CFD predictions of transition and distributed ...

CFD predictions of transition and distributed roughness over a wind turbine airfoil Esteban Ferrer∗ and Xabier Munduate† CENER (National Renewable Energy Centre), Ciudad de la Innovaci´ on 7, Sarriguren, Navarra, 31621, Spain CFD predictions of transitional flows and distributed roughness over a wind turbine airfoil to account for variable life cycle operational regimes are presented. The panel method code Xfoil 6.96 and the CFD commercial code Fluent 12.0.3 Beta are evaluated for the prediction of 2D wind turbine airfoil aerodynamic performance. The aim of the work is to asses the accuracy of the various methods in the determination of integrated loads (i.e. Cl, Cd, L/D and Cm1/4 ) for airfoils with both clean and rough surfaces that simulate contamination arising from wind turbine operational life. Numerical data is compared to experimental results for the NREL S814 wind turbine airfoil. Xfoil and Fluent are used to predict the three states present in a wind turbine blade life cycle. The aerodynamic characteristics are calculated with transition and no roughness (also called clean configuration), with fully turbulent flow and no roughness and finally applying roughness under fully turbulent flow conditions. Validation cases are presented where computations are compared to experimental data for cases with locally distributed roughness at the leading edge of the airfoil. Roughness of this type simulates airfoil contamination by bugs, dirt or debris. Results for smooth clean surfaces and fully turbulent flows (e.g. tripped boundary layer) are very similar for the two codes for attached or mildly separated flows. The transitional model (k − ω − γ − Reθ ) of Fluent gives reasonable results when compared to transition free experimental data and Xfoil computed with free transition. To account for roughness effects, the SST k−ω model modified to take into account surface roughness has been used in its Fluent version. CFD calculations, where roughness is modelled, are in good agreement with experimental data. It is shown that roughness originated from contamination has a more damaging effect on aerodynamics than a boundary layer tripping. It is concluded that CFD can simulate all the variety of flows that an operational wind turbine airfoil can encounter throughout its life cycle.

Nomenclature AOA a1 c Cd Cdp Cdw Cl

angle of attack [degrees] Bradshaw’s structural parameter airfoil chord [m] total drag coefficient (includes pressure and viscous drag) = 1 .ρ Drag [−] 2 ∞ .V∞ .Sref 2 pressure drag coefficient (measured through pressure taps) [−] wake drag coefficient (measured with wake rake) [−] t lift coefficient = 1 .ρ Lif [−] .V 2 .S

Cm1/4

moment coefficient about the quarter chord =

2

Cp F2 , F3 k k k+

∞

∞

ref

P −P∞ 1 2 2 .ρ∞ .V∞

M oment 1 2 2 .ρ∞ .V∞ .Sref .Lref

[−]

pressure coefficient = [−] auxiliary functions in turbulence model arbitrary roughness height parameter [m] in k − ω turbulence model is the turbulent kinetic energy [m2 /s2 ] τ equivalent flow quantity for k = k.u [−] ν

∗ Research † Senior

Scientist, Wind Energy Department, CENER, AIAA Member. Researcher, Wind Energy Department, CENER, AIAA Member.

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ks Ma N L/D Re Reθ uτ

equivalent sand roughness height [m] Mach number [−] in Xfoil it is the log of the amplification factor of the most-amplified frequency which triggers transition [−] Lift to drag ratio [−] ∞ [−] Reynolds number = chord.V ν τ [−] momentum thickness Reynolds number = θ.u ν q τw [m/s] friction velocity = ρ

yp y+ |Ω| γ µ ν ρ τw ω ωw

wall distance [m] τ non-dimensional normal distance from surface= yp.u [−] ν absolute value of vorticity [−] in transitional modelling is the intermittency [−] dynamic fluid viscosity [kg/(m.s)] kinematic fluid viscosity [m2 /s] fluid density [kg/m3 ] wall shear stress [P a] is the specific dissipation rate of turbulent kinetic energy [1/s] is the specific dissipation rate of turbulent kinetic energy at the wall [1/s]

I.

