Computational characterization of vortexes generated by low-profile Vortex Generators

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1 2017 Pamplona-Iruña, April 2017 Computational characterization of vortexes generated by low-profile Vortex Generators Iosu Ibarra Udaeta, Iñigo Errasti Arrieta, Unai Fernández- Gamiz, Ekaitz Zulueta, Javier Díaz de Argandoña Department of Nuclear Engineering and Fluid Mechanics Engineering School, Vitoria-Gasteiz University of the Basque Country (UPV/EHU)

MEMs - Fluidics FLOW CONTROL PHENOMENA CONTROLS: - Neural network - Adaptive -

2 1 Active/passive devices for flow control DEVICES: -TE flaps - Fences - Microtaps -Gurney flaps - VGs - AJVGs ACTUATORS: - Piezoelectric - Motors - MEMs - Fluidics FLOW CONTROL PHENOMENA CONTROLS: - Neural network - Adaptive - Physical model based - Optimal control theory SENSORS: - Conventional - Optical - MEMS

3 1 What is a VG?. How does it work? These passive devices are used for flow control: Modifying the boundary layer (BL) motion Generation of longitudinal vortices Overturn of the BL flow via large scale motions Evolution of boundary layer velocity profiles with adverse pressure gradient Bringing high momentum fluid down into the near wall region of the boundary layer IN SHORT: separation of the flow is delayed VG Boundary layer motion alteration by a rectangular VG

1 VG geometry and lay-out Geometry: triangular or rectangular vanes Dimensioned: to the local boundary layer thickness Lay-out: in cascades of groups

4 1 VG geometry and lay-out Geometry: triangular or rectangular vanes Dimensioned: to the local boundary layer thickness Lay-out: in cascades of groups of two vanes VGs on airfoils Ref.: Author design, 2013 VG1 VG2 VG3 VG4 Counter rotating passive device configuration Ref.: G. Godard and Stanislas, 2006

5 1 Parametric studies on VGs Requires (some) knowledge about the base flow VG cascade geometry optimization: Many degrees of freedom (angle, interspacing, orientation, height, length...) Very important for VG performance VG row positioning on blade: Chord/span Aeroelasticity considerations VGs VGs VGs VGs VGs VGs VGs VGs VGs Ref.: Miller, 1995

6 1 VG on airfoils Main functionality: to delay or prevent separation of the flow (a) Flow across an airfoil (b) Separated flow over the top surface of an airfoil Effect of vortex generators VGs on the performance of DU 97-W-300 (commonly used in wind turbines) Ref.: J.D. Anderson Jr., Brief History of the Early Development of Theoretical and Exp. Fluid Dynamics, Willey & Sons, 2010 Ref.: van Rooij R. P. J. O. M. and Timmer W A. Roughness Sensitivity Considerations for Thick Rotor Blade Airfoils. AIAA-paper

7 1 VG on wind turbines

8 1 VG on offshore wind turbines. Detail #1 VGs on Wind Turbines Source: Pictures were taken by the author in EWEA Conference 2012, Copenhaguen

1 VG on wind turbines Increased wind turbine performance from implementing VGs on the blades has also been

5 MW wind turbine performance (b) Effects of VGs on a 1 MW wind turbine performance Ref.: Miller, G.E., Comparitive Performance Tests on the Mod-2 2.

on Horizontal Axis Wind Turbine Technology, May 8-10, Cleveland, OH, 1984 Ref.: S.

9 1 VG on wind turbines Increased wind turbine performance from implementing VGs on the blades has also been confirmed in certain field tests: (a) Effects of VGs on a 2.5 MW wind turbine performance (b) Effects of VGs on a 1 MW wind turbine performance Ref.: Miller, G.E., Comparitive Performance Tests on the Mod MW Wind Turbine With and Without Vortex Generators, NASA TM N , Presented at the DOE/NASA Workshop on Horizontal Axis Wind Turbine Technology, May 8-10, Cleveland, OH, 1984 Ref.: S. Øye, The effect of Vortex Generators on the performance of the ELKRAFT 1000 kw Turbine, 9 th IEA Symp. On Aerodynamics of Wind Turbines, 1995

