[american institute of aeronautics and astronautics 46th aiaa aerospace sciences meeting and exhibit...

Wind-Tunnel Replication of Atmospheric Turbulence

with an Emphasis on MAVs

Simon Watkins∗ Benjamin J. Loxton,† and Juliette Milbank‡

RMIT University, Melbourne, Victoria 3000, Australia

William H. Melbourne§

Monash University, Melbourne,Victoria, Australia

Mujahid Abdulrahim¶

University of Florida, FL, USA

Our previous work1 documents the turbulent flying environment of the atmosphericboundary layer (ABL) as perceived by small birds, insects, and Micro Air Vehicles (MAV’s).Now we replicate this environment in a large wind tunnel using different turbulence gen-eration techniques. Through comparison and analysis of turbulence intensities, spectraand length scales it is shown that the natural turbulent environment has been reproducedwith good accuracy for the purposes of furthering research into MAV flight and the flightof birds and insects. In a companion paper2 we describe initial MAV flight trials in thefacility.

Nomenclature

f Frequency in HzI Turbulence intensity with Earth referenceJ Turbulence intensity with body referencek Wave numberV Free stream velocityd Lateral distance between measurement pointsL Integral length scale of the flowt TimeT Measurement sample lengthu, v, w Velocity components in the x, y and z directions respectivelyτ Autocorrelation time delayρ Autocorrelation coefficient functionα Pitch angle [= tan(w

u ) ]∆αij Pitch variation, or the difference in pitch angle between points i and jσ Standard deviationσΛα Pitch variation fluctuation

I. Introduction, Background and Aim

Since the missions envisaged for Micro Air Vehicles (MAVs) are typically of short range reconnaissanceand surveillance,3 MAV operations are of relatively short flying duration, at low speed and are close to

∗Professor, School of Aerospace, Mechanical and Manufacturing Engineering.†Research Associate, School of Aerospace, Mechanical and Manufacturing Engineering.‡Dr, Research Fellow, School of Aerospace, Mechanical and Manufacturing Engineering.§Emeritus Professor, Department of Mechanical Engineering.¶Dr, Research Engineer, University of Florida, FL, USA

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American Institute of Aeronautics and Astronautics

46th AIAA Aerospace Sciences Meeting and Exhibit7 - 10 January 2008, Reno, Nevada

AIAA 2008-228

Copyright © 2008 by Ben Loxton, Simon Watkins, Juliette Milbank, and Mujahid Abdulrahim. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

the ground. For their entire flight duration MAV’s are thus immersed in the lower part of the AtmosphericBoundary Layer (ABL) and for an appreciable part of the flight duration are operating in what wind engineerscall the roughness zone, where the wakes of the local surface obstructions are significant. Since one of thekey advantages of MAVs is to offer additional information than that afforded by direct line of sight i.e. flownover hillsides, around street corners or up to a window for reconnaissance and surveillance,4 it is clear thatthe operating environment is one which involves flights over, around, or through both natural and man madeobjects. The wind environment of cities is known to be complex and the wakes of ground-based objectsincrease the turbulent energy levels in the ABL. When the atmospheric wind is present, the operationalenvironments of MAVs are turbulent; far more so than larger aircraft that cruise well above the ABL.

Etkin5 notes that the turbulence present in the atmosphere is composed of two components; discretegust inputs and random continuous turbulence. The former comprises of discreet gusts which are isolatedencounters with steep gradients, such at the edge of convective disturbances or in the wake of a large object.The latter can be described as a chaotic motion of the air that needs to be described via its statisticalproperties. Etkin5 gives important references for describing this random turbulence using statistical quan-tities utilised by meteorologists and wind engineers including; stationarity, homogeneity, isotropy, time anddistance scales, and correlations and spectra.

The atmospheric wind environment has been been studied in detail over much of the past century by windengineers,6–9 although generally at much larger scales, (both temporary and spatially) than is desirable forMAVs. Data were obtained via large scale fixed (with respect to the Earth) anemometers, thus the frame ofreference is in the wind axis. For vehicles moving through the ABL, the interest is in the frame of referencewith respect to the moving vehicle. Our recent work has focused on building an understanding of the flightenvironment within the ABL at scales relevant to small flying aircraft, birds and insects, with the focus onmeasuring and understanding the finer scale turbulent structures found in the lower region of the ABL.10

This study is described in detail in previous work,10 where the authors gathered data by mounting a bankof multi-hole pressure probes11,12 on to a mast above a car, 4m above the road, and ”flying” them throughthe atmosphere under a range of different wind speeds, conditions and through different terrains.

