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Uncertainty Quantification for Production Navier-Stokes Solvers Project

Summary

Type of release
a one-off release of a single dataset

Data Licence
Not Applicable

Content Licence
Creative Commons CCZero

Verification
automatically awarded

Release Date
9 April 2015
Modified Date
8 July 2015
Publishers
National Aeronautics and Space Administration
Keywords
completed, langley-research-center, project
Identifier
uncertainty-quantification-for-production-navier-stokes-solvers-project
Landing Page
http://techport.nasa.gov/view/8732
Maintainers
TECHPORT SUPPORT hq-techport@mail.nasa.gov
Language
en-US

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Description

Solution errors are inherent in any Computational Fluid Dynamics (CFD) simulation. Systematic identification, reduction, and control of these various error sources is crucial if the results of CFD simulations are to be trusted for design and performance assessment of air vehicles. While grid refinement studies may verify the spatial accuracy of a solution, these studies are generally laborious and time intensive. Continued development of a standalone Error Transport Equation (ETE) solver is proposed. The proposed program exploits an existing mesh adaptation and error quantification package, CRISP CFD<SUP>REG</SUP>, which currently interfaces with meshes and solutions from the NASA unstructured Navier-Stokes solvers FUN3D and USM3D. The Phase I effort will explore the use of ETE methodology with these production Navier-Stokes solvers as well as the popular structured grid code OVERFLOW. Improvements in error prediction for aerodynamic coefficients will be sought. In addition, the proposed program will address uncertainty quantification for turbulence models commonly used in computational aerodynamics applications. The ETE solver provides a promising, viable path for reliable error quantification and solution verification. This tool will provide numerical error bars, quantifiable levels of uncertainty in both local and globally integrated variables, for use in computational aerodynamics and other applications.


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