Introduction

Wind turbine airfoils operate in variable environments. New manufactured blades are clean and airfoils show clean performance. The clean performance is characterized by the existence of a laminar flow region over the airfoil for operative (design) incidences. Once the blade has been in use and due to the dirty environmental conditions, deterioration of the blade aerodynamic performances are observed. Contamination can arise from multiple sources, among others dirt, insects, dust or erosion. As shown by Corten1 insects and dust may even halve wind turbine power particularly for stall regulated turbines. Localised contamination can be represented by distributed rough elements near the airfoil leading edge. The major effect of distributed roughness in the airfoil performance is to deteriorate its aerodynamic behaviour. In the first place, if the rough elements are located near the leading edge zone, roughness influences the laminar/turbulent transition process leading to an upstream location of the transition point2 . In addition to promote transition, roughness modifies the flow characteristics in fully turbulent flows. Both effects are often confused and sometimes the second is ignored. The promotion of transition and its effects on airfoil performance can be found in various works, and of particular interest to the wind energy industry are those carried out by Delft University in the Netherlands3,4,5 ). The following quote from Timmer and Chaffarczyk3 summarises the main expectable effects of roughness on aerodynamic aerofoil characteristics due to the promotion of transition. ”Leading edge roughness adds thickness to the boundary layer and makes the transition location shift to the nose region of the airfoil. The resulting thicker turbulent boundary layer leads to increased drag, a reduction of the effective camber and earlier stall.” As stated, the effect of roughness cannot only be related to the movement of the transition point. The effects of roughness on a fully turbulent boundary layer are summarized herein2,6 . Generally speaking, lift decreases due to modification of the log-law velocity distribution, and drag increases due to the increased shear near the surface. There is also an increase on the boundary layer thickness (and displacement thickness). The resulting lift to drag ratios show important decrease in its absolute values throughout all angles of attack. The modified forces tend to reduce nose down moment coefficients. Roughness also promotes earlier stall since the increased shear due to roughness that opposes streamwise momentum dominates the separation mechanism, for an equal streamwise pressure gradient. Most wind energy dedicated airfoils are conceived to be ’insensitive to roughness’. Some examples are the National Renewable Energy Laboratory (NREL)7 , the Risø National Laboratory8 or Delft University4 airfoil families. To the authors knowledge main design methods developed for the wind turbine industry 2 of 16 American Institute of Aeronautics and Astronautics

use 2D panel methods that couple potential calculations with boundary layer theory to compute the aerodynamic airfoil characteristics (e.g. Xfoil9 or Eppler10,11 ). It has to be pointed that these codes compute laminar/turbulent transition through semi-empirical methods implemented within the boundary layer formulation that switches from laminar to turbulent once the transitional criterion has been determined by the method (e.g Michel, eN, Eppler, Granville). However, there is no mechanism, as far as the authors knows, for panel methods to account for roughness effects beyond the promotion of transition. Therefore, the so called ’insensibility to roughness’ criterion used for design of wind turbine airfoil has to be taken with caution. This ’insensibility’ refers to laminar/turbulent transitional behaviour of the airfoil; that is how rapidly when increasing the angle of attack, the transition point moves towards the leading edge. The fact that the maximum lift (or maximum L/D ratio) is attained once all flow on the suction side is turbulent is defined as insensitivity since further contamination will not affect the maximum lift through transition point movement. But it should be kept in mind that transition movement is only a first consequence of roughness and that once the whole boundary boundary has become turbulent, further effects of roughness are to be expected. In the following sections, Xfoil and Fluent are used to predict the three states present in a wind turbine blade life cycle. The aerodynamic characteristics are calculated with transition and no roughness, with fully turbulent flow and no roughness and finally applying roughness with fully turbulent flow. Validation cases are presented where computations are compared to experimental data for cases with locally distributed roughness at the leading edge of the airfoil. Roughness of this type simulates airfoil contamination by bugs, dirt or debris. Section II describes the two numerical methods employed. Details of the turbulence model used for the inclusion of rough walls in CFD are found in section III Section IV includes details of the experimental data selected and within section V, the results from the two codes are compared to the experimental data. Finally, a summary of the results and conclusions of the methodology are presented in section VI.

