Statistical Models of Snow Strength

Abstract Snow is variable in both time and space. Because of this fact, a complete understanding of snow strength must include statistical strength analyses. Two types of statistical strength theories are the series-element, or weakest-link theories and the parallel-element theories. In the case of...

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Bibliographic Details
Published in:Journal of Glaciology
Main Author: Sommerfeld, Richard A.
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 1980
Subjects:
Online Access:http://dx.doi.org/10.1017/s0022143000010753
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143000010753
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Summary:Abstract Snow is variable in both time and space. Because of this fact, a complete understanding of snow strength must include statistical strength analyses. Two types of statistical strength theories are the series-element, or weakest-link theories and the parallel-element theories. In the case of snow in shear, Daniels’ (1945) parallel-element theory provides a quantitative explanation of the size and stress-rate relationships of snow, which are at least as accurate as presently available data. In the case of tensile tests, a combination of the two types of theories is proposed which also provides a quantitative explanation which is as accurate as present data. In each case large-volume, low-stress-rate strengths are predicted using small-volume, high-stress-rate data. More data are necessary to provide definitive tests of the proposed hypotheses.