Profiles STAR European Conference 2010 London By: Dr Martin van - - PowerPoint PPT Presentation

14th IAHR Conference – December 2009

Drag and Lift Validation of Wing Profiles

By: Dr Martin van Staden

Aerotherm Computational Dynamics STAR European Conference 2010 London

STAR European Conference 2010

 Background  Detailed Fan Modelling  2-D Wing Section Modelling  Comparison with Experimental data  Mesh & Turbulence model sensitivity  Summary & Conclusions

Outline of Presentation

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Background

 Two large Coal fired power stations are currently being

built in South Africa which make use of Air cooled Condensers for cooling.

 These ACC’s Consist of 384 fans each with a diameter

• f 10.4m (34ft).

 Detailed fan modelling

has become an important part of predicting the thermal performance of such a power station.

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Background….

 CFD provides us with the ideal tool

to model an ACC in order to understand the complex flows around as well as within the ACC’s A-frames.

 One of the most important parts of the

ACC modelling process is to understand how the fans react to poor inflow conditions.

 Fan performance can therefore be analysed as they will be installed

in situ and tested under real operating conditions.

 This data can then be used in global ACC models to model the entire

ACC in order to evaluate it’s response to changing wind conditions.

 An important outcome of the CFD analysis is the predicted fan power

for a given blade angle setting.

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Detailed Fan Modelling

 Requirements for fan modelling Global ACC model:

– Must predict the volume flow rate accurately – Must represent system pressure losses accurately – Must take into account the affect flow rate as a function of varying pressure losses – Must take into account the affect of skewed inflow conditions – Must be able to accurately predict fan power consumption

 Accurate prediction of the Fan power is important as

the fan power for a given flow rate is a contracted value and has a heavy financial penalty coupled to exceeding of the contract value.

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Detailed Fan Modelling

 What is a detailed fan model?

– The fan blades are explicitly modelled – Fan is rotated (explicitly or implicitly) – Cell sizes as small as 1mm – All support structures such as the A-frame, I-beams, fan screen supports, steam ducts, fan bridge, motor and gearbox, fan inlet bell etc are explicitly modelled.

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Detailed Fan Modelling

 The lift and drag is explicitly calculated based on the

3D flow field and pressure filed which develops around the fan blades as a result of the rotation.

 Rotation is achieved through steady state MRF or

explicitly rotation of the mesh (transient) i.e. using a sliding mesh.

 A test facility was modelled in order to compare the

• utcome of the CFD results with experimental results

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Outcome of test facility simulation

Good agreement was found with Pressure

• vs. Volume flow rate

Power was over predicted by the CFD models by more than 11%

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2D Wing profile comparison

 Tests were conducted on 2D wing sections in order to

evaluate the expected accuracy for relatively coarse meshes used in detailed fan models.

 The aim of the study was to identify which modelling

parameters were the main cause for large discrepancy in fan power predicted by the CFD models.

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Comparison of CFD vs. Experimental data

 The laser scanned fan wing section profile was

matched with a Wortmann FX60-126 wing section.

 Prof. Ewald Krämer from Stuttgart University was kind

enough to provide us with the aerodynamic data for comparison with 2D CFD simulations of the lift and drag.

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Initial mesh

 Low Rey poly mesh (15 boundary layer cells)  No wake refinement

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Simulation assumptions

 Free stream velocity of 50m/s was used (Rey=1.94E+6)  Inlet turbulence intensity of 0.01  Turbulent viscosity ratio of 10  Used all y+ approach in all turbulence models where this

• ption is relevant

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Initial mesh Y+ values

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FX60-126 - Aerofoil data Cl from CFD 2D profile simulation

• 0.50

0.00 0.50 1.00 1.50 2.00

• 10
• 5

5 10 15 20 25 Angle of attack (α) Lift Coefficien Cl Cl CFD Coarse k-e Cl Stuttgart : FX 60-126 - Rey=2e6

Comparison of lift curve

Stall point

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Comparison of drag curve

FX60-126 - Aerofoil data Cl and Cd from CFD 2D profile simulation

0.01 0.02 0.03 0.04 0.05 0.06

• 10
• 5

5 10 15 20 25

Angle of attack (α) Drag Coefficient Cd

Cd CFD Coarse k-e Cl Stuttgart : FX 60-126 - Rey=2e6

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Finer mesh

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Finer mesh y+ values

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Flow field at 10º & 15º angle of attack

10º 15º Onset of stall

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Turbulence models - lift

FX60-126 - Aerofoil data Cl and Cd from CFD 2D profile simulation

• 0.50

0.00 0.50 1.00 1.50 2.00 2.50

• 10
• 5

5 10 15 20 25 Angle of attack (α) Lift Coefficien Cl Cl CFD Coarse k-e Cl Stuttgart : FX 60-126 - Rey=2e6 k-e low Rey mesh k-w low Rey mesh Spalat-Almaris RS-2l k-e_V2-f k-w_trans

10º 15º

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Turbulence models - drag

FX60-126 - Aerofoil data Cl and Cd from CFD 2D profile simulation

0.01 0.02 0.03 0.04 0.05 0.06

• 10
• 5

5 10 15 20 25

Angle of attack (α) Drag Coefficient (Cd)

Cd CFD Coarse k-e Cl Stuttgart : FX 60-126 - Rey=2e6 k-e low Rey mesh k-w low Rey mesh-refine1 Spalat-Almaris RS-2l k-e_V2-f k-w_trans

10º 15º

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Pressure Coefficient

Pressure Coefficient

• 35000
• 30000
• 25000
• 20000
• 15000
• 10000
• 5000

5000 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Position (m) Skin Friction Coef. k-e low rey k-w Spalat-Almaris RST_2l k-e v2f

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Skin Friction Coefficient

Skin Friction Coefficient

50 100 150 200 250 300 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Position (m) Skin Friction Coef. k-e low rey k-w Spalat-Almaris RST_2l k-e v2f

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Summary Pressure vs. Shear

Pressure vs. Shear drag @ 10deg & 15deg angle of attack

0% 20% 40% 60% 80% 100% 120% k-e low Rey mesh RS_2l k-e_V2-f k-w low Rey mesh k-w_sst Spalat-Almaris

15deg Pressure 15deg Shear 10deg Pressure 10deg Shear

Pressure Shear 10 deg Average 68% 32% 15 deg Average 86% 14%

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Pressure vs. Shear

 On average at 15º angle of attack the drag due to

pressure accounts for 86% of the drag as opposed to 68% for an angle of attack of 10º.

 This leads one to suspect that the pressure drag may

be the component which is mainly to blame

 Further mesh refinement studies could confirm

and/or quantify this assumption.

 Better definition of the profile geometry could reduce

the shear drag.

 Sensitivity to inlet turbulence

levels still has to be investigated

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Summary and Conclusions

 Lift and stall point are predicted with a high degree of

accuracy even with relatively coarse meshes using the Realizable κ-ε turbulence model with an all Y+ wall function formulation.

 Drag however is highly over predicted with all

turbulence models that were tested. This coincides with the higher power predicted in detailed fan simulations.

 Further work has to be performed on mesh sensitivity

studies as only 2 mesh sizes have presently been investigated.

 Experimental work is underway at Universities to

evaluate drag and lift forces explicitly in order to

• btain a further set of independent aerodynamic data

14th IAHR Conference – December 2009

Thank you for your time ! Questions?

14th IAHR Conference – December 2009

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Mesh Sensitivity on Detailed Fan

FINE MESH (5.3 million cells) COARSE MESH (1.7 million cells)