cfd computations for nasa trap wing using the code hifun · introductiontypical gridsresults: case...
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
CFD computations for NASA TRAP
WING using the code HiFUN
Ravindra K., Nikhil Vijay Shende & N. BalakrishnanComputational Aerodynamics Laboratory,
Department of Aerospace Engineering,Indian Institute of Science, Bangalore 560012
First AIAA High Lift Prediction Workshop, Chicago, ILJune 26–27, 2010
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 1/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
1 Introduction
2 Typical grids
3 Results: Case 1–Grid convergence
4 Conclusions
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 2/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
1 Introduction
2 Typical grids
3 Results: Case 1–Grid convergence
4 Conclusions
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 3/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Introduction
Tools employed
Grid generation for NASA TRAP WING is carried outusing GAMBIT and TGRID, commercial grid generatorsfrom ANSYS available at Supercomputer Education andResearch Centre (SERC), IISc.
Flow computations for TRAP WING are performed usingthe code HiFUN, a commercial flow solver fromSimulation and Innovation Engineering Solutions (SandI)available at CAd Lab, Department of AerospaceEngineering, IISc.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Introduction continued
Tools employed continued
Post-processing is carried out using TECPLOT availableat SERC, IISc.
The compute platform used in the present study is IBMBlue Gene available at SERC, IISc. Hardware details ofBlue Gene are as follows:
4096 2-way SMP nodes (8192 processors)IBM PowerPC 440x5 processors operating at 700 Mhz32-bit1 GB main memory per node with a total of 4 TB forthe clusterGigabit network with Cisco 6500 Gigabit switch.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Features of code HiFUNHiFUN: HIgh Resolution Flow Solver on UNstructured Meshes
Algorithmic features
Unstructured cell centre finite volume methodology.
Higher order accuracy: linear reconstruction procedure.
Flux limiting: Venkatakrishnan Limiter.
Inviscid flux computation: Roe scheme.
Convergence acceleration: matrix free symmetric GaussSeidel relaxation procedure.
The viscous flux discretization: Green–Gauss theorembased diamond path reconstruction.
Eddy viscosity computation: Spalart Allmaras TM.
Parallelization: MPI.
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 6/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
1 Introduction
2 Typical grids
3 Results: Case 1–Grid convergence
4 Conclusions
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Surface grids
Coarse Medium FineField cells: 7695034 21903245 63305904
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Surface grids, tip zoomed view
Coarse Medium Fine
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Configuration 1: Grid details
Grid details
Grid Type Coarse Medium FineField Nodes 3088347 8188411 22419724Field Cells 7695034 21903245 63305904
Boundary Nodes 135004 236077 527552Boundary Faces 263557 459285 1035372BL 1st–Cell (in) 0.00020 0.00013 0.00009
BL Cells 21 31 36
Note
Boundary layer is grown using aspect ratio based algorithm.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Computational details
Resource details
Grid: Medium grid for configuration 1 with about 21million field cells
Computer Platform: Blue Gene with IBM PowerPCprocessors
Operating system: Unix
Compiler: XL FORTRAN 90
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Computational details continued
Resource details continued
Number of processors: 128
Memory requirement of HiFUN: Approximately 800 MBper million of grid size
Convergence criterion: 9–10 decades fall in energy residuewith change in drag count over 100 iterations to be lessthan 1
Number of iterations: Typically 6000–8000
Run time Wall clock: 60–80 hours
Expected run time on 128 nodes of a Xeon based cluster:15–20 hours (based on our our experience in SPICES–09)
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
1 Introduction
2 Typical grids
3 Results: Case 1–Grid convergence
4 Conclusions
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 14/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Overall viewM∞ = 0.2,Re∞ = 4.3 million, α = 13o
Coarse Medium Fine
With grid refinement, a significant difference in separationpattern can be seen on the body pod above the flap.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Main elementM∞ = 0.2,Re∞ = 4.3 million, α = 13o
Coarse Medium Fine
Flow on main element is predominantly chord–wise.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Flap–body podM∞ = 0.2,Re∞ = 4.3 million, α = 13o
Coarse Medium Fine
The bubble at flap–body pod junction grows in size with gridrefinement.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Tip regionM∞ = 0.2,Re∞ = 4.3 million, α = 13o
Coarse Medium Fine
The span-wise extent and chord-wise position ofseparation line on the flap upper surface does not changewith grid refinement.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 19/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Overall viewM∞ = 0.2,Re∞ = 4.3 million, α = 28o
Coarse Medium Fine
The complex flow over body pod exhibits multiple separationand re-attachment lines.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Main elementM∞ = 0.2,Re∞ = 4.3 million, α = 28o
Coarse Medium Fine
Flow on main element is predominantly chord–wise.
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 21/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Flap–body podM∞ = 0.2,Re∞ = 4.3 million, α = 28o
Coarse Medium Fine
The separation bubble size at flap–body pod junction isunaffected with grid refinement (unlike for α = 13o case).
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1 streamlines: Tip regionM∞ = 0.2,Re∞ = 4.3 million, α = 28o
Coarse Medium Fine
The span-wise extent and chord-wise position ofseparation line on the flap upper surface does not changewith grid refinement (also for α = 13o case).
