Quantitative Flow Visualization for Large ScaleWind Tunnels

R. Bömmels, M. Machacek, A. Landolt, and T. Rösgen

Institute of Fluid Dynamics, ETH Zurich, Switzerland

Introduction

Despite the increased use of numerical simulations in the development andperformance optimization of aerodynamic vehicles wind tunnel tests still are offundamental importance in the related engineering design process. In order tokeep the cost down and to increase the data return from the expensive meas-urement campaigns, there is an interest in improving and expanding the diag-nostic tools available.

Recent developments in modern measurement technology, especially in theareas of digital imaging and photonics, have led to the introduction of a num-ber of computer-based, quantitative flow visualization tools. While these tech-niques have rapidly gained acceptance in laboratory research, their introduc-tion into the domain of commercial testing has been slower. This may be notonly due to the cost involved but also for a number of technical reasons.

The reliability, precision and flexibility of the new methods still have to beimproved to convert them into turn-key tools. Furthermore, there are someproblems associated with the scale-up from bench-top hardware to systems op-erating in considerably larger and less controlled environments.

The paper will address some of those scaling issues. The specific require-ments for large scale testing will be analyzed and a number of recent flow visu-alization and measurement techniques are described which should be wellsuited for such applications.

Generic Issues in Large Scale Flow Visualization

Image based flow measurements and visualization techniques provide a num-ber of desirable features such as non-intrusiveness, remote access, and the si-multaneous processing of multiple measurement stations. This last feature en-ables also the computation of spatial gradients in unsteady flows, which isuseful in the detection and analysis of spatial flow structures. These propertieshave led to the widespread introduction of such techniques in the laboratory,

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where for example particle image velocimetry (PIV) has developed almost intostandard method within the last ten years (Kompenhans 2000).

In large scale facilities such as wind tunnels, there are a number of genericproblems which have delayed a similar progress. Although these problems areat times simple and of a purely technical nature, they still can affect the func-tionality and performance limits of various imaging techniques at a very fun-damental level.

Most camera-based measurement methods require some form of active sceneillumination. Dependent on the capabilities of the cameras (high speed or slowscan, direct integration or intensified, large or small dynamic range etc.) thislighting may have to be pulsed or continuous, wide band (white) or spectrallynarrow-band and often of a considerable intensity. Incandescent lamps, lasers,high-powered flash lamps or other, more specialized sources can usually befound to meet these requirements. However, when arbitrary aerodynamicmodels are to be inserted into the field of view, spurious surface reflectionsmay arise which cannot easily be controlled or eliminated. Since it is often theflow close to the model surface which is of particular interest, the cameras’ pix-els can become saturated and the information is lost where it counts most.Finding a locally optimized arrangement of illumination and observation an-gles may temporarily solve the problem but it will arise immediately again ifthe configuration is changed.

Another fairly common requirement in air flow diagnostics is the generationof flow seeding. Usually micron-sized particles or droplets have to be chosen sothat the tracers can follow the flow with a sufficient fidelity. Since the back-scatter signatures tend to be small, fairly high tracer densities have to be gener-ated which may affect the overall visibility of the model and the optical accessin general, defeating in part the original purpose. More importantly, in manyimaging techniques the individual tracers have to be spatially resolved by therecording device in order to extract the desired information. This puts con-straints on the cameras’ resolution and optical magnification which may inturn severely limit the size of the field of view. In addition, there are issues re-garding the chosen tracers’ lifetime (too short, too long) and the environ-mental and health impact of the sometimes corrosive or poisonous substancesinvolved.

For imaging techniques that require either long time integration periods orcomparisons with reference images, another problem may arise from a possiblelack of configurational stability. Model movements on the supports, facility vi-bration and other uncontrolled effects may affect the precision with which theposition of the measurement points on the model surface can be determined.In techniques such as pressure sensitive paint monitoring, where a pixel-by-pixel referencing is necessary, even very small displacements can create signifi-cant changes in the ratio images.

Finally, there are simple operational and financial constraints that have to beaccommodated. While the actual data taking with an imaging setup may bedone in a few seconds, the calibration and adaptation of that setup can be anhour-long activity. This may lead to the situation where a specific measure-ment technique is ruled out purely because of its operational complexity.

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Taking into account these technical constraints, there remain a few basicchoices which have to be made in the design and selection of a large scale,quantitative flow visualization system.