Piloting small MAVs has shown that one of the largest challenges to outdoor MAV flight is overcomingthe effects of turbulence, particularly small vortices and eddies that are inherent in atmospheric turbulenceand that produce seemingly random roll and pitch inputs. This is due to the relative size of structures inatmospheric turbulence with respect to MAVs. It is considered that this restriction would curtail the numberof possible days per year that they could be used for outdoor activities. Thus whilst the miniaturisation ofthe propulsion and control technology has enabled more sophisticated systems to be developed for MAVs, asignificant challenge is now posed by the flight environment; particularly as the scale of the craft reduces.Like their natural counterparts, MAVs are of light weight and have low moments of inertia, which, whencoupled with their small size, makes them very prone to disturbances from atmospheric turbulence. MAVsdo not have the advanced, interactive control systems of birds and insects.

It is evident that in order to design an MAV capable of successful outdoor flight, a development environ-ment that can simulate or replicate the conditions found in the lower parts of the ABL is desirable. Whilstit is considered that simulation in the computational domain (CFD) would provide a useful developmentenvironment for this task, the computation necessary to accurately replicate such complex flow fields is notyet available. This leaves experimental methods as the only practical solution, at least for the next few years.

By adapting a wind tunnel facility to physically replicate aspects of the turbulent wind conditions foundover a range of terrains and wind conditions, a more detailed analysis of an MAVs ability to achieve itsmission objectives could be made. Not that these techniques are now commonplace for the study of flowsaround and loads on buildings.

Thus our objective is to create a repeatable, realistic turbulent environment for the study of naturaland man-made MAVs. Our study is restricted to generating well mixed or random turbulent flow, ratherthan investigating discreet gusts and local effects (such as might be found in extremely close proximity tobuildings etc). This paper describes the replication of selected turbulent flight environments of MAVs, andcompares flow parameters between the outdoor measurements10 to those in the tunnel for a range of differentwind speeds and turbulence generation methods.

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II. The Wind Tunnel Facility

The wind tunnel facility chosen for this study was the large industrial wind tunnel located at MonashUniversity in Melbourne, Australia. This is the largest wind tunnel in the Southern Hemisphere, and issufficiently large to permit flight of MAVs of upto about 1m span. A schematic of the wind tunnel isshown in Figure 1. The wind tunnel has a closed-circuit and was designed as a multiple use facility withthree working sections: (i) an automotive semi-anechoic, open-jet test section on the lower level; (ii) a windengineering, closed test section on the upper level and; (iii) a general purpose test section, also on the lowerlevel.

The tunnel is driven by two 5-meter diameter, fixed pitch, variable speed, axial fans situated at the startof the lower circuit. The modified wind engineering test section that was used to take the measurements forthis research (and to also fly fully instrumented MAVs as described in a companion paper2) has a 4-meterhigh by 12-meter wide by approximately 50-meters long test section and is typically used for simulations ofthe ABL in wind engineering studies. The tunnel has several features which enable considerable geometricchanges. These include the ability to reconfigure the downstairs open-jet section via changes to the jet (amovable top flap which can either be up or down at the nozzle exit) and a collector which can be moved intoa ”forward” or ”back” position, see Figure 1. Whilst these geometric changes are primarily for reconfiguringthe geometry for various automotive applications, the effects on the flow in the top test section can beconsiderable. In addition to geometric changes, a series of grids and screens were also used to further changethe flow for this work. The result is a well mixed turbulent flow in the top section, of different turbulencecharacteristics depending on configuration. Table 1 shows the various combination of tunnel configurationsused during testing.

