Abstract
The random sampling approach offers an elegant yet accurate way of validating microsegregation models. However, both instrumental errors and interference from secondary phases complicate the treatment of randomly sampled microprobe data. This study demonstrates that the normal procedure of sorting the data for each element independently can lead to inaccurate estimation of segregation profiles within multicomponent, multiphase, aluminum alloys. A recently proposed alloy-independent approach is shown to more reliably isolate these interferences, allowing more accurate validation of microsegregation models. Application of this approach to examine solidification segregation of a 319-type alloy demonstrated that, for these slowly cooled castings, neither Sr or TiB2 additions significantly affected coring of Cu within the primary α-Al dendrites. Comparison against predictions of CALPHAD-type Gulliver–Scheil models was less satisfactory. Consideration of back-diffusion and morphology effects through a one-dimensional (1-D) numerical model do not improve the agreement. Possible reasons for the lack of agreement are hypothesized.
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