A new perspective on the normal grain growth exponent obtained in two-dimensional Monte Carlo simulations
Conventional Monte Carlo Potts models were reported to produce a significantly lower normal grain growth exponent of n #~ 0.41 in small grain size regimes. In this paper, it is shown that a three-parameter nonlinear regression analysis should be employed in order to obtain more accurate values for t...
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| Published in | Modelling and simulation in materials science and engineering Vol. 11; no. 6; pp. 859 - 861 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
IOP Publishing
01.11.2003
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| Online Access | Get full text |
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| Summary: | Conventional Monte Carlo Potts models were reported to produce a significantly lower normal grain growth exponent of n #~ 0.41 in small grain size regimes. In this paper, it is shown that a three-parameter nonlinear regression analysis should be employed in order to obtain more accurate values for the grain growth exponents from the simulation data. To some degree, the lower grain growth exponent previously reported can also be attributed to the strong random nature of the simulation algorithm. |
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| Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| ISSN: | 0965-0393 1361-651X |
| DOI: | 10.1088/0965-0393/11/6/004 |