II.

Methodology and Numerics

A brief overview of the codes used is presented in this section. II.A.

Xfoil 6.96

Xfoil9,12 is a panel method code developed by Mark Drela from the Massachusetts Institute of Technology (MIT). The code couples high-order panels methods with fully coupled viscous/inviscid interaction. The boundary layer (BL) and wake are described with two-equation lagged dissipation integral BL formulation and he eN transition criterion. The BL/inviscid flow coupling is interacted via surface transpiration model. The number of panels for the Xfoil calculations has been set to 250 for all cases. II.B.

The CFD code: Fluent 12.0.3 Beta

Fluent 12.0.3 Beta has been used to compute aerodynamic characteristics of the simulated airfoils. The 2D double precision incompressible segregated steady state solver has been selected for the present study. The second order upwind scheme selected for discretisation of convective terms and the standard formulation used for pressure. Only the steady-state solver has been used. When detached flow became significant, the solver failed to reach a steady state solution and calculations were abandoned to avoid the very long computations associated with transient flows. Therefore only moderately high AOAs will be presented (up to 8degrees). Furthermore, the rough cases tended to separate earlier and this is why its range of AOA is somewhat shorter. The commercial code Fluent 12.0.3 offers the possibility to compute laminar/tubulent transition using the recently implemented Menter-Langtry k − ω − γ − Reθ correlation.13 For the remaining simulations (fully turbulent) the Shear-Stress Transport (SST) k − ω by Menter14 is used. To date, Fluent does not allow the combination roughness with transition and thus, all rough simulations have been carried out assuming fully turbulent flow. Details of the roughness model will be found in following sections.

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II.C.

Grid generation

The grid topology used for Fluent is of C type. Meshes have been created using Icemcfd in its hexa version. The resulting mesh is a multiblock structured mesh constituted of hexahedral elements that can be stretched near the airfoil surface allowing the proper resolution of the boundary layer. The resulting y+ values are below 1, so the boundary is properly resolved using the k − ω family of turbulence models. Furthermore, grid growth in the normal direction has been restrained to obtain enough grid point within the boundary layer and resolve the subsequent normal velocity gradient accurately. Streamwise mesh stretching has been limited to allow for smooth development of turbulence when transition is enabled. The resulting mesh has a typical total number of elements of 100.000 nodes. 140 elements have been used in the airfoil surface normal direction, 100 from the trailing edge to the outflow and more than 400 elements around the airfoil to accurately capture transition and the roughness effects. The boundary conditions have been located far enough (20 chords away) upstream and around the airfoil not to influence the developing flow. The outflow boundary has been placed 40 chords away from the trailing edge to allow the wake to freely develop. Grid independence has been checked by simulating the airfoil at 6.1 degrees AOA with three different grids for the fully turbulent case with no roughness. Coarsening and refinement has been made by halving and doubling the number of elements respectively in all directions, without changing the adjacent to the wall cell height (y+ < 1). The coarse grid has 52.000 elements and a the refined grid 210.400. Results for the lift coefficient do not differ for more than 10−3 units, 10−5 for the drag coefficient and 10−4 for the moment coefficient. The intermediate mesh with 100.000 elements has been retained since meets accuracy requirements at an affordable computational cost. The resulting mesh is shown in figure 1. The same mesh has been used for all CFD calculations. When the modelling of distributed roughness has been enabled, the extension of the rough zone corresponds to the blue zone depicted near the airfoil nose. The gray lines limit the multiblock topology used in the mesh generation process with Icemcfd.