10 1 Pros and cons of VGs Pros Efficient Easy and fast practical implementation Inexpensive Can be integrated as part of the blade design Can also be applied as retrofits to improve existing designs Cons Small parasitic drag Require detailed understanding to be correctly applied VGs needed to be optimized for every specific flow/geometry Not an universal VG solution: VGs should be designed according to the local wind resource and turbine type

2 Study overview Characterization of the

15º, 18º,20º) β OUTLET Flat plate VG VG:

11 2 Study overview Characterization of the primary vortex generated by rectangular VGs of different heights h (H1, H2, H3, H4, H, H5) for four orientations ( =10º, 15º, 18º,20º) β OUTLET Flat plate VG VG: passive flow control device VG: rectangular vane (h x 2h) β : angle of attack Negligible pressure gradient Domain dimensions: 75 x 64 x 10

12 2 Study overview Vortex Generators VGs of different heights h are positioned at a distance on a flat plate where the local boundary layer thickness equals the conventional VG height H CFD code: OpenFOAM v2.4.0 VG δ = 20 ms -1 near wake region z=r Flat plate δ β : local boundary layer thickness : incident angle of attack Conventional VG height: h=h=0.25 m Six VG heights h respect to the local BL: h/δ=0.2, 0.4, 0.6, 0.8, 1, 1.2 Four orientations (incident angles of attack): 10º, 15º, 18º and 20º Free stream velocity U=20 ms -1, R E =27000

13 3 Geometry/3D Meshing Meshing of a rectangular VG vane on a flat plate: VG near wake External mesher or BlockMesh & blockmeshdict: - Multigrading feature - 44/64 structured blocks - Three or four levels (N0, N1, N2, N3) Proximity of the vane: Mesh containing around 6 x 10 6 cells VG Wake region containing around 4 x 10 6 cells Normalized height of the closest cell to the wall: y/h=1.5 x 10-6 y + <1 Wake region Vortex data (pressure, velocity and vorticicity) obtained in spanwise planes normal to the flow direction at distances 3 to 28 times the conventional VG height from its trailing edge (TE)

14 3 3D Meshing VG near wake N 2 N 1 VG N 0-44/64 structured blocks - 5 blocks defining the VG: A, A B, B C Near wake region able to capture: - the primary vortex VG - a secondary vortex

15 3 3D Meshing VG near wake VG

of height H=h= δ Detailed mesh around VG VG near wake VG

Turbulent flow Negligible pressure gradient No heat

simulation Turbulence modelling (K-Omega SST model)

=27000 Averaged normalized wall distance y + <1 Typical

0 Ghz): 10 days Mesh dependency study Richardson

16 4 Assumptions & Numerical setup. Standard BCs and solver Rectangular Vortex Generator (VG) of height H=h= δ Detailed mesh around VG VG near wake VG Assumptions: Setup: VG Incompressible flow (air) Turbulent flow Negligible pressure gradient No heat transfer Steady-state case Numerical methods: RANS simulation Turbulence modelling (K-Omega SST model) Boundary condition at inlet: uniform U=20 ms -1 R E =27000 Averaged normalized wall distance y + <1 Typical RANS simulation time (16 CPUs, 3.0 Ghz): 10 days Mesh dependency study Richardson extrapolation method (Ref.: Urkiola et al, 2017) 44 blocks of 16 3 cells: 44 blocks of 32 3 cells: 44/64 blocks of 64 3 cells. 12 x 10 6 cells:

17 5 Axial u x and azimuthal u theta velocity profiles CFD and analytical (Velte, 2013) results of the axial u x and azimuthal u theta velocity profiles at the same plane 5h past the VG for incident angles 10º, 15º, 18º and 20º: Beta= Ref.: Urkiola et al, 2017 Case: conventional VG

18 5 Vortex evolution. Beta=10º Ux (ms -1 )

19 5 Vortex evolution. Beta=15º Ux (ms -1 )

20 5 Vortex evolution. Beta=18º Ux (ms -1 )

21 5 Vortex evolution. Beta=20º Ux (ms -1 )

22 5 Wall shear stress past the VG. Beta=10º. Beta=15º du τ ω = µ dy BL detachment condition: 0 du dy = Ref.: Godard and Stanislas (2006) c f = τ ω 1 ρu 2 2

23 5 Wall shear stress past the VG. Beta=18º. Beta=20º

half the peak vorticity w x,max measured on planes normal to the streamwise direction R 0.

