Institute of Aerodynamics and Gas Dynamics

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

21 to 30 of 374 Results

example_access_data_h5py.py Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Python Source Code - 3.8 KB - MD5: 8ef2f3dd7a9abc9258bcdfa999619efa Example script for how to access data in python using h5py API
ztmd_pgc.h5 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Hierarchical Data Format - 501.3 MB - MD5: 2ee6197cfe88567d6b69c047d2578789 HDF5 data file for case PG-C
ztmd_pgc.xmf2 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Unknown - 16.3 KB - MD5: 17f641ad6d3bb9c2052ec4376130899d ParaView XML companion file for ztmd_pgc.h5
ztmd_pgf.h5 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Hierarchical Data Format - 393.3 MB - MD5: 78172ea4568d5ed9b66fe66302083ac2 HDF5 data file for case PG-F
ztmd_pgf.xmf2 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Unknown - 15.3 KB - MD5: e47558b55ecb09af0c68b0f7627f9e1a ParaView XML companion file for ztmd_pgf.h5
ztmd_zpgc.h5 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Hierarchical Data Format - 522.9 MB - MD5: a04ed189245183ad534b3c93d93e7f2d HDF5 data file for case ZPG-C
ztmd_zpgc.xmf2 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Unknown - 16.3 KB - MD5: c577f96636a8f35a6ad851b4f4a3c7b1 ParaView XML companion file for ztmd_zpgc.h5
ztmd_zpgf.h5 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Hierarchical Data Format - 393.3 MB - MD5: 45a41070308e3c40ce4162b57364ad71 HDF5 data file for case ZPG-F
ztmd_zpgf.xmf2 Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers Unknown - 15.4 KB - MD5: a2384ad99a2c558066f39ed282f17272 ParaView XML companion file for ztmd_zpgf.h5
GALÆXI Verification: Convergence Tests May 3, 2024 - Supplementary Data: GALÆXI Paper Kurz, Marius; Kempf, Daniel; Blind, Marcel P.; Kopper, Patrick; Offenhäuser, Philipp; Schwarz, Anna; Starr, Spencer; Keim, Jens; Beck, Andrea, 2024, "GALÆXI Verification: Convergence Tests", https://doi.org/10.18419/DARUS-4155, DaRUS, V1, UNF:6:vL1WFzY+Nmd1P5y9jFLWLg== [fileUNF] This Dataset contains the setup and the results of the convergence tests which are reported in the GALÆXI Paper (Section 5.1). The results are contained in the file results.txt. The used case is based on the method of manufactured solution. The detailed formulation is specified in Hindenlang et al. and is implemented as ExactFunc=4 in GALÆXI. The f...

example_access_data_h5py.py

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Python Source Code - 3.8 KB -

Example script for how to access data in python using h5py API

ztmd_pgc.h5

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Hierarchical Data Format - 501.3 MB -

HDF5 data file for case PG-C

ztmd_pgc.xmf2

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Unknown - 16.3 KB -

ParaView XML companion file for ztmd_pgc.h5

ztmd_pgf.h5

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Hierarchical Data Format - 393.3 MB -

HDF5 data file for case PG-F

ztmd_pgf.xmf2

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Unknown - 15.3 KB -

ParaView XML companion file for ztmd_pgf.h5

ztmd_zpgc.h5

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Hierarchical Data Format - 522.9 MB -

HDF5 data file for case ZPG-C

ztmd_zpgc.xmf2

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Unknown - 16.3 KB -

ParaView XML companion file for ztmd_zpgc.h5

ztmd_zpgf.h5

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Hierarchical Data Format - 393.3 MB -

HDF5 data file for case ZPG-F

ztmd_zpgf.xmf2

Jul 19, 2024 - Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers

Unknown - 15.4 KB -

ParaView XML companion file for ztmd_zpgf.h5

GALÆXI Verification: Convergence Tests

May 3, 2024 - Supplementary Data: GALÆXI Paper

Kurz, Marius; Kempf, Daniel; Blind, Marcel P.; Kopper, Patrick; Offenhäuser, Philipp; Schwarz, Anna; Starr, Spencer; Keim, Jens; Beck, Andrea, 2024, "GALÆXI Verification: Convergence Tests", https://doi.org/10.18419/DARUS-4155, DaRUS, V1, UNF:6:vL1WFzY+Nmd1P5y9jFLWLg== [fileUNF]

This Dataset contains the setup and the results of the convergence tests which are reported in the GALÆXI Paper (Section 5.1). The results are contained in the file results.txt. The used case is based on the method of manufactured solution. The detailed formulation is specified in Hindenlang et al. and is implemented as ExactFunc=4 in GALÆXI. The f...

Add Data

Share Dataverse

Link Dataverse

Reset Modifications