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...
| Published in: | Journal of Glaciology |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
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Cambridge University Press (CUP)
1980
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1017/s0022143000010753 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143000010753 |
| 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. |
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