Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - Journal of Computational Physics, 2019 - Elsevier
Data-driven methods for improving turbulence modeling in Reynolds-Averaged Navier–
Stokes (RANS) simulations have gained significant interest in the computational fluid …
被引用次数：154 相关文章

Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - arXiv preprint arXiv:1807.02901, 2018 - arxiv.org
Data-driven methods for improving turbulence modeling in Reynolds-Averaged Navier-
Stokes (RANS) simulations have gained significant interest in the computational fluid …

[引用][C] Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - Journal of Computational Physics, 2019 - cir.nii.ac.jp
Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian
deep neural networks | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] …

Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - 2019 - dl.acm.org
Data-driven methods for improving turbulence modeling in Reynolds-Averaged Navier–
Stokes (RANS) simulations have gained significant interest in the computational fluid …

Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - Journal of Computational Physics (Print), 2019 - inis.iaea.org
[en] Highlights:• Propose a novel data-driven framework of model form uncertainty
quantification for turbulence models.• Develop a fully Bayesian deep neural network to …

Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

N Geneva, N Zabaras - Journal of Computational Physics, 2019 - ui.adsabs.harvard.edu
Data-driven methods for improving turbulence modeling in Reynolds-Averaged Navier-
Stokes (RANS) simulations have gained significant interest in the computational fluid …