in supply chains steel and aluminum have already been the subject of numerical studies at the process scale (Bellot et al., 2014 ; Waz et al., 2016) in which the transport and agglomeration of inclusions are modelled. In order to improve the modelling of key phenomena such as the aggregation and capture of wall inclusions, local simulations, at the scale of an inclusion pair and a layer limit to the wall of a reactor, are carried out here using a lattice Boltzmann method (Sungkorn and Derksen, 2012).

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Section: Introductionunclassified

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Local behavior of inclusions in reactors metallurgical: Aggregation and deposition on the walls

et al. 2023

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“…The behaviour of particles present in various foundry alloys (both inclusions and intentionally added particles -e.g. reinforcing phase in Metal Matrix Composite (MMC) composites) and their influence on the properties of the casting are the subjects of many works covering numerical and mathematical modelling [2][3][4][5][6] These studies concern various stages of the production of castings, starting from the melting of materials and ending with the formation of the microstructure. However, the process of inmold filtration of particles existing in the liquid metal is generally merely considered to be a "black box", which is defined with a few flow-relevant parameters.…”

Section: Introductionmentioning

confidence: 99%

Archives of Foundry Engineering

Baumann,

Keßler,

Hoppach

et al. 2021

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The objective of this work is to gain a deeper understanding of the separation effects and particle movement during filtration of nonmetallic inclusions in aluminum casting on a macroscopic level. To understand particle movement, complex simulations are performed using Flow 3D. One focus is the influence of the filter position in the casting system with regard to filtration efficiency. For this purpose, a real filter geometry is scanned with computed tomography (CT) and integrated into the simulation as an STL file. This allows the filtration processes of particles to be represented as realistically as possible. The models provide a look inside the casting system and the flow conditions before, in, and after the filter, which cannot be mapped in real casting tests. In the second part of this work, the casting models used in the simulation are replicated and cast in real casting trials. In order to gain further knowledge about filtration and particle movement, non-metallic particles are added to the melt and then separated by a filter. These particles are then detected in the filter by metallographic analysis. The numerical simulations of particle movement in an aluminum melt during filtration, give predictions in reasonable agreement with experimental measurements.

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“…Under operating conditions, however, it is difficult to perform optimization of the refining technology; therefore, simulation methods are preferred as more beneficial. Modelling processes is a method that aims at capturing the behaviour of a real system using a physical or mathematical model [14][15][16][17][18][19][20][21][22] without having to interfere with a real technological process and thereby limit the standard production process. Based on the results obtained on the model, it is possible to predict the behaviour of the real system in the course of various process changes.…”

Section: Introductionmentioning

confidence: 99%

Archives of Metallurgy and Materials

Michalek

Tkadlečková

Socha

et al. 2018

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This paper deals with the possibilities of using physical modelling to study the degassing of metal melt during its treatment in the refining ladle. The method of inert gas blowing, so-called refining gas, presents the most common operational technology for the elimination of impurities from molten metal, e.g. for decreasing or removing the hydrogen content from liquid aluminium. This refining process presents the system of gas-liquid and its efficiency depends on the creation of fine bubbles with a high interphase surface, uniform distribution, long period of its effect in the melt, and mostly on the uniform arrangement of bubbles into the whole volume of the refining ladle. Physical modelling represents the basic method of modelling and it makes it possible to obtain information about the course of refining processes. On the basis of obtained results, it is possible to predict the behaviour of the real system during different changes in the process. The experimental part focuses on the evaluation of methodical laboratory experiments aimed at the proposal and testing of the developed methods of degassing during physical modelling. The results obtained on the basis of laboratory experiments realized on the specific physical model were discussed.

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Modeling of Inclusion Behavior in an Aluminum Induction Furnace

Cited by 4 publications

References 15 publications

Local behavior of inclusions in reactors metallurgical: Aggregation and deposition on the walls

Local behavior of inclusions in reactors metallurgical: Aggregation and deposition on the walls

Archives of Foundry Engineering

Archives of Metallurgy and Materials

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