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Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations.
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A. Vollant, G. Balarac, G. Geraci, C. Corre, Optimal estimator and artificial neural network as efficient tools for the subgrid-scale scalar flux modeling, Tech. rep., Proceedings of Summer Research Program, Center of Turbulence Research, Stanford University, Stanford, CA, USA (2014)
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2015
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H. Xiao, J.-L. Wu, J.-X. Wang, R. Sun, C. J. Roy, Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes equations: A data-driven, physics-based, Bayesian approach, Journal of Computational Physics 324 (2015) 115–136
2015
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K. Duraisamy, Z. J. Zhang, A. P. Singh, New approaches in turbulence and transition modeling using data-driven techniques, in: 53rd AIAA Aerospace Sciences Meeting, 2015, Kissimmee, FL, paper 2015-1284
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J.-X. Wang, J.-L. Wu, H. Xiao, Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data, Physical Review Fluids 2 (3) (2017) 034603
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A. P. Singh, S. Medida, K. Duraisamy, Machine-learning-augmented predictive modeling of turbulent separated flows over airfoils, AIAA Journal 55 (7) (2017) 2215–2227
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R. Maduta, S. Jakirlic, Improved RANS computations of flow over the 25°-slant-angle Ahmed body, SAE International Journal of Passenger Cars-Mechanical Systems 10 (2017-01-1523) (2017) 649–661
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A. N. Marques, Q. Wang, Y. Marzouk, Data-driven integral boundary-layer modeling for airfoil performance prediction in laminar regime, AIAA Journal (2017) 1–15
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A. Vollant, G. Balarac, C. Corre, Subgrid-scale scalar flux modelling based on optimal estimation theory and machine-learning procedures, Journal of Turbulence (2017) 1–25
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2017
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A. P. Singh, R. Matai, K. Duraisamy, P. Durbin, Data-driven augmentation of turbulence models for adverse pressure gradient flows, in: 23rd AIAA Computational Fluid Dynamics Conference, 2017, Denver, CO, paper 2017-3626
2017
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J.-L. Wu, J.-X. Wang, H. Xiao, J. Ling, A priori assessment of prediction confidence for data-driven turbulence modeling, Flow, Turbulence and Combustion 99 (2017) 25–46
2017
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P. Durbin, personal communication (2017)
2017
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S. Poroseva, Personal communication (2018)
2018
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2018
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