Estimation of 2D pressure and cavitation fields from sparse pseudo-pressure sensor point data using super-resolution machine learning
Author:
Affiliation:
1. Department of Mechanical Engineering, Osaka University
Publisher
Japan Society of Mechanical Engineers
Link
https://www.jstage.jst.go.jp/article/transjsme/advpub/0/advpub_24-00115/_pdf
Reference23 articles.
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3. Coutier-Delgosha, O., Reboud, J. L. and Delannoy, Y., Numerical simulation of the unsteady behaviour of cavitating flows, International Journal of Numerical Method in Fluids, Vol.42 (2003), pp.527-548.
4. Coutier-Delgosha, O., Deniset, F., Astolfi, J. A. and Leroux, J. B., Numerical prediction of cavitating flow on a two-dimensional symmetrical hydrofoil and comparison to experiments, Journal of Fluids Engineering, Vol.129 (2007), pp.279-292.
5. Dong, C., Loy, C. C., He, K. and Tang, X., Image super-resolution using deep convolutional networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.38, No.2 (2016), pp.295-307.
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