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Campus Collection (Forschungszentrum Jülich GmbH)
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441 to 450 of 1,924 Results
test.py
Python Source Code - 2.0 KB - SHA-256: dfd8763a647d52c0a89b99cb50f0e364e9d203c37bb637e5d019a010f86f951f
variableSizedInput.cpython-38.pyc
Unknown - 4.2 KB - SHA-256: 00ae845485edf580cb6d012dc126bfff17ebbf3fe2aae6fd427b8b2ee200cf4b
variableSizedInput.py
Python Source Code - 7.1 KB - SHA-256: f09dae3c27eb1f6f788e6ad854c48dd6407232f79921fe2d2c8e10246209cf98
variableSizedPacking.cpython-38.pyc
Unknown - 10.2 KB - SHA-256: a816badc12311dd0f9f581dd86cb47e9f7f80a043695400990e4fe7b64b8efa3
variableSizedPacking.py
Python Source Code - 16.1 KB - SHA-256: ea8fd270adbdd962f2f68e3b0bf259a2876087cff50a3cd7df71aeb10d4ad474
workflow.sh
Shell Script - 326 B - SHA-256: 13ff32d8593add6cf3f5ba662732e88cef9cf252c7c7b301dd95c8fea3a52626
Experimental FZJ ParFlow DE06 hydrologic forecasts
May 14, 2024
Belleflamme, Alexandre; Hammoudeh, Suad; Görgen, Klaus; Kollet, Stefan, 2024, "Experimental FZJ ParFlow DE06 hydrologic forecasts", https://doi.org/10.26165/JUELICH-DATA/GROHKP, Jülich DATA, V1
The dataset entails experimental ParFlow hydrologic model forecast simulations by BELLEFLAMME, HAMMOUDEH, GOERGEN, and KOLLET. The basic setup and configuration is described in "Belleflamme et al. (2023): Hydrological forecasting at impact scale: the integrated ParFlow hydrologic...
Convection-permitting ICON-LAM Simulations for Renewable Energy Potential Estimates over Southern Africa
Mar 20, 2024
Chen, Shuying; Poll, Stefan; Hendricks Franssen, Harrie-Jan; Heinrichs, Heidi; Vereecken, Harry; Goergen, Klaus, 2024, "Convection-permitting ICON-LAM Simulations for Renewable Energy Potential Estimates over Southern Africa", https://doi.org/10.26165/JUELICH-DATA/JYGQ65, Jülich DATA, V1
This regional atmospheric modelling dataset was produced by a dynamical downscaling setup, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON-NWP) model v2.6.4 was run in limited area mode (ICON-LAM) with a weather forecast configuration (ICON-D2) from the G...
Simulation of CSDs for Automated Tuning Solutions (SimCATS)
Feb 27, 2024
Hader, Fabian; Fleitmann, Sarah; Fuchs, Fabian, 2024, "Simulation of CSDs for Automated Tuning Solutions (SimCATS)", https://doi.org/10.26165/JUELICH-DATA/QIUWRZ, Jülich DATA, V1
Simulation of CSDs for Automated Tuning Solutions (SimCATS) is a Python framework for simulating charge stability diagrams (CSDs) typically measured during the tuning process of qubits. Source code: https://github.com/f-hader/SimCATS Documentation: https://simcats.readthedocs.io/...
Load changes of a polymer electrolyte fuel cell under different operating conditions
Load changes of a polymer electrolyte fuel cell under different operating conditions
Feb 21, 2024
Froning, Dieter; Shi, Yan; Janßen, Holger; Lehnert, Werner, 2024, "Load changes of a polymer electrolyte fuel cell under different operating conditions", https://doi.org/10.26165/JUELICH-DATA/MLN4JX, Jülich DATA, V1
A lab scale polymer electrolyte fuel cell (PEFC) with a power of 9 W and an active area of 17.64 cm² was operated with 90% humidity and a stoichiometry factor of two in galvanostatic mode. Load cycles were applied to the PEFC, and the dynamic voltages were monitored. During the e...
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