Investigation on the formation of microporosity in aluminum alloys

Liu, Yongqin; Wang, Jie; Gao, Zhiming; Zheng, Yufeng

doi:10.1016/j.jallcom.2015.01.009

Cited by 21 publications

(15 citation statements)

References 9 publications

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“…A review of the early attempts to model microporosity in aluminumsilicon alloys was presented by Lee et al [16]. More recently, Liu et al [17] proposed a mathematical model on the microporosity of aluminum castings taking into account the dissolved hydrogen, the solidification shrinkage, and the interface energy. As detailed by the former authors, the flow of liquid alloy through the solid skeleton within the mushy zone is stopped when the pressure exerted by gas dissolution P g overcomes the sum of the local pressure of the liquid P l and the pressure exerted by the surface energy on the bubble P σ :…”

Section: Criterion Of Gas Porosity Formationmentioning

confidence: 99%

A review on the porous medium approaches to model the flow of interdendritic liquid during the solidification of alloys in casting processes: theory and experiments

Castro

2020

Int J Adv Manuf Technol

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The porous medium approach is one of the most popular methods to model the flow of liquid alloys through the solid interdendritic channels in the mushy zone, which is crucial to predict casting defects. In particular, characterizing the permeability of the mushy zone is of vital importance to reliably predict shrinkage porosity and blowholes. Nevertheless, this is not as simple task as permeability continuously evolves through the different stages of the solidification process. For these reasons, a great effort has been made in the past to obtain relationships relating the microstructural parameters to the permeability of the mushy zone. Also, some researchers have taken advantage of the advances in pore network modeling to predict permeability, obtaining promising results. Although a number of numerical experiments have been performed, their reliability has traditionally been hampered by the technical difficulties in reproducing real process conditions. The recent development of imaging techniques with improved spatial and temporal resolution, such as synchrotron 4D (3D + time) X-ray microtomography, has marked a turning point in the experimental validation of the models and is an efficient means to explore the solidification mechanisms. This context of prolific theoretical modeling and major technical achievements provides an excellent opportunity for the materials processing research community to apply the recent progress in fluid flow modeling through complex porous media to the field of casting processes. The aim of this article is to review the state of the art in modeling and experimental evaluation of the permeability of semi-solid zone of casting alloys during solidification so as to smooth the way to future studies. The main stumbling blocks in the field are also presented.

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Section: Criterion Of Gas Porosity Formationmentioning

confidence: 99%

A review on the porous medium approaches to model the flow of interdendritic liquid during the solidification of alloys in casting processes: theory and experiments

Castro

2020

Int J Adv Manuf Technol

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“…The final quality of the casting products is greatly affected by the characteristics of the molten metal [1][2][3]. In order to control the casting defects of aluminum products, such as porosity and shrinkage cavity, it is particularly important to control the temperature of the liquid aluminum and the dissolved hydrogen content in the liquid aluminum during the melting process [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Temperature of Liquid Aluminum and the Dissolved Hydrogen Content in Liquid Aluminum with a Machine Learning Approach

Kim

Yun

Yang

et al. 2020

Metals

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In aluminum casting, the temperature of liquid aluminum and the dissolved hydrogen density are crucial factors to be controlled for the purpose of both quality control of molten metal and cost efficiency. However, the empirical and numerical approaches to predict these parameters are quite complex and time consuming, and it is necessary to develop an alternative method for rapid prediction with a small number of experiments. In this study, the machine learning models were developed to predict the temperature of liquid aluminum and the dissolved hydrogen content in liquid aluminum. The obtained experimental data was preprocessed to be used for constructing the machine learning models by the sliding time window method. The machine learning models of linear regression, regression tree, Gaussian process regression (GPR), Support vector machine (SVM), and ensembles of regression trees were compared to find the model with the highest performance to predict the target properties. For the prediction of the temperature of liquid aluminum and the dissolved hydrogen content in liquid aluminum, the linear regression and GPR models were selected with the high accuracy of prediction, respectively. In comparison to the numerical modeling, the machine learning modeling had better performance, and was more effective for predicting the target property even with the limited data set when the characteristics of the data were properly considered in data preprocessing.

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“…Jie et al . 25,26 adopted a mathematical model on the microporosity of aluminum castings, incorporating the pressure increase induced by dissolved hydrogen, solidification shrinkage and interface energy. Nevertheless, the model could not provide the graphical morphology output of the subject porosity.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional cellular automaton simulation of coupled hydrogen porosity and microstructure during solidification of ternary aluminum alloys

Gu¹,

Lu²,

Ridgeway³

et al. 2019

Sci Rep

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Hydrogen-induced porosity formed during solidification of aluminum-based alloys has been a major issue adversely affecting the performance of solidification products such as castings, welds or additively manufactured components. A three-dimensional cellular automaton model was developed, for the first time, to predict the formation and evolution of hydrogen porosity coupled with grain growth during solidification of a ternary Al-7wt.%Si-0.3wt.%Mg alloy. The simulation results fully describe the concurrent nucleation and evolution of both alloy grains and hydrogen porosity, yielding the morphology of multiple grains as well as the porosity size and distribution. This model, successfully validated by X-ray micro-tomographic measurements and optical microscopy of a wedge die casting, provides a critical tool for minimizing/controlling porosity formation in solidification products.

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Investigation on the formation of microporosity in aluminum alloys

Cited by 21 publications

References 9 publications

A review on the porous medium approaches to model the flow of interdendritic liquid during the solidification of alloys in casting processes: theory and experiments

A review on the porous medium approaches to model the flow of interdendritic liquid during the solidification of alloys in casting processes: theory and experiments

Prediction of the Temperature of Liquid Aluminum and the Dissolved Hydrogen Content in Liquid Aluminum with a Machine Learning Approach

Three-dimensional cellular automaton simulation of coupled hydrogen porosity and microstructure during solidification of ternary aluminum alloys

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