Magister UT Burner CFX droplet dataset
doi:10.4121/19355288.v2
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/19355288
doi: 10.4121/19355288
Datacite citation style:
Ghasemi Khourinia, Alireza; Kok, Jim (2022): Magister UT Burner CFX droplet dataset. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/19355288.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2022-06-28 (latest)
version 1 - 2022-03-16
Simulation dataset corresponding to droplet evolution within Magister UT Burner. Corresponding to MAGISTER project ESR 7
history
- 2022-03-16 first online
- 2022-06-28 published, posted
publisher
4TU.ResearchData
format
HF5
references
funding
- The authors would like to acknowledge the funding of this research by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 766264
- Machine learning for Advanced Gas turbine Injection SysTems to Enhance combustoR performance. (grant code 766264) [more info...] European Commission
organizations
University of Twente, Faculty of Engineering Technology (ET), Thermal Engineering (TE)
DATA
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- 710 bytesMD5:
2fb3184f6015f94237ac3569b5ca5146
README.md - 247,362,032 bytesMD5:
19cbffe2033e4a16efa176cbf28b306a
UTBurner_Droplets_Sim.h5 -
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