| Summary: | Microporosity refers to small voids in the material in the size range from a few to hundreds of micrometers. These small voids can reduce the fatigue performance of the cast components. In the foundry industry, numerous efforts have been made to predict and control microporosity formation.
The present work studies the formation of microporosity in A356 (Al-7wt%Si-0.3wt%Mg) aluminum alloy castings. The focus is on prediction of pore size distribution, which is a crucial factor in fatigue analysis. This requires precise experimental characterization of pore size and simulation of both nucleation and growth kinetics of the pores.
In the initial stage of this work, microporosity formed in directionally solidified tapered cylindrical A356 casting samples were analyzed using high resolution X-ray microtomography (XMT). The results showed that increasing the cooling rate and degassing time yields lower microporosity within the microstructure.
These microporosity data were later used to validate a numerical model that simulates microporosity formation in A356 castings. In this model, the nucleation site distribution of the pores is a Gaussian function of hydrogen supersaturation in the melt. The pore growth is a hydrogen-diffusion controlled process. With the model it is possible to evaluate the relative contributions of hydrogen content, cooling rate and nucleation sites to microporosity formation, and to quantify the pore nucleation kinetics at given casting conditions.
Furthermore, this model was applied to study the effect of oxide inclusions on pore nucleation kinetics. Castings were prepared under different casting conditions aimed at manipulating the tendency to form and entrain oxides in the melt. Two alloy variants of A356 were tested in which the main difference was Sr content. By fitting the experimental results with the pore formation model, an estimate of the pore nucleation site distribution has been made. It is shown increasing the tendency to form oxide films increases both the number and potency of nucleation sites. Based on the model prediction, Sr-modification impacts both the pore nucleation and pore growth kinetics. === Applied Science, Faculty of === Materials Engineering, Department of === Graduate
|
|---|