In the laboratory, a certain preference has developed for imaging configura-tions which exploit the Eulerian view of the flow such as in PIV. This may bedue to technical reasons (e.g. the need for strong illumination, available only inlight sheets) but is also related to the interest in spatial flow structures and gra-dient properties. As a consequence, the flows under investigation are often“tailored” to accommodate an essentially planar image acquisition philosophy.Furthermore, the amount of raw data produced and the associated transfer andstorage requirements for a full 3-dimensional measurement grid would becomeprohibitively large.

In flows around complex model surfaces, three-dimensionality is almost al-ways present and a volumetric view of the measurement domain is necessary.In order to keep the data complexity at a reasonable level, it may be more ad-vantageous to rely on Lagrangian techniques, which track localized flow featuresin time rather than providing spatially resolved snapshots.

A similar duality is present when one looks at the data processing philoso-phies. The established approach is based on a time-global approach where alldata acquired during a measurement run are stored and utilized in a post-processing step to extract the desired information. The need for fast, near real-time data visualization and efficient data storage, however, does favor incre-mental strategies where the incoming data are processed “on the fly” with onlya limited knowledge of the temporal flow evolution. Especially for Lagrangiantechniques (e.g. particle tracking methods), the choice of such an incrementalapproach does have a significant impact on the overall processing scheme.

Finally, a balance has to be found between the requirements for fast dataanalysis / presentation and the achievable measurement accuracy. For visuali-zation-oriented schemes the temporal coherence of the data may be more im-portant than the ultimate precision of each individual data point reading, cre-ating a requirement for efficient error rejection, but not necessarily for errorcorrection. In other situations, the priorities are reversed in that accuracy ismore important than speed and an increased temporal effort (including aver-aging multiple measurements or recursive processing) is considered acceptable.

Looking at these considerations, one may state that large scale diagnosticapplications create their own set of requirements which may be different fromthose applicable to laboratory-style research. The measurement techniqueswhich are to be applied have to be adapted especially regarding their opera-tional characteristics. At times, even the development of new methods de-signed specifically for large scale environments may become necessary.

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Candidate Technologies and Techniques

At the Institute of Fluid Dynamics of ETH, a medium sized wind tunnel (2mx 3m test section, see Fig. 1) is being operated for educational and researchpurposes, which was built in the 1930’s by J. Ackeret.

Fig. 1: Medium scale wind tunnel at IFD / ETHZ

This facility is also used as a test bed for a number of advanced quantitativeimaging techniques which are being developed with true large scale applica-tions in mind.

Pressure sensitive paints are being studied in cooperation with RUAG Aero-space (CH). Being a technique of obvious potential for wind tunnel applica-tions, the research concentrates specifically on ways to eliminate the inherenttemperature sensitivity of the fluorescent paints used and the wind-on / wind-off calibration procedure (see also Engler 2000).

A pulsed infrared thermography system has been installed to provide a toolfor the rapid visualization of laminar-turbulent transition and separation lineson model surfaces. It utilizes a high power stroboscope (7500 W, approx. 7 J /flash) in conjunction with a midwave (3-5mm) infrared camera (20 mKNETD) to detect the subtle changes in surface heat transfer associated withthose flow phenomena. The technical challenge lies in the development of im-aging strategies which are independent of the model’s surface structure andcomposition which can strongly affect the infrared signature (Le Sant 2002).

In the area of flow velocimetry, a Doppler global velocimeter is being devel-oped based on a custom narrow band pulsed laser with two independent os-cillators. This permits the simultaneous use as a PIV system for comparisonand the measurement of 3-dimensional velocity vectors with a single camera /single view point arrangement.

At the same time a particle tracking velocimeter is being used to provide aLagrangian view of the flows under investigation. A pair of high speed camerastracks the motion of helium-filled soap bubbles which are used as low-inertia

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tracers. The resulting three-dimensional path lines can be used to determinevelocities and topological information.

Finally, activities are under way to develop a simple real-time visualizationtool to enhance the information obtained from operating standard smokeprobes. Here the emphasis is strictly on the fast processing of the visual infor-mation, not on the extraction of detailed quantitative information.

In the following, three of the above mentioned examples will be describedin more detail as they highlight the points made about large scale diagnostics.

