Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/54723
Type: Artigo de periódico
Title: Application of an Artificial Intelligence Technique to Improve Purification in the Zone Refining Process
Author: Cheung, T
Cheung, N
Garcia, A
Abstract: A combined theoretical and experimental approach was undertaken to quantitatively determine the influence of a variable solute distribution coefficient, k, on impurity distribution in multipass purification by zone refining. Axial impurity profiles have been experimentally determined for a number of zone passes. It has been shown that the adoption of a variable-k approach in the simulation of impurity profiles during different zone passes is generally much closer to the experimental profiles than the usual adoption of a constant k. An artificial intelligence technique interacts with the numerical model to determine the best molten zone size in each pass in order to provide maximum purification.
Subject: Purification
zone refining
segregation
pure materials
simulation
artificial intelligence
Country: EUA
Editor: Springer
Rights: fechado
Identifier DOI: 10.1007/s11664-009-0947-4
Date Issue: 2010
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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