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Jose, Basil and Hampp, Fabian (2023) Machine learning based spray process quantification. International Journal of Multiphase Flow, 172, p. 104702. Elsevier. doi: 10.1016/j.ijmultiphaseflow.2023.104702. ISSN 0301-9322.
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Official URL: https://dx.doi.org/10.1016/j.ijmultiphaseflow.2023.104702
| Item URL in elib: | https://elib.dlr.de/202113/ | ||||||||||||
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| Document Type: | Article | ||||||||||||
| Title: | Machine learning based spray process quantification | ||||||||||||
| Authors: |
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| Date: | 21 December 2023 | ||||||||||||
| Journal or Publication Title: | International Journal of Multiphase Flow | ||||||||||||
| Refereed publication: | Yes | ||||||||||||
| Open Access: | No | ||||||||||||
| Gold Open Access: | No | ||||||||||||
| In SCOPUS: | Yes | ||||||||||||
| In ISI Web of Science: | Yes | ||||||||||||
| Volume: | 172 | ||||||||||||
| DOI: | 10.1016/j.ijmultiphaseflow.2023.104702 | ||||||||||||
| Page Range: | p. 104702 | ||||||||||||
| Publisher: | Elsevier | ||||||||||||
| ISSN: | 0301-9322 | ||||||||||||
| Status: | Published | ||||||||||||
| Keywords: | Machine learning, spray characteristics | ||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||
| HGF - Program: | Aeronautics | ||||||||||||
| HGF - Program Themes: | Clean Propulsion | ||||||||||||
| DLR - Research area: | Aeronautics | ||||||||||||
| DLR - Program: | L CP - Clean Propulsion | ||||||||||||
| DLR - Research theme (Project): | L - Components and Emissions, E - Combustion and Power Plant Systems | ||||||||||||
| Location: | Stuttgart | ||||||||||||
| Institutes and Institutions: | Institute of Combustion Technology > Combustion Diagnostícs | ||||||||||||
| Deposited By: | Geigle, Dr. Klaus Peter | ||||||||||||
| Deposited On: | 22 Jan 2024 09:37 | ||||||||||||
| Last Modified: | 29 Jan 2024 13:07 |
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