Doppler Global Velocimetry

Doppler global velocimetry is a planar imaging technique designed to measurethree-dimensional velocity components. Instead of analyzing the displacementof individual tracers (as in particle tracking velocimetry – PTV) or of smalltracer clusters (as in particle image velocimetry – PIV) one looks at the opticalDoppler shift of the moving tracers (Mosedale 2000, Samimy 2000). Thegreat advantage in doing this is that the individual particles do not have to beresolved anymore by the recording camera. Any feature that moves with theflow and crosses the illuminating light sheet will create the desired signature.The camera magnification can be set so as to image the whole test section andone of the major drawbacks of PTV / PIV - the limited recording area - isavoided.

Fig. 2: Components of a DGV setup – seeded long pulse laser (left),dual camera / iodine filter cell (right)

The price one has to pay for this improvement is twofold. First, the lasersrequired to generate the light sheet have to be very stable and must emit a verynarrow-band radiation with an optical line width of, say, below 20 MHz. Suchlasers are available as CW systems, but the illumination in large facilities de-mands higher intensities only available from pulsed systems (e.g. Nd:YAG la-sers). Here a so-called injection seeder has to be used. A low power, highly sta-ble ring laser injects seed radiation into the cavity of a Q-switched oscillatorwhich leads to a longitudinal mode selection and stabilization. Since the opti-

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cal bandwidth of the emitted radiation is inversely proportional to the pulselength / roundtrip time, the laser cavities can become fairly large (several me-ters, see Fig 2) to support the desired bandwidth reduction.

The frequency shifts caused be the moving tracer clouds are on the order ofthe ratio (flow velocity / speed of light), a very small number indeed. TheDoppler frequencies in the MHz regime cannot be detected directly since oneis using an integrating device (CCD camera) - imaging heterodyne detectorsare not (yet) available for those frequencies. A molecular filter cell filled withiodine is used to convert frequency changes into intensity variations. Tuningthe laser frequency onto the edge of one of the absorption lines of iodine, anyDoppler shift in the imaged scenery can then be observed as a change intransmission (Fig. 3). A camera pair monitors the filtered and unfiltered im-ages and the ratio of both images encodes the velocity observed in the Dopplersensitive direction (Fig. 2). Since each pixel can be processed separately andindependently, a very high spatial resolution can be achieved.

Fig. 3: Operating principle of a molecular filter cell in DGV

The system operated at IFD is more advanced in that it operates two seededlasers in parallel to provide a double pulse capability as well. This facilitates theuse of the lasers in a PIV mode for comparison. As a matter of fact, if the scale-up / resolution issue is not critical, a simultaneous DGV / PIV measurement ispossible. In such an arrangement, the out-of-plane (DGV) and in-plane (PIV)velocity components in the light sheet can be measured with the same camerasystem, creating a true 3-component velocimeter. (Normally, different velocitycomponents are measured with separate camera systems in an all-DGV con-figuration).

Besides the advantages cited so far, DGV as a large scale imaging techniqueis also affected by some inherent limitations. First of all, the intensity ratioingapproach for the computation of velocities makes DGV into an essentiallyanalogue technique. The intensity reading of a single camera pixel is affected

molecular filtering in an io-dine cell

0

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z result: data image

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by a number of factors (sensor non-uniformities, background noise, gain non-linearities, etc.) which have to be carefully compensated. In addition, pulsedlaser illumination leads to the appearance of speckles in the images which haveto be eliminated. Spatial filtering can achieve this, but at the cost of a reducedspatial resolution.

Figure 4 shows an image sequence acquired with a special test target (rotat-ing disc). The processed ratio image shows a component of the overall discrotation velocity vector. Note also that the surface features can be used in con-nection with a second image pair to compute the in plane velocity componentswith PIV.

Fig. 4: DGV images or a rotating disc target: filtered (left), unfiltered (center), processed (right)

3D Particle Path Line Tracking

The path line tracking system which is described next may serve as an examplefor a Lagrangian imaging technique. It is based on the tracking of helium filledsoap bubbles as they flow through the field of view of a stereo camera system(Fig. 5).

In contrast to most established tracking schemes, the bubbles are not im-aged based on a short-time flash exposure but rather using continuous lighting.Their signature on the integrating CCD sensors (120 frames/s) is thus a short,continuous path line segment. The correspondence problem is solved bylooking at the bubble signatures as they cross the boundaries between con-secutive image frames. This creates a unique coordinate in space-time whichcan easily be linked to the complementary second camera view using theepipolar matching condition known from photogrammetry theory. Velocityinformation is derived from the measurement of the bubbles’ displacementwithin and across the individual image frames (Machacek 2002).

