Snow Compression Force and Tomography Data for Viscoplastic Analysis

Compression force data from 11 experiments and corresponding 3D image data from X-ray tomography scans study the viscoplastic behavior of snow. The dataset was published by ENVIDAT and last updated in 2023. It supports analysis of a transition in Glen's law stress exponent based on geometrical grain size.

Use Cases

• Model stress exponent transitions in Glen's law using compression force data and grain size from tomography images.
• Analyze the relationship between geometrical grain size and deformation mechanism from fine to coarse grains.
• Validate implicit transient scalar models for creep relations using experimental force and relaxation data.
• Compare grain boundary sliding versus dislocation creep regimes using the provided force and 3D image datasets.
• Study the viscoplastic behavior of intact ice matrix under consecutive loading-relaxation conditions.

Strengths

• Contains data from 11 distinct micro-compression experiments.
• Includes corresponding 3D image data from X-ray tomography scans for each experiment.
• Data reveals a specific cross-over of stress exponent from n=1.9 for fine grains to n=4.4 for coarse grains.

Limitations

• Small sample size of only 11 experiments may limit statistical power.
• Specific file formats, data size, and column details are unknown.
• Geographic and temporal coverage of the snow samples is not specified.

Provenance

Source

ENVIDAT via NASA Earthdata.

Collection Method

Data gathered from consecutive loading-relaxation experiments using a micro-compression stage within an X-ray tomography scanner in the SLF cold laboratory.

Freshness

Last updated in 2023.