Table 1. Wind Tunnel Configurations Used During Testing

Tunnel Configuration Jet Position Collector Presence Screen Presence Grid Presence1. Baseline down forward no - -2. Baseline down forward yes - -3. Effect of jet position up forward no - -4. Effect of jet position up forward yes - -5. Effect of collector position up back no - -6. Effect of collector position up back yes - -7. Effect of grid presence up back no 300mm8. Effect of grid presence up back no 600mm9. Effect of grid presence up back yes 600mm

III. Data Acquisition, Processing and Turbulence Generation

In order to measure the turbulence levels in the wind tunnel, similar instrumentation to that used in theprior on-road testing10 was utilized. This configuration consisted of four Cobra Probes11 mounted on anaerodynamically faired bracket, with probe separation variable in the lateral direction from 2-6in. (NB Cobraprobes are dynamically calibrated pressure probes, which provide time-averaged and time accurate velocityand pressure information. They have a cone of acceptance of 90 degrees and a relatively flat frequencyresponse to 2000Hz). The bracket with probes was mounted at the center of the wind-engineering testsection (Figure 4 ), and measurements were taken for different tunnel configurations in order to investigatethe turbulence obtained within the test section.

Measurement samples were 5 minutes in length and data were acquired at 5 kHz and then filtered anddown sampled to 1.25 kHz to avoid aliasing effects.

Here the turbulence characteristics were calculated with respect to the moving aircraft, where the aircraftwould essentially be flying at one position in the tunnel. To denote the fact that the turbulence intensitieswere related to the moving aircraft rather than fixed relative to a ground-mounted anemometer as is normalin wind engineering, we use the terminology of Ju etc. (Note in wind engineering the quantity Iu is normally

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Figure 1. Schematic of the Monash / RMIT Wind Tunnel.

used to denote Intensities with a Earth frame of reference). Details of the relationship between the Earthand aircraft frame of reference can be found in a previous paper.10

Turbulence intensities in the three axis system, Ju, Jv and Jw are defined as the standard deviation ofthe fluctuating signal divided by the mean longitudinal velocity V , see equation 1.

Ju =

√(u′)2

V, Jv =

√(v′)2

V, Jw =

√(w′)2

V(1)

whereV =

√u2 + v2 + w2 (2)

To estimate the longitudinal integral length scales the auto-correlation method was used.1 This assumesTaylors frozen turbulence approximation where the constant mean (advection) velocity is large with respectto the turbulence fluctuations, thus the eddies or vortex lines do not change appreciably in shape as theypass a given point. In this situation the auto-correlation with time delay, τ , can approximate the spacecorrelation with separation −Vrτ ,13,15 Equation 3 shows the calculation for length scale, where c is the firstzero crossing of the auto-correlation coefficient function ρuu (equation 4) of the u-component velocity and sis the time delay or lag.

Lx = V

∫ c

0

ρuu(s).ds (3)

ρuu(τ) =lim

x→∞

1T

∫ T

0

{u(t)− u}{u(t + τ)− u}dt

(σu)2(4)

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Figure 2. Wind Engineering Test Section.

The corresponding longitudinal length scales for the y- and z-axes, Ly and Lz, can be calculated byrespectively substituting v or w for u in the above equations. Further details of the data processing methodsand assumption, including the outdoor measurements, can be found in prior work.10

Spectral levels of flow velocity components give an indication of the magnitude of the velocity fluctuationin a given component versus frequency. Spectral levels, as they are plotted here, are in units of (m/s)2/Hz(or mean square velocity per Hertz) and each point on a spectral plot is essentially the variance of thevelocity component at that frequency. In contrast turbulence intensities (Ju, Jv, Jw) are overall normalisedmeasures of the velocity-component fluctuations, thus a measure of the overall relative gustiness. Spectrallevels and turbulence intensities are thus related, with the latter being a single figure estimate of the totalrelative velocity fluctuations without any frequency information. However, in simulating flow conditions fordynamic and response applications it is important to simulate the flow fluctuations at frequencies of interest,rather than the overall turbulence levels. Thus spectral levels provide important information that turbulenceintensities do not. For this reason wind tunnel and atmospheric turbulence data are compared by plottingtheir energy spectra versus wave number, k = f/V (essentially, frequency scaled with mean flow speed, orinverse wave length of the turbulence structures).

Since the potential roll inputs of MAVs were of interest, additional statistical measurements were soughtto document the variations in pitch angles as a function of lateral spacing.

Several different methods for changing the levels of turbulence present in the wind tunnel were used(Table 1), including changing the configuration of the test section, and the use of different screens and gridsto reproduce turbulence with similar properties in terms of energy density levels and length scales as thosefound outside under different conditions.10

Moving the top flap up and collector forward gave the largest scale and longest frequency turbulencesimulation. To give a range of smaller scales, turbulence grids were also used. These were placed just afterthe acoustic splitters, upstream of the lower test section. One had grid elements of 300mm width (Figure5), and the other had 600mm (Figure 6). A optional fine mesh screen could also be placed at the entranceof the top test section which had the effect of reducing the turbulence levels in the test section.

