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Characterization of Cast Metals with Probability Distribution Functions

Published online by Cambridge University Press:  10 February 2011

M. Steinzig  and
F. H. Harlow
M. Steinzig
Affiliation:
Group T-3, Los Alamos National Laboratory, Los Alamos, NM 87545
F. H. Harlow
Affiliation:
Group T-3, Los Alamos National Laboratory, Los Alamos, NM 87545
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Abstract

Characterization of microstructure using a probability distribution function (PDF) provides a means for extracting useful information about material properties. In the extension of classical PDF methods developed in our research, material characteristics are evolved by propagating an initial PDF through time, using growth laws derived from consideration of heat flow and species diffusion, constrained by the Gibbs-Thomson law. A model is described here that allows for nucleation, followed by growth of nominally spherical grains according to a stable or unstable growth law. Results are presented for the final average grain size as a function of cooling rate for various nucleation parameters. In particular we show that the model describes linear variation of final grain size with the inverse cube root of cooling rate. Within a subset of casting parameters, the stable-to-unstable manifests itself as a bimodal distribution of final grain size. Calculations with the model are described for the liquid to epsilon phase transition in a plutonium I weight percent gallium alloy.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 538: Symposium J – Multiscale Modelling of Materials , 1998 , 185
Copyright
Copyright © Materials Research Society 1999

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