Computational Fluid Dynamics Comparison and Flight Test Measurement of F-5E Off-Body Pressures

2005 ◽  
Author(s):  
Keith Meredith ◽  
John Dahlin ◽  
David Graham ◽  
Michael Malone ◽  
Edward Haering ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Flight Test ◽  
Test Measurement

Computational Fluid Dynamics–Computational Structural Dynamics Rotor Coupling Using an Unstructured Reynolds-Averaged Navier–Stokes Methodology

2012 ◽  
Vol 57 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Jennifer N. Abras ◽  
C. Eric Lynch ◽  
Marilyn J. Smith
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Structural Dynamics ◽  
Flight Test ◽  
Navier Stokes ◽  
Structured Grid ◽  
Direct Contrast ◽  
Computational Structural Dynamics ◽  
Computational Fluid Dynamics Cfd ◽  
Grid Points

The focus of this paper is to discuss the unique challenges introduced through the use of unstructured grids in rotorcraft computational fluid dynamics (CFD)–computational structural dynamics (CSD) coupling. The use of unstructured grid methodology in CFD has been expanding because of the advantages in grid generation and modeling of complex configurations. However, the resulting amorphous distribution of the grid points on the rotor blade surface provides no information with regard to the orientation of the blade, in direct contrast to structured grid methodology that can take advantage of the ordered mapping of points to identify the orientation as well as simplifying airloads integration. A methodology has been developed and is described here, which now permits unstructured methods to be utilized for elastic rotary-wing simulations. This methodology is evaluated through comparison of the UH60A rotor with available flight test data for forward flight.

scholarly journals Computational fluid dynamics trimming of helicopter rotor in forward flight

2020 ◽  
Vol 12 (5) ◽  
pp. 168781402092525 ◽  
Author(s):  
Chenglong Zhou ◽  
Ming Chen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Test Data ◽  
Pitch Angle ◽  
Flight Test ◽  
Helicopter Rotor ◽  
Main Rotor ◽  
Forward Flight ◽  
Thrust Coefficient ◽  
Moment Coefficient

A computational fluid dynamics (CFD) trimming method based on wind tunnel and flight test data is proposed. Aerodynamic coefficients obtained for a helicopter rotor using this method were compared with both experimental data from a test report and CFD results based on the control parameters that were reported in the same document. The method applies small disturbances to the collective pitch angle, the lateral cyclic pitch angle and the longitudinal cyclic pitch angle of the helicopter’s main rotor during forward flight to analyze the effects of each disturbance on the thrust coefficient, the pitching moment coefficient and the rolling moment coefficient of the rotor. Then, by solving a system of linear equations, the collective pitch angle, the lateral cyclic pitch angle and the longitudinal cyclic pitch angle of the main rotor in the CFD trim state are obtained. The AH-1G rotor is used in this paper. NASA has conducted a comprehensive flight test program on this model and has published detailed test reports. Using this method, the pitch moment and the roll moment can be corrected to almost zero and the calculated thrust coefficient is more consistent with the test data when compared with results from direct CFD simulations.

Comparison of flight test data with a computational fluid dynamics model of a Scottish Aviation Bulldog aircraft

2013 ◽  
Vol 117 (1198) ◽  
pp. 1273-1291 ◽  
Author(s):  
N. J. Lawson ◽  
N. Salmon ◽  
J. E. Gautrey ◽  
R. Bailey
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Test Data ◽  
Laser Scanner ◽  
Flight Test ◽  
Test Methods ◽  
Surface Model ◽  
Cfd Model ◽  
Ansys Fluent ◽  
Lift And Drag

Abstract The following paper presents detailed aerodynamic data of a Scottish Aviation Bulldog light aircraft. The data is taken from the pre-stall region of the aircraft flight envelope through two flight test methods and from a geometrically accurate computational fluid dynamics (CFD) model of the full scale aircraft, which was meshed in Ansys ICEM CFD and solved in Ansys Fluent. The fidelity of the CFD model was achieved by development of a CATIA solid model with surfaces matching a spatial point cloud of the aircraft taken using a 3D laser scanner. Following a CFD verification process, a 3·4m hybrid mesh with a Spalart-Allmaras (SA) turbulence model was found to give the best overall lift and drag characteristics. Further detailed comparisons with the glide flight test data showed the CFD drag polar to have 63% lower zero lift drag, although this discrepancy was related to the simplification of the original CATIA surface model, which excluded the undercarriage, aerials and other protuberance drags. Inclusion of estimates of these sources of drag resulted in a match in zero lift drag to within 15% and a maximum lift to drag of 10:1 which was within 11% of the glide flight test result. The remaining drag discrepancy is attributed to other effects including trim drag and the surface finish of the actual aircraft.

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