Physics-constrained bayesian neural network for fluid flow reconstruction with sparse and noisy data
ABSTRACT: In many applications, flow measurements are usually sparse and possibly noisy. The reconstruction of a high-resolution flow field from limited and imperfect flow information is significant yet challenging. In this work, we propose an innovative physics-constrained Bayesian deep learning ap...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-03-01
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| Series: | Theoretical and Applied Mechanics Letters |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095034920300295 |