3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy
We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:4a8ad0e782e54b36b89ba56fc832ce96 2023-05-15T18:32:22+02:00 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy N. Calonne C. Geindreau F. Flin S. Morin B. Lesaffre S. Rolland du Roscoat P. Charrier 2012-09-01 https://doi.org/10.5194/tc-6-939-2012 http://www.the-cryosphere.net/6/939/2012/tc-6-939-2012.pdf https://doaj.org/article/4a8ad0e782e54b36b89ba56fc832ce96 en eng Copernicus Publications doi:10.5194/tc-6-939-2012 1994-0416 1994-0424 http://www.the-cryosphere.net/6/939/2012/tc-6-939-2012.pdf https://doaj.org/article/4a8ad0e782e54b36b89ba56fc832ce96 undefined The Cryosphere, Vol 6, Iss 5, Pp 939-951 (2012) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2012 fttriple https://doi.org/10.5194/tc-6-939-2012 2023-01-22T19:15:16Z We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy of permeability was detected and is consistent with that observed for the effective thermal conductivity obtained from the same samples. The anisotropy coefficient, defined as the ratio of the vertical over the horizontal components of K, ranges from 0.74 for a sample of decomposing precipitation particles collected in the field to 1.66 for a depth hoar specimen. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA×ρi. We define K and K* as the average of the diagonal components of K and K*, respectively. The 35 values of K* were fitted to snow density (ρs) and provide the following regression: K = (3.0 ± 0.3) res2 exp((−0.0130 ± 0.0003)ρs). We noted that the anisotropy of permeability does not affect significantly the proposed equation. This regression curve was applied to several independent datasets from the literature and compared to other existing regression curves or analytical models. The results show that it is probably the best currently available simple relationship linking the average value of permeability, K, to snow density and specific surface area. Article in Journal/Newspaper The Cryosphere Unknown The Cryosphere 6 5 939 951 |
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geo envir N. Calonne C. Geindreau F. Flin S. Morin B. Lesaffre S. Rolland du Roscoat P. Charrier 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
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geo envir |
description |
We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy of permeability was detected and is consistent with that observed for the effective thermal conductivity obtained from the same samples. The anisotropy coefficient, defined as the ratio of the vertical over the horizontal components of K, ranges from 0.74 for a sample of decomposing precipitation particles collected in the field to 1.66 for a depth hoar specimen. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA×ρi. We define K and K* as the average of the diagonal components of K and K*, respectively. The 35 values of K* were fitted to snow density (ρs) and provide the following regression: K = (3.0 ± 0.3) res2 exp((−0.0130 ± 0.0003)ρs). We noted that the anisotropy of permeability does not affect significantly the proposed equation. This regression curve was applied to several independent datasets from the literature and compared to other existing regression curves or analytical models. The results show that it is probably the best currently available simple relationship linking the average value of permeability, K, to snow density and specific surface area. |
format |
Article in Journal/Newspaper |
author |
N. Calonne C. Geindreau F. Flin S. Morin B. Lesaffre S. Rolland du Roscoat P. Charrier |
author_facet |
N. Calonne C. Geindreau F. Flin S. Morin B. Lesaffre S. Rolland du Roscoat P. Charrier |
author_sort |
N. Calonne |
title |
3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
title_short |
3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
title_full |
3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
title_fullStr |
3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
title_full_unstemmed |
3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
title_sort |
3-d image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy |
publisher |
Copernicus Publications |
publishDate |
2012 |
url |
https://doi.org/10.5194/tc-6-939-2012 http://www.the-cryosphere.net/6/939/2012/tc-6-939-2012.pdf https://doaj.org/article/4a8ad0e782e54b36b89ba56fc832ce96 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 6, Iss 5, Pp 939-951 (2012) |
op_relation |
doi:10.5194/tc-6-939-2012 1994-0416 1994-0424 http://www.the-cryosphere.net/6/939/2012/tc-6-939-2012.pdf https://doaj.org/article/4a8ad0e782e54b36b89ba56fc832ce96 |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/tc-6-939-2012 |
container_title |
The Cryosphere |
container_volume |
6 |
container_issue |
5 |
container_start_page |
939 |
op_container_end_page |
951 |
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1766216471559536640 |