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Acceleration of Modeling Capability for GDI Spray by Machine-Learning Algorithms

Cold start causes a high amount of unburned hydrocarbon and particulate matter emissions in gasoline direct injection (GDI) engines. Therefore, it is necessary to understand the dynamics of spray during a cold start and develop a predictive model to form a better air-fuel mixture in the combustion c...

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Principais autores: Yassine El Marnissi, Kyungwon Lee, Joonsik Hwang
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-11-01
Serier:Fluids
Fag:
machine learning
Gasoline Direct Injection (GDI)
projected liquid volume
tomographic reconstruction
Online adgang:https://www.mdpi.com/2311-5521/9/11/267
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