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Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary
  Layers using Physics-Informed Machine Learning

Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning

19 August 2018
Jian-Xun Wang
Junji Huang
L. Duan
Heng Xiao
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning"

8 / 8 papers shown
Implicit Neural Differential Model for Spatiotemporal Dynamics
Implicit Neural Differential Model for Spatiotemporal Dynamics
Deepak Akhare
P. Du
Tengfei Luo
Jian-Xun Wang
PINNAI4CE
276
1
0
03 Apr 2025
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid
  Neural Modeling
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling
Deepak Akhare
Tengfei Luo
Jian-Xun Wang
319
11
0
30 Dec 2023
Emerging trends in machine learning for computational fluid dynamics
Emerging trends in machine learning for computational fluid dynamics
Ricardo Vinuesa
Steve Brunton
AI4CE
195
24
0
28 Nov 2022
Real-time simulation of parameter-dependent fluid flows through deep
  learning-based reduced order models
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models
S. Fresca
Andrea Manzoni
AI4CE
206
49
0
10 Jun 2021
Uncertainty Quantification of Locally Nonlinear Dynamical Systems using
  Neural Networks
Uncertainty Quantification of Locally Nonlinear Dynamical Systems using Neural NetworksJournal of computing in civil engineering (J. Comput. Civ. Eng.), 2020
Subhayan De
166
10
0
11 Aug 2020
Modeling Stochastic Microscopic Traffic Behaviors: a Physics Regularized
  Gaussian Process Approach
Modeling Stochastic Microscopic Traffic Behaviors: a Physics Regularized Gaussian Process Approach
Yun Yuan
Qinzheng Wang
X. Yang
157
10
0
17 Jul 2020
Explainable Machine Learning for Scientific Insights and Discoveries
Explainable Machine Learning for Scientific Insights and DiscoveriesIEEE Access (IEEE Access), 2019
R. Roscher
B. Bohn
Marco F. Duarte
Jochen Garcke
XAI
558
810
0
21 May 2019
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of
  Airfoil Flows
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
Nils Thuerey
Konstantin Weissenow
L. Prantl
Xiangyu Y. Hu
AI4CE
467
489
0
18 Oct 2018
1
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