Figure 1. Grid used for the CFD runs for the S814 airfoil.

III.

Roughness and turbulence modelling

The retained option to simulate rough airfoils is the use of the SST k − ω model. This naturally resolves the whole boundary layer with no necessity of wall functions or low Reynolds number corrections. The k − ω

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family of models (i.e. Wilcox’s and Menter’s SST) have proved to be robust and accurate for a wide range of airfoil simulations15,14 . Wilcox15,16 derived a modification of the standard k − ω to account for roughness effects through the modification of the dissipation rate at the wall (ωw ). This model is presented in section III.A. Wilcox’s modification was conceived for the standard k − ω model, however it is generally used when the SST k − ω model is implemented. Section III.B comments the main differences between Wilcox’s model and the Fluent implementation of this model. Finally, the inclusion of a specific correction for the SST model called Hellsten and Laine correction is discussed in section III.C. III.A.

Wilcox k − ω formulation modified for roughness

The omega formulation has a special advantage over the epsilon formulation since the value of omega can be arbitrarily specified at the wall. The resulting formulation reads: ωw =

where uτ is the friction velocity defined as ( SR =

q

τw ρ

u2τ SR ν

(1)

and SR is:

(50/kS+ )2 100/kS+

kS+ < 25 kS+ ≥ 25

kS+ is the non dimensional sand grain height defined as: kS+ =

uτ ks ν

(2)

The higher range corresponds to the fully rough regime. The present calculations correspond to the higher range that simulate operational contamination. Three remarks have been pointed out by Wilcox:16 • The minimum value to be attained by kS+ has to be limited. For the model to reduce to the smooth model, it is necessary to have kS+ < 5 that is the condition for hydrodynamically smooth surface. • Wilcox states that the model works well for attached and separated flows and that this method should be used even for smooth surfaces (specifying a small enough value for kS+ ). • the model has been validated for a maximum kS+ value of 400. III.B.

Fluent implementation of Wilcox k − ω formulation modified for roughness

Two modification of Wilcox’s basic model are found in Fluent’s implementation. Firstly, blending for the use of wall functions is found for big values of y+ is included. This is not presented herein since the low values of y+ used (y+ < 1) are sufficient condition for the application of the above presented Wilcox’s implementation (wall functions are not used). Secondly, the lower limiting value for kS+ for the model stated by Wilcox (e.g. kS+ < 5) is modified to be limited to 1 by setting: kS+ = max(1.0;

uτ ks ) ν

(3)

The applied roughness for the computed cases corresponds to values of kS+ that are high enough (25 ≤ ≤ 500) for all computed AOA. The minor difference above described in the modelling implementation is of minor importance for the present work as it affects only the minimum kS+ for the model to start acting. This is well bellow the modelled airfoil roughness. kS+

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III.C.

Hellsten and Laine SST k − ω correction

Hellsten and Laine17 found in 1997 that the SST-model and particularly the SST limitation based on Bradshaw’s assumption is not suitable for rough walls since the SST limiter leads to under prediction of roughness effects (e.g. skin friction). They proposed a modified SST model for rough walls where the turbulent viscosity is redefined as: µT =

a1 ρk max(a1 ω; |Ω|F2 F3 )

(4)

a1 is a model constant set to 0.31 and Ω is the vorticity. The F2 function is used to avoid the activation of the SST-limitation in case of free shear flow.The damping function F3 is defined as: " F3 = 1 − tanh

150ν ωyp2

4 # .

