Deep feature learning of in-cylinder flow fields to analyze cycle-to-cycle variations in an SI engine,International Journal of Engine Research

当前位置： X-MOL 学术 › Int. J. Engine Res. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Deep feature learning of in-cylinder flow fields to analyze cycle-to-cycle variations in an SI engine
International Journal of Engine Research ( IF 2.5 ) Pub Date : 2020-12-04 , DOI: 10.1177/1468087420974148
Daniel Dreher ₁ , Marius Schmidt ₂ , Cooper Welch ₂ , Sara Ourza _{1,

2} , Samuel Zündorf ₁ , Johannes Maucher ₃ , Steven Peters ₁ , Andreas Dreizler ₂ , Benjamin Böhm ₂ , Alexander Hanuschkin ₁

Affiliation

Machine learning (ML) models based on a large data set of in-cylinder flow fields of an IC engine obtained by high-speed particle image velocimetry allow the identification of relevant flow structu...

中文翻译：