Data from: Dynamic models for impact-initiated stress waves through snow columns
Cite this dataset
Verplanck, Samuel (2024). Data from: Dynamic models for impact-initiated stress waves through snow columns [Dataset]. Dryad. https://doi.org/10.5061/dryad.ngf1vhj1b
Abstract
The objective of this research is to model snow’s response to dynamic, impact loading. Two constitutive relationships are considered: elastic and Maxwell-viscoelastic. These material models are applied to laboratory experiments consisting of 1000 individual impacts across 22 snow column configurations. The columns are 60 cm tall with a 30 cm by 30 cm cross-section. The snow ranges in density from 135-428 kg m-3 and is loaded with both short-duration (~1 ms) and long-duration (~10 ms) impacts. The Maxwell-viscoelastic model more accurately describes snow’s response because it contains a mechanism for energy dissipation, which the elastic model does not. Furthermore, the ascertained model parameters show a clear dependence on impact duration; shorter duration impacts resulted in higher wave speeds and greater damping coefficients. The stress wave’s magnitude is amplified when it hits a stiffer material because of the positive interference between incident and reflected waves. This phenomenon is observed in the laboratory and modeled with the governing equations.
README: Dynamic models for impact-initiated stress waves through snow columns
https://doi.org/10.5061/dryad.ngf1vhj1b
This dataset contains supporting information for the Journal of Glaciology paper titled "Dynamic models for impact-initiated stress waves through snow columns" authored by S.V. Verplanck and E.E. Adams.
Description of the data and file structure
The scripts to run the models are in two folders: "FD Model" and "FE Model". The finite difference (FD) model is scripted and executed Matlab R2023A. The finite element (FE) model is scripted in Python and executed in Abaqus 2022.
The "FD Model" folder contains a pdf with detailed documentation of the finite difference method implementation. This file is called "FD_Documention.pdf". There is also a top level matlab script titled "runModel.m" which calls "wave_1D.m".
The "FE Model" folder contains 12 python scripts. The filenaming convention is "loop_" + "longDur" or "shortDur" + "E" or "VE" + "low" or "mid" or "high". The permutations of this naming convention is short or long duration, elastic or viscoelastic model, and low, middle, or high drop height. The two csv files are called by these scripts and contain model parameters.
The scripts to generate figures are in a folder titled "Figure generation scripts" folders with their figure title. The top level script in each sub-folder is titled "generateFigureX.m" where X is the figure number. See the comments in each figure generation script for more details.
All considered regressions are in the "Regressions" folder. The four xlsx files in this folder are show all considered regressions for the two parameters (E or eta) and the two durations (short or long).
Table S1, the details for each snow test, is in the file "TableS1_detailedSnowTests.xlsx"
Sharing/Access information
All data was generated and processed by the authors. Thus, linking to other sources of data is not applicable. It is only hosted in this Dryad repository and no other publicly available locations.
Code/Software
See the description of data and file structure section of the README.
Methods
Collected in the Subzero Research Laboratory at Montana State University and processed with various Python and Matlab scripts.
Funding
Montana State University, Civil and Mechanical Engineering Departments
American Avalanche Association