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    <identifier>10.11922/sciencedb.01597</identifier>
    <datestamp>2022-03-17T17:32:31Z</datestamp>
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  <dc:date>2022-03-17</dc:date>
  <dc:title>Ice in granular media</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.01597</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description># Ice in granular mediaMatlab scripts to simulate the undercooling of ice in granular media, for the publication [_A Monte Carlo Approach to Approximating the Effects of Pore Geometry on the Phase Behavior of Soil Freezing_](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020MS002117). The functions are organized in serveral classes, including:- `mc.m`. Perform Monte Carlo simulations given the synthetic sediment model (in `.mat` format containing a four-column array of particle positions and radii), number of test points, simulation name, scale of simulation region, and provide some analysis tools.- `grow.m`. Calculate the maximum inscribed sphere between particles encompassing the test point using a 'nudge-and-bulge' algorithm, as well as the Apollonian circle for the throat and crevice calculation.- `sediment.m`. Some tools to analyze the synthetic sediment model.- `undercooling.m`. Use the Gibbs-Thomson equation to calculate the undercoolings caused by curvatures, and calculate the colligative effect of salts using the ZSR model.- `freezing.m`. Compare the results against experiments and field measurements.- `bubbleplot3.m`. A script by [Peter Bodin](https://www.mathworks.com/matlabcentral/fileexchange/8231-bubbleplot3) for easier visualization of multiple spheres, used in `grow.m`.- `line_fewer_markers.m`. A script by [Massimo Ciacci](https://www.mathworks.com/matlabcentral/fileexchange/42560-line_fewer_markers) for plotting curves with better control of markers.Parameters for calculations are in:- `data/colligative.xlsx`. An Excel file contains all ZSR coefficients used to calculate the undercooling of chlorides.- `param.json`. A file contains all other relevant parameters used in the simulation.- `data/soil`. Some digitized measurements from literatures we compare our simulation results against.Examples of simulated results are in `data/mc`.</dc:description>
  <dc:subject>Ice; Undercooling; Monte Carlo; Gibbs-Thomson</dc:subject>
  <dc:creator>Jiangzhi Chen</dc:creator>
  <dc:creator>Shenghua Mei</dc:creator>
  <dc:creator>Julia T. Irizarry</dc:creator>
  <dc:creator>Alan W. Rempel</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1029/2020MS002117</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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