1 to 10 of 197 Results
Apr 18, 2024 - PN 1-X
Keim, Leon; Class, Holger, 2024, "Replication Code for: Rayleigh invariance allows the estimation of effective CO2 fluxes due to convective dissolution into water-filled fractures", https://doi.org/10.18419/darus-4089, DaRUS, V1
This dataset consists of software code associated with the publication titled "Rayleigh Invariance Enables Estimation of Effective CO2 Fluxes Resulting from Convective Dissolution in Water-Filled Fractures." It includes a Dockerimage that contains the precompiled code for immedia... |
Docker Image File - 1.6 KB -
MD5: 02160968dac8422e84745cac7a1d02d8
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TAR Archive - 3.1 GB -
MD5: 9a074fa2b0464eecbeced19a28299f90
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Nov 17, 2023 - DuMux
Buntic, Ivan; Coltman, Edward; Flemisch, Bernd; Ghosh, Tufan; Gläser, Dennis; Grüninger, Christoph; Hommel, Johannes; Keim, Leon; Kelm, Mathis; Koch, Timo; Kostelecky, Anna Mareike; Lipp, Melanie; Oukili, Hamza; Schneider, Martin; Utz, Martin; Wang, Yue; Weishaupt, Kilian; Wendel, Kai; Winter, Roman; Wu, Hanchuan, 2023, "DuMux 3.8.0", https://doi.org/10.18419/darus-3788, DaRUS, V1
Release 3.8.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environmen... |
Nov 17, 2023 -
DuMux 3.8.0
Gzip Archive - 33.9 MB -
MD5: 68ebdbd5b4c33852944e7a45f68caa43
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May 25, 2023 - Data and Code for: Meta-Uncertainty in Bayesian Model Comparison
Schmitt, Marvin, 2023, "Replication Code for: Meta-Uncertainty in Bayesian Model Comparison", https://doi.org/10.18419/darus-3514, DaRUS, V1, UNF:6:zUDr3KGdcaDCy+jFtcz8lA== [fileUNF]
This dataverse contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://doi.org/10.48550/arXiv.2210.07278 Note that the R code is structured as a package, thus requiring a local installation with subsequent loading via library(MetaUncertaintyPaper).... |
R Syntax - 26.5 KB -
MD5: 406e38f92fbf258e7b0dff76e476c307
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Unknown - 508 B -
MD5: efd4078885864b7ee481d7a750a7fc92
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R Syntax - 2.0 KB -
MD5: f118a5dd0ac9405176e3e031b22cfdba
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Jupyter Notebook - 268.9 KB -
MD5: 51ef505d165efcfb6df367a909152beb
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