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
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
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version 2 - 2022-06-28 (latest)
version 1 - 2022-03-16
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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
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

files (2)