(5)

The above equations 4 and 5 have been implemented in Fluent 12.0.3 through a UDF and tested on the S814 airfoil. The definition of the F2 function that is necessary to compute µT has been retained from the SST model implemented in fluent and reads: " !#2  √   k 500µ F2 = tanh max 2 ; . (6)   0.09ωy ρωy 2

The first test has been to use the correction (Hellsten and Laine via UDF) for the fully turbulent clean configuration (no roughness and no transition) and to compare the results to the clean default SST Fluent model (SST k − ω). The results for Fluent with the correction enabled and default Fluent model appeared identical when the skin frictions were compared. The second part of the evaluation of the correction has been to compare the UDF results and the default model for a rough case. Figure 2 shows the computed resulting skin frictions with the default SST model and Hellsten and Laine model applying distributed roughness to the S814 airfoil leading edge at an AOA of 6.1 degrees. Skin friction results for the smooth surface with fully turbulent flow are also included for comparative purposes.

Figure 2. Computed skin friction using Fluent 12.0.3 Beta with grit roughness (ks/c=0.0019) at an AOA of 6.1deg for the S814. Suction and pressure airfoil sides are depicted separately

The computations show in both cases the increased skin friction due to presence of distributed roughness near the leading edge. The sudden change in shear (x/c ≈ 0.1) corresponds to the end of the rough region towards the smooth portion of the airfoil surface.

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It is seen that Hellsten and Laine correction leads to lower skin frictions that the default SST model implemented in Fluent 12.0.3 for the rough zone and the smooth portion of the airfoil. It can be also seen that with the Hellsten and Laine correction enabled, the skin friction does not recover to the fully turbulent values. Furthermore, the correction leads to separation on the suction side at x/c ≈ 0.4 which has not been observed in the experimental data. On the other hand, the SST model without corrections gives the same curve as the clean calculation for the aft smooth portion of the airfoil. From the above results and after conversations with Fluent’s support18 it was decided that the correction is not necessary in the present Fluent’s implementation and will not be considered in the following simulations.

IV.

Experimental data

The selected airfoil is the NREL S814. This thick airfoil (t/c = 24%) has been designed for wind turbine blade root sections and has been chosen for being a demanding test for numerical methods. The airfoil was designed to be insensitive to leading-edge roughness and to have high maximum lift coefficients19, .20 The airfoil was tested at the Ohio State University (OSU) 3 × 5m subsonic wind tunnel with clean, rough and oscillating configurations19,21 at various Reynolds numbers (e.g. 0.75, 1.0, 1.25 and 1.5 millions). IV.A.

Roughness definition

The standard roughness (also called sand roughness) is defined for a whole surface covered with a layer of spheres packed together as dense as possible. The diameter of these spheres is then called sand roughness height ks .2 The value for ks depends on the density and shape of the distributed roughness elements22,23 but it is possible to find an equivalent roughness height corresponding to the rough pattern employed for the tests that will produce the same effects on the flow. The roughness pattern used for the S814 tests was generated by NREL using a molded insect pattern taken from a wind turbine in the field.21 The roughness experimental results have been retained from OSU data where the roughness height is defined as quoted21 : ”Based on average particle size from the field specimen, standard ]40 lapidary grit was chosen for the roughness elements, giving k/c = 0.0019 for a 457-mm (18-in) chord model. To use the template, 102-mm (4-in) wide double-tack tape was applied to one side of the template, and grit was poured and brushed from the opposite side. The tape was then removed from the template and transferred to the model. This method allows the same roughness pattern to be replicated for any test.” It is assumed that the k/c value mentioned corresponds to the calculated ks/c value and thus the value of ks/c=0.0019 is retained and applied uniformly to the rough airfoil cases. the extend of the roughness zone corresponds to a length of 102mm equally distributed to the suction and pressure sides. The corresponding Ra to a 40 grit is approximately 425µm.24 Therefore the relation from ks/c to Ra can be calculated for this particular case to be: ks/c = 2.043Ra

(7)

This roughness size is characteristic of wind turbine blades contamination by bugs/dirt that is typically found on onshore sites. IV.B.