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 24/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on slatM∞ = 0.2,Re∞ = 4.30 million, α = 13o
17 % 50 % 98 %
Good Cp comparison on upper surface at each station.
Poor Cp comparison on lower surface involving underbellybubble: limitation of turbulence model.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on main elementM∞ = 0.2,Re∞ = 4.30 million, α = 13o
17 % 50 % 98 %
Good Cp comparison at 17 % & 50 % stations.
Inadequate grid resolution to capture tip vortices (even) onfine grid has resulted in not–so–good Cp comparison beyondmid–chord location on upper surface at 98 % station.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on flapM∞ = 0.2,Re∞ = 4.30 million, α = 13o
17 % 50 % 98 %
Good Cp comparison at 17 % & 50 % stations.
Inadequate grid resolution to capture tip vortices (even) onfine grid has resulted in not–so–good Cp comparison on uppersurface at 98 % station.
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 27/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
Ravindra et.al. — HiLiftPW1: CFD computations for TRAP WING using HiFUN 28/45
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on slatM∞ = 0.2,Re∞ = 4.30 million, α = 28o
17 % 50 % 98 %
Good Cp comparison on upper surface at all stations.
Reduction in (disappearance of) separation on lower surfacehas led to good Cp prediction at all stations.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on main elementM∞ = 0.2,Re∞ = 4.30 million, α = 28o
17 % 50 % 98 %
Good Cp comparison at 17 % & 50 % stations.
Inadequate grid resolution to capture tip vortices (even) onfine grid has resulted in not–so–good Cp comparison beyondquarter–chord location on upper surface at 98 % station.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Config 1: Cp comparison on flapM∞ = 0.2,Re∞ = 4.30 million, α = 28o
17 % 50 % 98 %
Good Cp comparison at 17 % station.
Severe adverse pressure gradient on the flap leading to apossible flow separation not captured in the numerics;compounded by inadequate resolution of tip vortices leadingto not–so–good Cp comparison at 50 % and 98 % stations.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Comparison of Lift coefficientM∞ = 0.2,Re∞ = 4.3 million
Overall view Zoom:α = 13o Zoom:α = 28o
With grid refinement, the computed lift coefficients forα = 13o and α = 28o are tending to the experimental values.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Comparison of Drag coefficientM∞ = 0.2,Re∞ = 4.3 million
Overall view Zoom:α = 13o Zoom:α = 28o
With grid refinement, the computed drag coefficient forα = 28o is tending to the experimental value.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Comparison of Moment coefficientM∞ = 0.2,Re∞ = 4.3 million
Overall view Zoom:α = 13o Zoom:α = 28o
With grid refinement, the computed moment coefficients forα = 13o and α = 28o are tending to the experimental values.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
3 Results: Case 1–Grid convergenceStreamlines: α = 13o
Streamlines: α = 28o
Cp comparison: α = 13o
Cp comparison: α = 28o
Integrated coefficients comparisonTypical convergence histories
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Convergence history: Fine grid, α = 130
Fine grid: M∞ = 0.2,Re∞ = 4.3 million
Relative Residue CL,CD evolution ∆CL,∆CD counts
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Convergence history: Fine grid, α = 280
Fine grid: M∞ = 0.2,Re∞ = 4.3 million
Relative Residue CL,CD evolution ∆CL,∆CD counts
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Outline
1 Introduction
2 Typical grids
3 Results: Case 1–Grid convergence
4 Conclusions
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Concluding remarks
Conclusions
In the present work, results of RANS computations forNASA TRAP WING using the code HiFUN are presented.
During grid generation the guidelines provided byworkshop committee are followed, except for the numberof field cells.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Concluding remarks
Grid convergence study: α = 13o and α = 28o
Separation bubble is seen at flap–body pod junction forboth angles of attack.
At α = 13o , separation bubble becomes more pronouncedwith grid refinement.
Separation line is seen on upper surface of flap for bothangles of attack.
The chord-wise location and span-wise extent of theseparation line does not change with grid refinement.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Concluding remarks
Grid convergence study: α = 13o and α = 28o
An overall good comparison of computed andexperimental Cp distributions can be seen on uppersurfaces of slat, main element and flap.
Cp comparison on the lower surface of slat in theunderbelly separation region is poor owing to thelimitation of turbulence model.
Better prediction of Cp for higher incidence (α = 28o) onthe slat lower surface is indicative of better flowalignment at higher incidences resulting in subduedseparation activity.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Concluding remarks
Grid convergence study: α = 13o and α = 28o
Cp comparison near the tips of main element and flap isnot–so–good owing to inadequate grid resolution incapturing vortices and can be improved with further gridrefinement.
With grid refinement, lift, drag and moment coefficientstend towards experimental values.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Acknowledgments
Authors wish to thank
Prof. Govindarajan, Chairman, Supercomputer Education andResearch Centre (SERC), IISc for the use of IBM Blue Gene.
Mr. Satish Regode for his help in post-processing the results.
Dr. P. R. Viswanath (Boeing, India) for his useful commentson the work.
Dr. Mori Mani (Boeing) for kindly agreeing to make thispresentation on their behalf.
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Introduction Typical grids Results: Case 1–Grid convergence Conclusions
Thank you
Thank you
Thank you
Contact
Ravindra K.: [email protected]
Nikhil Vijay Shende: [email protected]
N. Balakrishnan: [email protected]
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