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Figure 3. View Looking Downstream Through the Automotive Open-Jet Test Section Showing the Variable GeometryCollector

Figure 4. The First Author in the Wind Tunnel with Measurement Equipment

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Figure 5. Illustration of 300mm Grid

Figure 6. Illustration of 600mm Grid

IV. Results, Discussion and Comparison to Outdoor Measurements

The results from the tunnel configurations in Table 1, with and without the screen, are summarized inFigures 7 and 8 respectively. The results are plotted as energy spectra of the u-component velocity wherethe frequency is non-dimentionalized by wave number. Only the results for the u component are shown herefor brevity.

IV.A. Velocity Fluctuation Analysis

The turbulence intensity levels and length scales were measured for a wide range of outdoor conditions andflight speeds. A representative sample is summarised in Table 2. Those measured in the wind tunnel aresummarised in Table 3.

Table 2. Turbulence Intensities and Integral Length Scales in Outdoor Measurements

Terrain Type Mean Wind Speed (m/s) Ju (%) Jv (%) Jw(%) Lx (m) Ly (m) Lz (m)Smooth (Open) 22 5.3 7 4.1 39 38.1 2.5Medium (sparse) 7.2 13.2 8.8 8.3 30.2 5.2 6.1Inner City (Built-up) 10.1 9.4 11.2 5.7 23.6 17.2 2.3

Figure 7 shows that without the use of the screen, changes in the tunnel configuration have a significanteffect on the turbulence levels. Moving the jet up from the baseline configuration reduces turbulence levelsby almost half, and moving the collector back then further reduces the turbulence levels by another third.The addition of the grids upstream is shown to have minimal effect on the turbulence levels. The additionof the screen (Figure 8) gives overall lower turbulence levels during all configurations. However, this alsohas the effect of reducing the differences between the various test configurations. Moving the jet up and

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Table 3. Turbulence Intensities and Integral Length Scales with Different Tunnel Configurations in Table 1

Tunnel Configuration Tunnel Speed (m/s) Ju (%) Jv (%) Jw(%) Lx (m) Ly (m) Lz (m)Configuration 1 8.5 25.9 22.1 20.3 1.73 0.64 0.62Configuration 2 9.5 6.6 6.2 5.7 0.87 0.48 0.40Configuration 3 10.3 13.8 12.0 10.3 1.69 0.62 0.41Configuration 4 10.4 5.3 4.9 4.4 0.78 0.39 0.27Configuration 5 10.5 7.9 6.8 6.0 1.13 0.59 0.28Configuration 6 10.2 4.6 4.0 3.7 0.58 0.32 0.26Configuration 7 10.2 8.4 7.3 6.3 1.46 0.65 0.31Configuration 8 10.1 8.8 7.4 6.5 1.11 0.65 0.30Configuration 9 10 5.2 4.3 3.9 0.72 0.37 0.26

collector back again reduces the turbulence levels. As before, use of the grids has only a minimal effect onthe turbulence levels in the upper test section. These results show that a range of turbulence intensities canbe generated in the wind tunnel that cover the typical turbulence intensities measured outdoors.

Figure 7. Energy Density Spectrum, all Tunnel Configurations no Screen.

Figures 9, 10 and 11 show energy spectral levels of the flow velocity found in the Wind Tunnel, comparedto data gathered in three outdoor locations of differing terrain. Above a wave number (k) of 0.5, the windtunnel and atmospheric data coincide very well, and show that a wind tunnel configuration can be found tosimulate the turbulent velocity fluctuations, for a range of wind and terrain conditions.

In contrast, the overall integral length scales (Luvw) are significantly different between the wind tunneland that of the atmospheric data, with the latter usually being at least three times larger than the former.This is because the atmospheric turbulence includes large length scale (i.e. low frequency) turbulence thatis not found in the wind tunnel. This is reflected in the spectral plots by the difference between the windtunnel and atmospheric data below a wave number of 0.5.

