Application of Supervised Learning to Quantify Uncertainties in Turbulence and Combustion Modeling
Author:
Affiliation:
1. Stanford University
Publisher
American Institute of Aeronautics and Astronautics
Link
http://arc.aiaa.org/doi/pdf/10.2514/6.2013-259
Reference26 articles.
1. Bayesian uncertainty analysis with applications to turbulence modeling
2. Bayesian uncertainty quantification applied to RANS turbulence models
3. Uncertainty Quantification of Structural Uncertainties in RANS Simulations of Complex Flows
4. Modeling Structural Uncertainties in Reynolds-Averaged Computations of Shock/Boundary Layer Interactions
5. Laminar flamelet concepts in turbulent combustion
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