Using Machine Learning to Predict Synthetic Fuel Spray Penetration from Limited Experimental Data Without Computational Fluid Dynamics
In: Energy and Sustainable Futures: Proceedings of the 3rd ICESF, 2022; (2023) S. 51-59
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E-Book
Zugriff:
Titel: |
Using Machine Learning to Predict Synthetic Fuel Spray Penetration from Limited Experimental Data Without Computational Fluid Dynamics
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Autor/in / Beteiligte Person: | Richards, Bryn ; Emekwuru, Nwabueze ; Rashid, Muhammad H., Series Editor ; Kolhe, Mohan Lal, Series Editor ; Nixon, Jonathan D. [Ed.] ; Al-Habaibeh, Amin [Ed.] ; Vukovic, Vladimir [Ed.] ; Asthana, Abhishek [Ed.] |
Quelle: | Energy and Sustainable Futures: Proceedings of the 3rd ICESF, 2022; (2023) S. 51-59 |
Veröffentlichung: | 2023 |
Medientyp: | E-Book |
ISBN: | 978-3-031-30959-5 (print) ; 978-3-031-30960-1 (print) |
DOI: | 10.1007/978-3-031-30960-1_6 |
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