It had previously been determined that the frequency range of most relevance to an MAV with a 150mm wingspan is between wave numbers of 0.7 to 65,10 and so the agreement in spectral levels between the

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Figure 8. Energy Density Spectrum, all Tunnel Configurations with Screen.

wind tunnel and atmospheric data within this range is very good. From this we can conclude that variousconfigurations of the wind tunnel can simulate the relevant turbulence for light to moderate wind conditionsin built-up areas to more open terrain well. For the testing of larger aircraft (UAVs and manned craft),where the low frequency turbulence in the tunnel is deficient, there are several options to explore, includingactive generation methods (NB such methods are now being used for full size automotive testing,1617) andmodel scale testing.5 For smaller MAVs however these low frequency disturbances are many times largerthan the vehicles themselves and could be considered to be ”quasi-static”.

IV.B. Fluctuation of Pitch Angle with Time and Lateral Separation

While the energy spectra and turbulence intensity are useful quantities for describing the flow field in terms ofvelocity fluctuation, the transience in flow pitch angle is also of interest. Good agreement in vertical velocityspectra was found between outdoor and tunnel measurements, and a typical plot of pitch angle spectraldensity from outdoor measurements can be seen in Figure 12. Also evident are corresponding spectra fortwo tunnel configurations, illustrating the ability for the tunnel to replicate the outdoor pitch angle spectra.However to gain a deeper understanding of the effects of turbulence on roll inputs is also useful to examine thevariation over several laterally separated points in space. The stick-fixed perturbations in roll of an aircraftis due to roll inputs from turbulence, thus a useful quantity to consider is the local pitch angles at multiplepoints in space across the virtual wingspan. This analysis gives a means of estimating the likely stick fixedroll response of a vehicle flying through turbulence. A useful quantity for analysing the difference betweentwo laterally separated points in space is pitch variation. Pitch variation is defined here as the difference inpitch angle between two points in space (i, j), or in this case two laterally spaced flow measurements usingthe Cobra Probes.

4αij = αj − αi (5)

The standard deviation of the pitch variation, σ∆α has a direct influence on the difference in lift generatedat the two points on the wing span, and therefore gives an indication of the roll input. It does not, however,take account the frequency information contained within the turbulent structures, thus is analogous to the

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Figure 9. Comparison of u-Component Spectral Levels in a Gentle Breeze: Metropolitan Area, Terrain 7-2 (Built-UpUrban Area, 2-3 Story Buildings, with Prevailing Wind from Across the City).

Figure 10. Comparison of u-Component Spectral Levels in a Moderate Breeze: Low Suburbs, Terrain 6-2 (Low,Well-Spaced Buildings and no High Trees).

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Figure 11. Comparison of u-Component Spectral Levels in a Fresh Breeze: Open Farmland, Terrain 4-2 (Low Cropsand Plant Cover, Occasional Obstacles Separated by Less Then 20H)

way that turbulence intensities are overall measures of velocity fluctuations but contain no information aboutthe magnitude of those velocity fluctuations with frequency.

Figure 13 shows the standard deviation of the pitch angle plotted against lateral separation (probespacing) for both the wind tunnel data, and the atmospheric data. These data have not been normalised,but possible methods of normalisation are discussed in.1 It is most interesting to note that even at veryclose lateral spacing there are considerable potential for roll inputs.

V. Conclusion

Atmospheric turbulence characteristics, including intensities and spectra, were physically replicated ina very large wind engineering wind tunnel for a range of outdoor flight conditions relevant to MAVs. Atsmall scale it was previously shown that the roll inputs from turbulence were significant for MAVs. It wasconcluded that relative turbulence characteristics (including fluctuating pitch angle) can be simulated for theentire relevant frequency range for 150 mm (6 inch) span MAVs, but that 1 m (40 inch) span MAVs mightrequire additional active turbulence generation techniques to augment the low frequency components. Thelatter would be required in order to adequately replicate the larger length scales that affect the roll inputsof the larger span MAVs. It was noted that such techniques exist and should prove effective to achieve thisgoal.

This controlled replication of aspects of turbulence experienced by MAVs permits new understanding anddevelopment (and hopefully offers enhanced utility) for MAVs in real world conditions and can be used in twomain ways. 1) Flight experiments of existing MAVs, in order to measure the sensitivity and controllabilityof man-made craft and perhaps bird and insect flight enabling insight into how nature has evolved systemsto permit flying in turbulent winds. 2)Measurements of flight loads and inputs from atmospheric turbulencethat can be used to develop aircraft platforms to mitigate the effects of turbulence, and control systems toenable stable viewing platforms.

