Summary & Purpose
Accurate knowledge of snow mechanical properties, including Young's modulus, shear modulus, Poisson’s ratio, and density, is critical to many areas of snow science and to snow-related engineering problems. To facilitate the assessment of these properties, an innovative non-contacting laser ultrasound system (LUS) has been developed. This system acquires ultrasound waveform data at frequencies ranging from tens to hundreds of kHz in a controlled cold-lab environment. Two different LUS devices were compared in this study to determine which recorded more robust ultrasound in granular ice mix samples. We validated the ultrasound observations with poro-elastic traveltime modeling based on physical and empirical constitutive relationships, comparison to and replication of previous studies, and the use of other accredited snow property measurement systems, i.e., the SnowMicroPen. For ice mixes, we determined that the PSV-400 Scanning Vibrometer (Polytec GmbH) produces higher quality ultrasonic wavefield observations (i.e. has a better signal-to-noise ratio) than the VibroFlex Fiber Vibrometer (Polytec GmbH) in the lab conditions tested here. Using the PSV-400, we then demonstrate the utility of this new LUS to study the relationship between snow compression-wave speed and density during snow compaction experiments.
Date of Publication or Submission
2-29-2024
DOI
https://doi.org/10.18122/cryogars_snow_data.1.boisestate
Funding Citation
This research is based upon work supported in part by the National Science Foundation under Grant 1906160 and by the Cold Regions Research and Engineering Laboratory (CRREL). JCM is supported by the SMART Scholarship funded by: OUSD/R\&E (the Under Secretary of Defense Research and Engineering), National Defense Education Program (NDEP)/BA-1, Basic Research.
Single Dataset or Series?
Single Dataset
Data Format
*.xlsx; *.mat; *.svd; *.pnt; *.txt
File Size
14.8MB
Data Attributes
2 PFV datasets, 13 PSV datasets with 46 SMP datasets and its config file, and a *.csv file containing sample information. Along with 17 *.xlsx datasets that are Capelli et al. 2016 datasets split into individual datasets.
Time Period
20220128 - 20240117
Privacy and Confidentiality Statement
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Use Restrictions
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Disclaimer of Warranty
BOISE STATE UNIVERSITY MAKES NO REPRESENTATIONS ABOUT THE SUITABILITY OF THE INFORMATION CONTAINED IN OR PROVIDED AS PART OF THE SYSTEM FOR ANY PURPOSE. ALL SUCH INFORMATION IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND. BOISE STATE UNIVERSITY HEREBY DISCLAIMS ALL WARRANTIES AND CONDITIONS WITH REGARD TO THIS INFORMATION, INCLUDING ALL WARRANTIES AND CONDITIONS OF MERCHANTABILITY, WHETHER EXPRESS, IMPLIED OR STATUTORY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT.
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Recommended Citation
McCaslin, James Christopher; Mikesell, T. Dylan; and Marshall, Hans-Peter, "Dataset for a Laser Ultrasound System to Non-Invasively Measure Compression Waves in Granular Ice Mixes" (2024). CryoGARS Snow Data. 1.
https://scholarworks.boisestate.edu/cryogars_snow_data/1