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Recent progress in augmenting turbulence models with physics-informed machine learning 被引量:4
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作者 Xinlei Zhang Jinlong Wu +1 位作者 Olivier Coutier-Delgosha Heng Xiao 《Journal of Hydrodynamics》 SCIE EI CSCD 2019年第6期1153-1158,共6页
In view of the long stagnation in traditional turbulence modeling,researchers have attempted using machine learning to augment turbulence models.This paper presents some of the recent progresses in our group on augmen... In view of the long stagnation in traditional turbulence modeling,researchers have attempted using machine learning to augment turbulence models.This paper presents some of the recent progresses in our group on augmenting turbulence models with physics-informed machine learning.We also discuss our works on ensemble-based field inversion to provide training data for constructing machine learning models.Future and on-going research efforts are introduced. 展开更多
关键词 Machine learning turbulence modeling data-driven modeling model uncertainty
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