Experimental and Computational Investigation of Flow Distortion Around a Tubular Meteorological Mast

Transcription

1 CanWEA Conference Toronto, Ontario October 2005 Experimental and Computational Investigation of Flow Distortion Around a Tubular Meteorological Mast Matthew Filippelli - Pawel Mackiewicz mfilippelli@awstruewind.com - pmackiewicz@awstruewind.com AWS Truewind LLC 255 Fuller Road, Suite 274 Albany, New York

2 Introduction The accuracy of wind resource assessments can be affected by the meteorological mast. Two- and three-dimensional CFD models were created to examine the effects and mitigate induced error

3 Procedure Computational Model Created 2D and 3D models of tubular met mast were designed Physical and environmental parameters were chosen Model Runs Executed 2D and 3D models run on Fluent v. 6.0 CFD software Numerous case studies were executed to study varying tower and flow configurations Field Measurement Comparisons Selected long term, well-documented data sets North America Compared results with several instrumentation configurations

4 2D Computational Model Parameters Environmental Parameters: Representative of common North American monitoring environments Density: ρ= 1.18 kg/m³ Viscosity: μ= x 10 5 Turbulence Intensity: ti= 12.5% Speed: V= 7.5, 11, 15 m/s Physical Parameters: Typical met mast dimensions 6 in ( m) diameter cylinder Variable surface roughness m Boom length (7.5 diameters from tower axis) Model Parameters RANS equation based, K-epsilon turbulence model Mesh Size: ~20,000 cells

5 2D Case Results: Model Output Case 1 Dashed line indicates measurement distance Flow Direction Speed Ratio Dimensions in Meters

6 2D Case Results: Case Comparison Case 1: High Roughness Tower Case 2: Tower w/ Signal Cables Percent Speed Deviation Case 1 Case Angular Position (Degrees)

7 Comparison with Existing Models: Iso-speed Plot RED: Case B CFD Black: IEA and IEC potential flow Flow Direction

8 2D Data Analysis: Percent Speed Variation at Standard Instrument Stand-off 2-D model output, normalized total speed 1.15 Percent Speed Deviation Angular Position (Degrees)

9 2D Data Analysis: Percent Speed Variation for Two Booms (330 and 242 ) 2-D model output, normalized total speed for two boom directions 1.15 Percent Speed Deviation Angular Position (Degrees)

10 2D Data Analysis: Output Ratio between two Booms (330 and 242 ) º D model output, ratio for two boom directions º 110 Percent Speed Deviation Angular Position (Degrees)

11 2D Data Analysis: Tower Validation CFD Model and Mid-Tower Data (30 m) Percent Speed Deviation CFD Model CFD Case 1 30m Tower Data 0.85 Tower Measurement (30m) Angular Position (Degrees)

12 3D Computational Model Parameters Environmental Parameters: Representative of common North American monitoring environments Density: ρ= 1.18 kg/m³ Viscosity: μ= x 10 5 Turbulence Intensity: ti= 12.5% Speed: V= 7.5 m/s Physical Parameters: Tower-top model 6 in ( m) diameter hollow cylinder, 6 m total height Surface roughness 0.15 in (3.81E-3 m) m Boom length (7.5 diameters from tower axis) Model Parameters RANS equation based, K-epsilon turbulence model Mesh Size: ~70,000 cells

13 3D Case Results: Model Output Speed Ratio for Y-Z Plane (Flow into Page) Speed Ratio for X-Z Plane (Flow Left to Right) Dimensions in Meters

14 3D Data Analysis: Percent Speed Variation Radially Outward from Tower (Y-Z Plane) Percent Speed Deviation Radial Distance (Tower diameters)

15 3D Data Analysis: Percent Speed Variation Radially Outward from Tower (X-Z Plane) Percent Speed Deviation Radial Distance (Tower diameters)

16 Conclusions Tower surface irregularities impact flow at typical instrument stand-offs Use Longer booms to lower induced error Significant 3D flow effects occur ~6 diameters above and below the tower top, but can be avoided Locate side-mounted booms at least 6 mast diameters below the top Mount tower-top instruments at least 6 mast diameters above the top

17 Future Work Additional model validation against field measurements Refinement of CFD model construction and parameters Case-specific field or tunnel testing Develop correction routines for tower data sets

18 Thank You