A. Spentzos 1, G. Barakos 1, K. Badcock 1 P. Wernert 2, S. Schreck 3 & M. Raffel 4 1 CFD Laboratory,...
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Transcript of A. Spentzos 1, G. Barakos 1, K. Badcock 1 P. Wernert 2, S. Schreck 3 & M. Raffel 4 1 CFD Laboratory,...
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A. Spentzos1, G. Barakos1, K. Badcock1
P. Wernert2, S. Schreck3 & M. Raffel4
1 CFD Laboratory, University of Glasgow, UK 2 Institute de Recherche de Saint Louis, France3 National renewable energy laboratory USA4 DLR - Institute for Aerodynamics and Flow Technology, Germany
Numerical Simulation of 3D Dynamic Stall
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Outline
Background and Objectives Past efforts in 3D dynamic stall CFD requirements for validation Summary of selected tools 2D dynamic stall Validation cases and results Conclusions
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Motivation and Objectives
DS is encountered in rotorcraft and highly maneuverable aircraft
Complex problem – prediction of loads and flow structure 3D studies are rare Study 3D DS, use a variety of turbulence models and
simulation (LES) Improve existing turbulence models Understand flow physics Validate CFD so that industry can exploit Take things a bit further…
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Background
What is Dynamic Stall? Experimental and CFD work on DS The majority of the work performed on DS (experimental
and CFD) has been done on 2-D Most CFD has been done for code validation rather than
investigation of the flow physics. 2D CFD suggested that turbulence modelling is a key
issue if fidelity is required Missing: 3D, centrifugal effects, dM/dt, interaction with
wake
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CFD requirements for validation
Surface pressure Integral loads Boundary layers Information for turbulence levels in the tunnel
and transition Higher Mach numbers Near-tip and flow-field measurements Measurements on rotating blades Measurements on more complex geometries
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Summary of experiments Most experiments on DS are 2D 3D work has been done by the following:
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Selected Validation Cases
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CFD solver PMB solver of the Univ. of Glasgow Control volume method Parallel (distributed memory) Multi-block (complex geometry) structured grids Moving grids Unsteady RANS - Variety of turbulence models – LES Implicit time marching Osher's and Roe's schemes for convective fluxes MUSCL scheme for effectively 3rd order accuracy Central differences for viscous fluxes Conjugate gradient linear solver with pre-conditioning Validation database
www.aero.gla.ac.uk/Research/CFD/validation
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2D Results for Ramping and Oscillating Aerofoils
CFD results for dynamic stall of helicopter sections
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Flow Field Comparison
Sinusoidal pitch, k=0.15, Re=373,000, M=0.1
a) 22 Deg (upstroke) b) 23 Deg (upstroke) c) 24 Deg (upstroke)
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Geometry – Grid Generation
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Geometry – Grid Generation
One-block extruded tip
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Geometry – Grid Generation
C-O topology
4-block extruded tip
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Grid and Time Convergence
Three levels of refinement: 120k, 800k, 1,800k
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Grid and Time Convergence
Two levels of time refinement resolving frequencies up to 20 Hz and 40Hz
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Experimental evidence of the -shaped vortex
3D CFD
Schreck & Hellin2D CFD
Coton et al.
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Surface Pressure
Ramping motion,Re=69,000, M=0.1, K=0.1Incidence 40.9 degrees
Experiment CFD
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Close the loop – AnalysisONERA model
Cz Cz
Cz
C C Cz z z 1 2
C C C k C k C k C kz z z s z c1 z s z c2 20 2 1 2 2 2 2 22 2 sin cos sin cos C C C k C kz z z s z c 0 sin cos
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Close the loop – AnalysisONERA model
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Conclusions
Experimentalists like CFD pictures! Are keen to collaborate and look in their
databases for measurements They developed the ability to understand
much about the flow from a small number of measurements
They are getting used to the idea of CFD…or at least looking at CFD results
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Conclusions
CFD developers are always looking for good data and have many requirements
Have sometimes to make a first step Have to be open about any limitations of
their methods Perform simulations, validation,
comparisons and maybe …some analysis!