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Austenite Grain Size Estimtion from Chord Lengths of Logarithmic-Normal Distribution

Austenite Grain Size Estimtion from Chord Lengths of Logarithmic-Normal Distribution AbstractLinear section of grains in polyhedral material microstructure is a system of chords. The mean length of chords is the linear grain size of the microstructure. For the prior austenite grains of low alloy structural steels, the chord length is a random variable of gamma- or logarithmic-normal distribution. The statistical grain size estimation belongs to the quantitative metallographic problems. The so-called point estimation is a well known procedure. The interval estimation (grain size confidence interval) for the gamma distribution was given elsewhere, but for the logarithmic-normal distribution is the subject of the present contribution. The statistical analysis is analogous to the one for the gamma distribution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Metallurgy and Materials de Gruyter

Austenite Grain Size Estimtion from Chord Lengths of Logarithmic-Normal Distribution

Archives of Metallurgy and Materials , Volume 62 (4): 5 – Dec 1, 2017

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Publisher
de Gruyter
Copyright
© 2017 H. Adrian et al., published by De Gruyter Open
ISSN
2300-1909
eISSN
2300-1909
DOI
10.1515/amm-2017-0300
Publisher site
See Article on Publisher Site

Abstract

AbstractLinear section of grains in polyhedral material microstructure is a system of chords. The mean length of chords is the linear grain size of the microstructure. For the prior austenite grains of low alloy structural steels, the chord length is a random variable of gamma- or logarithmic-normal distribution. The statistical grain size estimation belongs to the quantitative metallographic problems. The so-called point estimation is a well known procedure. The interval estimation (grain size confidence interval) for the gamma distribution was given elsewhere, but for the logarithmic-normal distribution is the subject of the present contribution. The statistical analysis is analogous to the one for the gamma distribution.

Journal

Archives of Metallurgy and Materialsde Gruyter

Published: Dec 1, 2017

References