X-Ray Microtomographic Characterization of Porosity in Aluminum Alloy A356

Abstract

The presence of microporosity can, in certain circumstances, lead to a significant reduction in the mechanical properties of cast aluminum alloys. The size of the microporosity is especially crucial to the performance of castings in fatigue applications. The aim of this study is to investigate the effect of cooling rate and degassing time on the formation and evolution of microporosity in aluminum alloy A356 (Al-7Si-0.3Mg) castings using traditional metallography and X-ray microtomography (XMT) methods. The final results clearly confirm that increasing the cooling rate and degassing time yield lower microporosity within the microstructure. The XMT analysis enabled the calculation of the volume fraction and size distribution of microporosity. The XMT analysis revealed a bimodel distribution of pores with one population of small pores and a second population of large pores. The large population has been attributed to hydrogen gas solubility, whereas the smaller population is proposed to be linked to the localized entrapment of liquid metal occurring at the end of mass feeding.

Cellular Automaton Modeling of Microporosity Formation during Solidification of Aluminum Alloys

“…These results are coincident with those observed experimentally. 15,39) It is understandable that at a faster cooling rate, dendrites develop rapidly with finer and longer arms and side branches, so that the complex dendrite network could be formed sooner. The formed dendrite network blocks hydrogen diffusion in liquid, and thus inhibits the growth of porosities.…”

“…2,3) Because of the fundamental and practical importance, extensive efforts have been devoted to develop models for predicting the occurrence of porosity in castings. As reviewed by Lee et al 2) and Stefanescu,3) most models, [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] such as analytical solutions, criteria functions, Darcy's law coupled with the conservation and continuity equations, and gas diffusion-controlled pore growth models, focus on predicting the amount of porosity in a solidified casting, but without graphical morphology output.…”

Modeling of Microporosity Size Distribution in Aluminum Alloy A356

“…More details about the casting and image analysis procedures can be found in previous work. [3] III. NUMERICAL MODEL The numerical model uses a volume element with uniform temperature and pressure representing the conditions at a point of interest in the casting to be analyzed.…”

“…Using a different approach from Lee and Hunt, [12] the supersaturation, ss (mol/m 3 ), in this model is the difference between the concentration of hydrogen in the liquid C l (mol/m 3 ) and the critical hydrogen concentration, i.e., ss ¼ C l À C e l : It should be noted that the three parameters, A, r, and ss 0 , appearing in Eq. [3] represent a quantification of the pore nucleation kinetics. The preexponential constant A is the total number density of available nucleation sites provided by the inclusions in the melt.…”

“…The existence of these two defect populations was confirmed by X-ray microtomography (XMT) observations performed on A356 in a previous study. [3] Threedimensional (3-D) XMT experimental observations of the porosity distribution are required as two-dimensional (2-D) metallographic observations can lead to errors in porosity size distribution measurement, as shown by Lashkari et al [3] and Nicoletto et al [4] Although the role of the small pore population on fatigue behavior is still unclear due to the competition with other microstructural features (such as the primary eutectic and intermetallics), it is well recognized that assessment of the large defect population is crucial for accurate fatigue assessment. [2] Many authors observed a reduction of the fatigue life of A356 T6 with increasing pore size.…”