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A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media
Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical pro...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530238/ https://www.ncbi.nlm.nih.gov/pubmed/36192410 http://dx.doi.org/10.1038/s41597-022-01664-0 |
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author | Santos, Javier E. Chang, Bernard Gigliotti, Alex Yin, Ying Song, Wenhui Prodanović, Maša Kang, Qinjun Lubbers, Nicholas Viswanathan, Hari |
author_facet | Santos, Javier E. Chang, Bernard Gigliotti, Alex Yin, Ying Song, Wenhui Prodanović, Maša Kang, Qinjun Lubbers, Nicholas Viswanathan, Hari |
author_sort | Santos, Javier E. |
collection | PubMed |
description | Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation. |
format | Online Article Text |
id | pubmed-9530238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-95302382022-10-05 A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media Santos, Javier E. Chang, Bernard Gigliotti, Alex Yin, Ying Song, Wenhui Prodanović, Maša Kang, Qinjun Lubbers, Nicholas Viswanathan, Hari Sci Data Data Descriptor Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation. Nature Publishing Group UK 2022-10-03 /pmc/articles/PMC9530238/ /pubmed/36192410 http://dx.doi.org/10.1038/s41597-022-01664-0 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Santos, Javier E. Chang, Bernard Gigliotti, Alex Yin, Ying Song, Wenhui Prodanović, Maša Kang, Qinjun Lubbers, Nicholas Viswanathan, Hari A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title | A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title_full | A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title_fullStr | A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title_full_unstemmed | A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title_short | A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media |
title_sort | dataset of 3d structural and simulated transport properties of complex porous media |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530238/ https://www.ncbi.nlm.nih.gov/pubmed/36192410 http://dx.doi.org/10.1038/s41597-022-01664-0 |
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