While the approach is quite robust, the technique is affected by some of theproblems listed above. Reflections from walls or models can become quiteprominent and the best tracking results tend to be generated in the wake re-gions away from any solid surface. The situation may be improved by increas-ing the number of independent views of the scene (i.e. cameras) but other al-ternatives appear to be more promising in the long term. Preliminary studieshave been performed on the utility of fluorescent and / or smoke filled bubbleswhich could increase the image contrast in the surface reflection regions.

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However, issues regarding the environmental safety and pollution have to beconsidered and have not yet been resolved.

Fig. 5: Schematic of the stereo path line tracking system

Another aspect of generic importance is the photogrammetric calibration ofthe camera systems involved. This can be divided into the tasks of finding thecameras’ inner parameters (e.g. lens distortion, focal lengths) and the outer pa-rameters such as camera orientation in space and relative positioning (Ruyten2002). Especially the measurement of the spatial orientation requires a cali-bration or reference structure of known geometry which has to be inserted intothe field of view. When large volumes have to be imaged these calibrationstructures also tend to become very large and difficult to handle / position.

Fig. 6: Outer parameter calibration using a synthesized calibration target:calibration rod (left); cloud of accumulated reference points (right)

In the present arrangement, the outer parameters are determined using asynthetic target created by moving a calibration rod (length L=0.5m) throughthe measurement volume (see Fig. 6). Two point-source LEDs on the rod cre-

Point source LED’s

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ate a “cloud” of reference points with a known relative distance from whichthe unknown parameters can be deduced (Borghese 2000).

A typical result of a reconstructed path line field is shown in Fig. 7. Thevortex flow behind a delta wing is clearly visible in this 3D rendering of the re-constructed bubble tracks. The color coding of the individual tracks is an indi-cation of the relative velocity of the helium bubbles forming the path lines.

Fig. 7: Flow behind a delta wing visualized using 3D reconstructed path lines

Direct Digital Visualization

As a last example, some elements and results of a direct visualization techniquewill be described. Here the idea is to reduce the amount of data processingand, more importantly, data interpretation, to a minimum and to producesimply an enhanced view of the measurement scene which is interpreted by theobserver rather than the computer.

As a last example, some elements and results of a direct visualization tech-nique will be described. Here the idea is to reduce the amount of data proc-essing and, more importantly, data interpretation, to a minimum and to pro-duce simply an enhanced view of the measurement scene which is interpretedby the observer rather than the computer.

This type of context-insensitive processing can usually be done in real-time,that is faster than the normal camera acquisition frame rate (25 frames/s).Since the data is updated rapidly, no sophisticated noise reduction and / or er-ror handling is required: the human observer is usually very tolerant towardstransient visualization faults.

The main advantage of such a tool, its true interactiveness, is difficult to de-pict in static images. To give an indication, Fig. 8 shows a typical scene from awind tunnel test where a smoke probe is used to visualize the flow around acar. The second image shows a streak line picture which is assembled out ofthe live camera frames in real time. As the smoke probe is traversed, the com-puter builds up a cumulative image of all streak lines as they are extracted fromthe smoke trails.

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The challenges in this type of processing are once again primarily the light-ing and choice of seeding. In addition, fast processing hardware is required butthe rapid increase in computing power means that dedicated hardware such aspipelined image processors can successively be replaced by general purposeCPUs.

Fig. 8: Real-time processing of smoke trails into a cumulative streak line picture

Summary

Quantitative flow visualization based on the processing of remotely acquiredimage data can significantly enhance the understanding and analysis of engi-neering flows. Modern techniques such as Doppler global velocimetry, pres-sure sensitive (fluorescent) paints or infrared thermography make use of ad-vanced lasers and image detectors to provide the optical raw data that aresubsequently transformed into the desired flow information (velocity, tem-perature, pressure, etc.). While the different principles of operation have beensuccessfully verified, there are still a number of generic technical issues whichhave to be resolved before one can expect a routine use in commercial facilities.

Examples were given for a DGV system, a 3D particle tracking velocimeterand a simple yet powerful real-time visualization tool. All systems are designedfor operation irrespective of the large scales involved (several meters field ofview). The control of the illumination and the seeding density remain as aproblem which is directly related to the geometrical size and complexity of themeasurement environment. The scaling issues will remain one of specificproblems in large scale flow diagnostics which are not found on the laboratoryscale and must thus be addressed separately.

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