Article ID Journal Published Year Pages File Type
1563287 Computational Materials Science 2008 8 Pages PDF
Abstract

A computational image analysing algorithm was developed for the separation and quantitative characterisation of different Mg17Al12 phases in the long term annealed (LTA), high pressure die cast (hpdc) AZ91 magnesium alloy such as βm (massive) and βc+d (continuous + discontinuous). The size distribution, nearest neighbour distance (NND) distribution, number density, average size, average NND and area fraction of βm and βc+d phases with respect to different annealing temperatures were obtained by means of novel image processing techniques and compared with the as-cast (AC) material. The different trends associated with the changes of these quantities and morphologies, nucleation and agglomeration of the phases with respect to the annealing temperature is explained. These micro quantities are also correlated with the tensile properties of different annealed castings.

Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics
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