Snow Micro-Structure Model ...

PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model imp...

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Bibliographic Details
Main Author: Micah Johnson, Andrew
Format: Article in Journal/Newspaper
Language:English
Published: Idaho National Laboratory (INL), Idaho Falls, ID (United States) 2014
Subjects:
Online Access:https://dx.doi.org/10.11578/dc.20171025.5003
https://www.osti.gov/doecode/biblio/6416
id ftdatacite:10.11578/dc.20171025.5003
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spelling ftdatacite:10.11578/dc.20171025.5003 2023-08-27T04:10:02+02:00 Snow Micro-Structure Model ... Micah Johnson, Andrew 2014 https://dx.doi.org/10.11578/dc.20171025.5003 https://www.osti.gov/doecode/biblio/6416 en eng Idaho National Laboratory (INL), Idaho Falls, ID (United States) Snow Micro-Structure Model SoftwareSourceCode Software article 2014 ftdatacite https://doi.org/10.11578/dc.20171025.5003 2023-08-07T14:24:23Z PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore ... Article in Journal/Newspaper Ice Sheet DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore ...
format Article in Journal/Newspaper
author Micah Johnson, Andrew
spellingShingle Micah Johnson, Andrew
Snow Micro-Structure Model ...
author_facet Micah Johnson, Andrew
author_sort Micah Johnson, Andrew
title Snow Micro-Structure Model ...
title_short Snow Micro-Structure Model ...
title_full Snow Micro-Structure Model ...
title_fullStr Snow Micro-Structure Model ...
title_full_unstemmed Snow Micro-Structure Model ...
title_sort snow micro-structure model ...
publisher Idaho National Laboratory (INL), Idaho Falls, ID (United States)
publishDate 2014
url https://dx.doi.org/10.11578/dc.20171025.5003
https://www.osti.gov/doecode/biblio/6416
genre Ice Sheet
genre_facet Ice Sheet
op_doi https://doi.org/10.11578/dc.20171025.5003
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