Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks

Tomographic background oriented Schlieren (Tomo-BOS) imaging measures density or temperature fields in three dimensions using multiple camera BOS projections, and is particularly useful for instantaneous flow visualizations of complex fluid dynamics problems. We propose a new method based on physics...

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Vydáno v:	Journal of fluid mechanics Ročník 915
Hlavní autoři:	Cai, Shengze, Wang, Zhicheng, Fuest, Frederik, Jeon, Young Jin, Gray, Callum, Karniadakis, George Em
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 25.03.2021
Témata:	Algorithms Coffee computational methods convection Data Datasets Deep learning Dimensions Experiments Fluid dynamics Fluid flow Fluid mechanics Heat transfer Hydrodynamics Imaging Imaging techniques Inference JFM Papers machine learning MATHEMATICS AND COMPUTING Neural networks Partial differential equations Physics Pressure Temperature distribution Temperature fields Velocity Velocity distribution Visualization computational methods convection machine learning
ISSN:	0022-1120, 1469-7645
On-line přístup:	Získat plný text
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