Experimental results

Results for the experimental lift coefficients are plotted for various Reynolds numbers (i.e. 0.75, 1.0, 1.25 and 1.5 millions) in figure 3. As can be noted there is almost not scattering on the data with Reynolds. The data corresponding to the Reynolds of 1.5 million has been retained for subsequent analysis. In figure 4 the wake and pressure drag curves are compared for Reynolds number of 1.5 million for both clean and rough configurations. It is observed that the increase of skin friction due to roughness is well captured with the wake rake and missed if pressure drag is used for low AOAs. Roughness influences pressure drag through separation and thus it becomes apparent at high AOAs.

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Figure 3. Experimental lift coefficient against AOA for the S814 airfoil obtained at OSU

Figure 4. Experimental drag coefficient against AOA for the S814 airfoil obtained at OSU

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V.

Numerical results and discussion

This section shows the CFD results obtained with Fluent 12.0.3. The results show the three flow conditions that a wind turbine airfoil can encounter throughout its life cycle. Results include integrated loads for clean airfoil surface with transition (laminar region), fully turbulent cases (that correspond to tripped cases) and simulations where distributed rough surfaces are implicitly implemented through the turbulence model. As stated in section III.C no correction are needed in Fluent 12.0.3 to compute the aerodynamic coefficients. Distribution of Cl, L/D and Cm1/4 against the angle of attack (AOA) can be found for the S814 airfoil. The polar Cl versus Cd is also included. The computed Cd values correspond to the total airfoil drag including pressure and viscous effects. This choice allows the comparison with experimental Cd wake data presented in section IV.B. The values given for Cl, Cd and Cm1/4 have all been calculated using the freestream dynamic pressure. The given values for the Cm1/4 moments correspond to nose down movement of the airfoil. Figure 5 show the comparison of the experimental data in the clean configuration compared to the computed values using Fluent’s transitional correlation and the fully turbulent model. Results using Xfoil with free transition (N parameter set to 8) and fully turbulent case (N parameter set to 0) have also been plotted. It is seen that the Fluent results match the Xfoil N=8 curve if the transition correlation is enabled, despite the difference in transition modelling used in the two codes. The fully turbulent cases also are in very close agreement for Xfoil and Fluent. When comparing transitional against fully turbulent, the transitional cases provide higher values for Cl all along the range of computed angles. It is also observed that the experimental curve is midway between the transitional curve and the fully turbulent one, which could indicate that the experimental data was obtained with higher turbulence levels that the ones used for the transition clean simulation.

Figure 5. Cl coefficient vs AOA for the S814. Comparison of CFD and Xfoil to experimental data for clean transitional and fully turbulent configurations.

In figure 6 results for clean and rough cases are depicted. These include experimental data clean and rough, CFD with clean transition and rough leading edge surface and Xfoil with free transition. No fully turbulent cases have been depicted in this figure for the sake of clarity. The figure shows that the rough calculation of Fluent is in very good agreement with its equivalent experimental rough case for the whole range of calculated angles. As already mentioned, since for high AOAs it was not possible to obtain a converged solution using the steady-state solver, the study has been limited to moderately-high AOAs.

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Figure 6. Cl coefficient vs AOA for the S814. Comparison of CFD and Xfoil to experimental data for clean transitional and CFD with rough leading edge.

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In the following the three states above mentioned (clean transitional, clean fully turbulent and rough fully turbulent) are depicted for comparative purposes. The Cl, Cd (total drag coefficient) polar curves are compared in figure 7. There is an offset of the curves to higher drag values due, in the first place, to the lack of laminar flow (i.e. Fluent’s fully turbulent case and Xfoil with N=0), and in the second, to the addition of wall shear due to roughness (seen in Fluent’s rough case). CFD results are generally in close agreement with experimental data. However discrepancies are seen when comparing the CFD transitional case and the clean experimental data. These discrepancies may in part be due to higher free stream turbulence levels in the experimental set up than in the calculations. Higher turbulence would move the transition point towards the airfoil nose, leading to higher shear and consequently a higher total drag.