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Figure 12. Comparison of Pitch Angle Spectral Levels in a Fresh Breeze (IAS 8.7 m/s, Ground Speed 0 m/s): OpenFarmland, Terrain 4-2 (Low Crops and Plant Cover, Occasional Obstacles Separated by Less Then 20H).

Figure 13. Standard Deviation of Pitch Variation Fluctuation Levels for Both Wind Tunnel and Atmospheric Datawith no Normalisation

Acknowledgements

The authors would like to acknowledge the assistance of the United States Air Force, specifically the AirForce Office for Scientific Research (AFOSR) for providing the funding for this research, Monash University

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for the use of the wind tunnel, and the technical, administrative and IT staff at RMIT University for theirsupport and hard work during the project.

References

1Milbank, J., Loxton, B.J., Watkins, S. and Melbourne, W.H.,Replication of Atmospheric Conditions for the Pur-pose of Testing MAVs , Final Report, USAF Project No: AOARD 05-4075, RMIT University, 2005. Available gratis viahttp://mams.rmit.edu.au/cibbi0b6g34o.pdf and http://mams.rmit.edu.au/nqjhdfdjn29o.pdf

2Loxton, B., Abdulrahim, M., Watkins, Trivalio, P. , An Investigation of Fixed and Rotary Wing MAV Flight in ReplicatedAtmospheric Turbulence AIAA Journal, In Press.

3Anon, UAVs Applications are Driving Technology Micro Air Vehicles, UAV Annual Report, Defense Airborne Recon-naissance Office, Pentagon, Washington, DC, 6 November 1997, pp. 32.

4Burger, K., Micro Air Vehicle Demo Approaching, Janes Defense Weekly, Janes Publications, UK, Vol 36, Issue No14, pp 6, 12 September 2001.

5Etkin, B, Turbulent Wind and Its Effect on Flight, AIAA Journal of Aircraft, Vol. 18, No. 5, May 1981, pp 327-3456Holmes, J. D., Wind Loading of Structures, Spon Press, London, 2001.7Sutton, O.G., Micrometeorology, McGraw-Hill Books, New York, 1953.8Van Der Hoven, I., Power Spectrum of Horizontal Wind Speed in the Frequency Range from 0.0007 to 900 Cycles per

Hour, Journal of Meteorology, Vol. 14, 1957, pp 160-164.9Lawson, T.V., Wind Effects on Buildings, in 2 volumes, Applied Science Publishers, London, 1980.

10Watkins, S., Milbank, J., Loxton, B.J., and Melbourne, W.H., Atmospheric winds and their effects on Micro Air VehiclesAIAA Journal, v.44, 11, Nov 2006, pp.2591-2600.

11Watkins, S., Mousley, P., and Hooper, J., Measurement of Fluctuating Flows Using Multi-Hole Probes, Proceedings ofthe Ninth International Congress on Sound and Vibration, 8-11 July, Orlando, Florida, International Institute of Acousticsand Vibration, Alabama, USA, 2002.

12Hooper, J.D., and Musgrove, A.R., Reynolds Stress, Mean Velocity, and Dynamic Static Pressure Measurement by aFour- Hole Pressure Probe, Experimental Thermal and Fluid Science, Vol. 15, No. 4, 1997, pp.375-383.

13Hinze, J.O. Turbulence, 2nd edn, McGraw Hill, New York.1975.14Cheung, J.C.K., Eaddy, M. and Melbourne, W.H. Active generation of large scale turbulence in a boundary layer wind

tunnel, Proceedings of the 10th Australasian Wind Engineering Society Workshop, Sydney, Australia.200315Pope, S.B. Turbulent Flows, Cambridge University Press, Cambridge, UK,2000.16Cooper, K R., Watkins, S., The Unsteady Wind Environment of Road Vehicles, Part One: A Review of the On-road

Turbulent Wind Environment., SAE International, Paper Number 2007-01-1236, 200717Cooper, K R., Watkins, S., The Unsteady Wind Environment of Road Vehicles, Part Two: Effects on Vehicle Develop-

ment and Simulation of Turbulence, SAE International, Paper Number 2007-01-1237, 2007

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