25,381 to 25,390 of 25,658 Results
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Gzip Archive - 6.1 MB -
MD5: 49693609843e40a31f4db34ff1f14f34
Tutorial cases for preCICE with real solvers |
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Gzip Archive - 246.3 KB -
MD5: 92f8d58b4fd50dfad6d2f8b26bb6a6c2
preCICE adapter for the CFD code SU2 |
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Gzip Archive - 18.1 MB -
MD5: 2a8e313707b168fe3e3bb3958c08fa1e
preCICE website including documentation sources |
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Markdown Text - 775 B -
MD5: 224e7f49c62d47fc695e22674751baa7
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Sep 27, 2021 -
preCICE Distribution Version v2104.0
Adobe PDF - 3.8 MB -
MD5: 5a0272ed0391ce2c2812f912a10e00a2
Offline PDF version of the preCICE documentation |
Sep 27, 2021 - Usability and Sustainability of Simulation Software
Chourdakis, Gerasimos; Davis, Kyle; Rodenberg, Benjamin; Schulte, Miriam; Simonis, Frédéric; Uekermann, Benjamin; Abrams, Georg; Bungartz, Hans-Joachim; Cheun Yau, Lucia; Desai, Ishaan; Eder, Konrad; Hertrich, Richard; Lindner, Florian; Rusch, Alexander; Sashko, Dmytro; Schneider, David; Totounferoush, Amin; Volland, Dominik; Vollmer, Peter; Ziya Koseomur, Oguz, 2021, "preCICE Distribution Version v2104.0", https://doi.org/10.18419/DARUS-2125, DaRUS, V1
The preCICE distribution is the larger ecosystem around preCICE, which includes the core library, language bindings, adapters for popular solvers, tutorials, and vagrant files to prepare a virtual machine image. The compressed source files of this data set are only meant to archive this specific version v2104.0 of the distribution. If you want to u... |
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Gzip Archive - 1.3 MB -
MD5: 154441d32e6be58b991e9fe755da1b62
The actual coupling library |
Sep 27, 2021 -
preCICE Distribution Version v2104.0
Gzip Archive - 75.6 KB -
MD5: 49c8f2737e907db71ad04fd3c06c8e5b
preCICE adapter for the FEM library FEniCS |
Sep 10, 2021 - PN 6-4
Munz, Tanja; Garcia, Rafael; Weiskopf, Daniel, 2021, "Visual Analytics System for Hidden States in Recurrent Neural Networks", https://doi.org/10.18419/DARUS-2052, DaRUS, V1
Source code of our visual analytics system for the interpretation of hidden states in recurrent neural networks. This project contains source code for preprocessing data and the visual analytics system. Additionally, we added precomputed data for immediate use in the visual analysis system. The sub directories contain the following: dataPreparation... |