Figure 7. Polar curve for the S814

Figure 8 shows the comparison for lift over drag ratios against the AOA. The drag coefficient used for the calculations of L/D are Cdw for the experimental data and Cd (total drag) for the CFD results. For the clean cases (with free transition), the CFD and Xfoil results are in very close agreement for AOAs up to 6 degrees. The experimental curve shows a different slope and generally lower values of L/D. Fluent’s fully turbulent case is in very good agreement with Xfoil with N = 0 which corresponds to a tripping of the boundary at the leading edge (only turbulent flow). When the rough curves are compared, Fluent shows a very good prediction of the L/D ratio over the computed AOA’s. From the L/D and Cd curves, it becomes clear that the effect of tripping the boundary layer is not equivalent to adding distributed roughness to the airfoil leading edge and if an airfoil is to be designed to be ’insensitive to roughness’ other methods than panel methods may be needed. Figure 9 shows the comparison for the moment coefficients obtained with Fluent and Xfoil and are compared to the experimental data. Again a very good agreement is found for moderated AOAs for both clean and rough cases when comparing CFD and experimental data. Xfoil using N = 0 and CFD with fully turbulent case agree for low AOA but differ for high AOA’s. For the S814 at high AOA’s trailing edge separation is more severe in the experimental results than in the CFD computations which explains the lower (in absolute value) nose down moment coefficient found experimentally.

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Figure 8. L/D ratio vs AOA for the S814

Figure 9. Cm coefficient vs AOA for the S814

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The following tables 1 and 2 show the computed values for the above depicted coefficients. The tables include the difference in percentage from the experimental clean values to the Fluent values using the transitional model. The agreement is particularly good for the AOA’s of 2,4 and 6 degrees. It can also be seen that the rough performance is better predicted that the clean cases using the transitional model. Table 1. Aerodynamic coefficients for the S814. Clean experimental results and simulations with transitional model k − ω − γ − Reθ enabled

AOA Cl exp Cl fluent % change Cdw exp Cd fluent % change L/D exp L/D fluent % change Cm exp Cm fluent % change

−4.2o

−2.1o

2o

4.1o

6.2o

8.2o

-0.113 -0.071 37.21 0.0107 0.0085 20.70 -10.56 -8.36 20.82 -0.1348 -0.1369 -1.52

0.139 0.175 -25.84 0.0103 0.0084 18.73 13.50 20.89 -54.83 -0.1396 -0.1411 -1.06

0.619 0.649 -4.89 0.0103 0.0092 10.96 60.10 70.79 -17.80 -0.1460 -0.1469 -0.65

0.847 0.881 -4.06 0.0109 0.0098 9.94 77.71 89.79 -15.55 -0.1456 -0.1492 -2.48

1.051 1.119 -6.46 0.0119 0.0112 6.10 88.32 100.13 -13.37 -0.1423 -0.1503 -5.66

1.217 1.345 -10.53 0.0147 0.0130 11.83 82.79 103.78 -25.36 -0.1333 -0.1496 -12.22

Table 2. Aerodynamic coefficients for the S814. Rough experimental results and simulations with SST k − ω model

AOA Cl exp Cl fluent % change Cdw exp Cd fluent % change L/D exp L/D fluent % change Cm exp Cm fluent % change

