Microsegregation quantification for model validation

Muthiah Ganesan, Ludovic Thuinet, David Dye, Peter D. Lee

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    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 319-type alloy demonstrated that, for these slowly cooled castings, neither Sr and/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 effects through a 1-D numerical model improves the agreement but still does not match the experimental profile. Possible reasons for the lack of agreement are hypothesized.
    Original languageEnglish
    Title of host publicationTMS Annual Meeting|TMS Annu Meet
    Pages41-50
    Number of pages9
    Volume2006
    Publication statusPublished - 2006
    Event2006 TMS Annual Meeting - San Antonio, TX
    Duration: 1 Jul 2006 → …

    Conference

    Conference2006 TMS Annual Meeting
    CitySan Antonio, TX
    Period1/07/06 → …

    Keywords

    • Aluminum alloys
    • Microprobe analysis
    • Microsegregation
    • Modeling
    • Solidification

    Fingerprint

    Dive into the research topics of 'Microsegregation quantification for model validation'. Together they form a unique fingerprint.

    Cite this