Leveraging Bayesian analysis to improve accuracy of approximate models
DOI10.1016/j.jcp.2019.05.015zbMath1453.62417arXiv1905.08227OpenAlexW2991889589WikidataQ127806718 ScholiaQ127806718MaRDI QIDQ2222288
Chiyu Jiang, Daniel Livescu, Balasubramanya T. Nadiga
Publication date: 26 January 2021
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1905.08227
Bayesian analysisneural networkturbulence modelingreduced order modelingsurrogate modelingReynolds-averaged Navier Stokes
Artificial neural networks and deep learning (68T07) Bayesian inference (62F15) Statistical turbulence modeling (76F55) Statistical solutions of Navier-Stokes and related equations (76D06)
Uses Software
Cites Work
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