−4.2o

−2.1o

2o

4o

6.1o

8.2o

-0.070 -0.167 -138.98 0.0226 -7.39 -0.0535 -0.0938 -75.28

0.043 0.078 -81.68 0.0180 0.0170 5.65 2.39 4.60 -92.56 -0.1078 -0.1148 -6.50

0.511 0.540 -5.68 0.0179 0.0169 5.71 28.55 32.00 -12.09 -0.1235 -0.1257 -1.77

0.721 0.745 -3.38 0.0174 0.0188 -7.95 41.44 39.68 4.23 -0.1229 -0.1256 -2.21

0.875 0.938 -7.23 0.0207 0.0223 -7.87 42.27 42.02 0.60 -0.1167 -0.1223 -4.80

0.994 1.094 -10.07 0.0304 0.0285 6.32 32.70 38.42 -17.49 -0.1047 -0.1156 -10.42

From these results, it could be concluded that Fluent shows a good performance in predicting the aerodynamic coefficients for the S814 profile. Both clean and rough cases match the experimental available data. Differences are appreciated for high and low AOA’s when detached flow dominates but results are accurate for moderate angles. It is also been seen that Xfoil is not capable to predict roughness effects since boundary layer tripping is not equivalent to add distributed roughness to the airfoil leading edge. Finally, table 3 shows the percentage change from the clean configuration to rough case for each AOA for the experimental data and the Fluent results. The deterioration on the Cl is quantified to be around 10% for positive AOA’s, 90% for Cd and 15% for Cm. The tabulated values for L/D are depicted in figure 10. It is seen that the loss in airfoil efficiency can reach up to 80% for negative AOA’s and settles to 50-60% for intermediate AOA’s which correspond to operational wind turbine angles. From these results it can be concluded that the evaluation of the aerodynamic performance in rough cases is of major importance if accurate prediction of wind turbine power is to be assessed.

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Figure 10. Percentage change in lift to drag ratio from clean to rough cases for various AOAs for the S814

Table 3. Percentage change from clean to rough aerodynamic coefficients for the S814. Experimental and CFD results

AOA % % % % % % % %

Cl exp change Cl fluent change Cdw exp change Cd fluent change L/D exp change L/D fluent change Cm exp change Cm fluent change

−4.2o

−2.1o

2o

4o

6.1o

8.2o

38.05 -135.77 -166.66 11.58 60.31 31.48

69.06 55.34 -74.76 -102.88 82.30 77.98 22.78 18.62

17.45 16.83 -73.79 -84.02 52.50 54.80 15.41 14.47

14.88 15.44 -59.63 -91.34 46.68 55.80 15.59 15.81

16.75 16.14 -73.95 -99.83 52.14 58.04 17.99 18.66

18.32 18.66 -106.80 -119.74 60.51 62.98 21.46 22.72

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VI.

Summary and Conclusions

Three distinct flows can be encountered on a wind turbine blade airfoil. When new clean blades are operating, the flow over the sections (airfoil) is expected to have a laminar zone before transition to turbulent flow occurs. If a mechanism exist that triggers transition (i.e. roughness, free stream bypass, crossflow) then the airfoil will perform as fully turbulent (e.g without any laminar region). Finally, once the blade has being operated for a long enough time and due to the dirt environmental conditions, roughness could appear at the leading edge of the airfoils leading to the so called rough flow. Recent advances in transition and roughness modelling in CFD have allowed to improve the predictions for these three different conditions. The present work shows how CFD is mature enough to account for the complete wind turbine life cycle operational regimes. Firstly, it has been possible to calculate laminar/tubulent transition comparing the results to fully turbulent cases, it has been showed that the existence of laminar regions can double the L/D coefficient compared to the fully turbulent case. Secondly, localised leading edge roughness, characteristic of wind turbine field contamination by bugs or dirt has been simulated. Comparison of aerodynamic performance with experimental data has shown that CFD is capable to provide valuable qualitative and quantitative results on this respect. Xfoil has shown not to be a valid tool for predicting roughness effects, on fully turbulent flows. On the other hand, CFD and particularly Wilcox’s roughness model (in its Fluent version with no need of further corrections) has been found to be a valuable tool to evaluate roughness effect on airfoil performance. It has been shown that roughness is a complicated phenomenon that cannot be reduce only to a change in the transition point location. Indeed, roughness can importantly reduce the aerodynamic performance (up to 60% for L/D for moderate AOA’s) of wind turbine airfoils even when conceived to be ’insensible to roughness’.

VII.

Acknowledgements

The authors would like to thank NREL (the National Renewable Energy Laboratory) for making available the S814 experimental data used throughout this work.

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