Automating Error Quantification and Reduction for Computational Fluid Dynamics (CFD)

Award Information
Agency:
Department of Defense
Branch:
Air Force
Amount:
$99,995.00
Award Year:
2006
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-06-M-3630
Agency Tracking Number:
F061-233-0493
Solicitation Year:
2006
Solicitation Topic Code:
AF06-233
Solicitation Number:
2006.1
Small Business Information
COMBUSTION RESEARCH AND FLOW TECHNOLOGY,
6210 Keller's Church Road, Pipersville, PA, 18947
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
929950012
Principal Investigator
 Peter Cavallo
 Senior Research Scientist
 (215) 766-1520
 cavallo@craft-tech.com
Business Contact
 Neeraj Sinha
Title: Vice President & Technical Director
Phone: (215) 766-1520
Email: sinha@craft-tech.com
Research Institution
N/A
Abstract
Solution errors are inherent in any Computational Fluid Dynamics (CFD) simulation. Sources of error include spatial and temporal discretization, inadequacy or incapacity of physical models to capture complex fluid flow phenomena, and human errors in the setup and use of the CFD code. 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 very laborious and time intensive. Solution verification using Richardson extrapolation techniques has largely been limited to structured grid applications. To automate grid refinement studies and solution verification for unstructured meshes, and render such studies more practical, the proposed research program exploits an existing mesh adaptation package and recent advances in generalized Richardson extrapolation. The CRISP CFD® mesh adaptation code, used with several unstructured Navier-Stokes solvers including the Air Vehicles Unstructured Solver (AVUS), provides a viable path for automated mesh refinement and solution verification. In addition to solution verification studies, the proposed research will explore issues in mesh suitability and ways of addressing errors due to near wall resolution and human factors.

* information listed above is at the time of submission.

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