421 to 430 of 4,807 Results
RAR Archive - 1.2 MB -
MD5: f7b0263b7790608d77785a77615cade3
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Nov 19, 2024 -
Replication Data for: Iaroslavtceva et al. "A consistent MMC-LES approach for turbulent premixed flames" (2024) Proc. Combust. Inst.
Gzip Archive - 41.1 GB -
MD5: 5ccccbc597c91e3582a8f9c0a38a31b3
Cases data. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 93.8 MB -
MD5: f35d5d39cff97cf36e09f9b22886bca5
Input data and results of POREMAPS and DUMUX for the Cylinder in channel domain. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 91.2 MB -
MD5: dea4f87121abc8de16a4bc24a1d84d40
Input data and results of POREMAPS and DUMUX for the Single Precipitate domain. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 3.3 GB -
MD5: 37a1ff71830aa042ab364b099c2b9f5d
Input data and results of POREMAPS and DUMUX for Segment 1. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 3.5 GB -
MD5: b089128223f7de5f4b92c9a965da446f
Input data and results of POREMAPS and DUMUX for the Segment 2. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 2.3 GB -
MD5: 2ab48092170a214fbe40291be774063c
Input data and results of POREMAPS and DUMUX for the Segment 3. |
Nov 19, 2024 -
Results for pseudo-3D Stokes simulations with a geometry-informed drag term formulation for porous media with varying apertures
Gzip Archive - 664.1 KB -
MD5: 57754fe1779bd4e7e18b636292d15f90
Condensed results/permeabilities for all domains including ploting scripts to replicate figures in Krach et al. |
Nov 19, 2024 -
Models and Prepared Datasets for Convolutional Long Short-Term Memory (ConvLSTM) Networks
ZIP Archive - 24.0 MB -
MD5: 228335dc8359943d20c0c623f967818d
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Nov 19, 2024 -
Models and Prepared Datasets for Convolutional Long Short-Term Memory (ConvLSTM) Networks
ZIP Archive - 19.5 MB -
MD5: d394595b346b14002a47239b475b7c64
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