24 5 Vortex size. Half-life radius R 0.5 Half-life radius: distance from the center of the vortex to the point where the axial vorticity w x is half the peak vorticity w x,max measured on planes normal to the streamwise direction R 0.5 based on estimations on the maximum value of the axial vorticity (peak vorticity) ( ) ln 1 2 ω r 0.5 = ω e (Eq. 2) peak r R 2 Ref.: Martinez-Filgueira et al, 2017 Gaussian distribution fitting to the CFD results corresponding to the axial vorticity w x taken from a horizontal line probe passing through the vortex center on a plane normal to the streamwise direction Primary vortex y x z=r Secondary vortex!!

25 5 Half-life radius evolution. Beta=10º. Beta=15º

26 5 Half-life radius evolution. Beta=18º. Beta=20º Best incident angle, according to Godard and Stanislas (2006)

27 5 Vortex center path. Vertical path. Beta=10º. Beta=18º

28 5 Vortex center path. Lateral path. Beta=10º. Beta=18º

29 6 Conclusions OpenFOAM Appropriate tool used in the Department for Educational & Research purposes Turbulence model & solver used are suitable for simulation & developing a computational model in order to characterize the primary vortex generated by rectangular VGs on a flat plate with negligible pressure gradient at Re=27000 based on the conventional VG height Vortex characterization study Similar vortex parameter results that those obtained in experiments, analytical models and commercial CFD codes Wall shear stress: Best cases: 0.6H and 0.4H Half life radius: Best cases: 0.6H and 0.8H Vortex path: As expected, the vortex with highest vertical path is that which corresponds to the case 1.2H. Lateral path moves as expected Considerable number of cases analysed: 6 VG heights (0.2H, 0.4H, 0.6H, 0.8H, H, 1.2H) and four incident angles (10º, 15º, 18º, 20º) Work in progress

30 6 References A. Urkiola, U. Fernandez-Gamiz, I. Errasti and E. Zulueta. Computational characterization of the vortex generated by a vortex generator on a flat plate for different vane angles. Aerospace Science & Technology. 65, P. Martinez-Filgueira, U. Fernandez-Gamiz, E. Zulueta, I. Errasti and B. Fernandez-Gauna. Parametric study of low-profile vortex generators. International Journal of Hydrogen Energy. In press U. Fernandez-Gamiz, G. Zamorano and E. Zulueta. Computational study of the vortex path variation with the VG height. J. Phys. Conf. Ser U. Fernandez-Gamiz, C.M. Velte, P.E. Réthoré, N.N. Sorensen and E. Egusquiza. Testing of self-similarity and helical symmetry in vortex generator flow simulations. Wind Energy G. Godard and M. Stanislas. Part 1. Optimization of passive vortex generators. Aerosp. Sci. Technol C. M. Velte. Vortex generator flow model based on self-similarity. AIAA J. 51(2), C. M. Velte, M. O. L. Hansen and V. L. Okulov. Helical structure of longitudinal vortices embedded in turbulent wall-bounded flow. J. Fluid Mech. 619 pp DOI: /S J. C. Lin, F. G. Howard and G. V. Selby. Small submerged vortex generators for turbulent-flow separation control. J. Spacecraft Rockets 27(5), J. C. Lin. Review of research on low-profile vortex generators to control boundary-layer separation. Prog. Aerospace Sci. 38(4-5), pp P. Ashill, J. Fulker and K. Hackett. Research at DERA on sub boundary layer vortex generators (SBVGs). Presented at 39th AIAA Aerospace Sciences Meeting and Exhibit, AIAA Paper

Computational study of the vortex path variation with the VG height

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