Measurement and assessment of wind tunnel flow quality

ARTICLE IN PRESS Progress in Aerospace Sciences 44 (2008) 315– 348

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Progress in Aerospace Sciences journal homepage: www.elsevier.com/locate/paerosci

Measurement and assessment of wind tunnel flow quality F. Kevin Owen a,, Andrew K. Owen b a b

Complere Inc., Pacific Grove, CA 93950, USA University of Oxford, Oxford, UK

a r t i c l e in fo

abstract

Available online 10 July 2008

For decades, wind tunnel testing has been conducted in test section environments that have not been adequately or consistently documented. Since wind tunnel flow quality can adversely affect test results, accurate and consistent flow quality measurements are required, along with an understanding of the sources, characteristics, and management of flow turbulence. This paper will review turbulence measurement techniques and data obtained in subsonic, transonic, and supersonic test facilities as they relate to the determination and assessment of wind tunnel flow quality. The principles and practical application of instrumentation used in the measurement and characterization of wind tunnel turbulence will be described. Techniques used for the identification of the sources of wind tunnel disturbances, and the performance of turbulence suppression devices will be outlined. These test techniques will be illustrated with extensive measurements obtained in a number of test facilities. The measurements will provide comprehensive turbulence data that are vital to the assessment and management of flow quality. Procedures designed to assess the potential influence of adverse flow quality on wind tunnel model test performance will also be discussed. & 2008 Elsevier Ltd. All rights reserved.

Contents 1. 2.

3.

4.

5.

6. 7. 8.

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 Flow quality requirements and sources of adverse wind tunnel flow quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 2.1. Review of flow quality requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318 2.2. Status of flow quality measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 Flow quality measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 3.1. Hot-wire turbulence measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 3.2. The hot wire in supersonic flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 3.3. The hot wire in transonic flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 3.4. Recent flow quality measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 3.5. Subsonic and transonic hot-wire calibrations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 Test techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326 4.1. Hot wire and hot film probes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326 4.2. Constant temperature versus constant current operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 4.3. Measurement of total temperature fluctuations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 4.4. Fluctuating pressure measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 Wind tunnel instrumentation and testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 5.1. Data acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 5.2. Data reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Review of flow quality measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Flow quality management recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 Concluding comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

 Corresponding author.

E-mail address: [email protected] (F.K. Owen). 0376-0421/$ - see front matter & 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.paerosci.2008.04.002

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Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Appendix A Flow quality test facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348

1. Background The effects of flow quality on aerodynamic performance have long been recognized as evidenced in this excerpt from a list of duties for 16th century gunners. Also, every gunner before he shoots ought to consider whether the air be thin and clear or close and thick, because a pellet will pass more quickly through a thin and clear air than through a close and thick air. Also every gunner ought to weather the mark according to the hardness of the wind, and the distance unto the mark: for as the wind being with him will cause a pellet to fly beyond the mark according to the hardness thereof, and the wind being against him will cause a pellet to fall short of the mark according to the hardness thereof, so a side wind driveth a pellet wide of the mark. (Nicolo Tartaglia, Nova Scientia, 1537: Cyprian Lucar, trans.) Unfortunately, some five centuries later, wind tunnel testing has, and is currently being conducted in test section environments that have not been adequately or consistently documented and, in general, the effects of flow quality on model test results have been largely ignored. Even the detail-conscious Wright Brothers, who recognized that the laboratory was the return path for their open return wind tunnel and prohibited the movement of people and equipment whilst taking data, did make one mistake, namely: they installed the tunnel’s two-bladed fan upstream of the test section which despite the installation shields, screens and a honeycomb grid must have resulted in increased test section flow turbulence. It is generally recognized that wind tunnel flow quality can affect the steady and unsteady aerodynamic and aerothermodynamic phenomena that may be encountered by model aerospace test vehicles. However, even though the effects of wind tunnel wall interference have long been recognized, little is known about the influence of freestream flow turbulence on steady and dynamic measurements in wind tunnels at transonic speeds. Indeed, few measurements have been made of the characteristics of freestream unsteadiness in transonic wind tunnels. The result is that information on velocity and pressure fluctuations, their amplitude and spectra, is lacking. This information is needed if we are to accurately assess the relationship between wind tunnel and flight behavior. As a minimum, detailed information on the magnitude and spectra of test section velocity and pressure fluctuations are needed to accurately assess the relationship between wind tunnel test model and full-scale flight performance. Wind tunnel disturbances must be measured to the highest accuracy to allow the aerodynamicist to distinguish between aerodynamic, aeroelastic, and Reynolds number effects in order to optimize wind tunnel model designs. With increased commercial competition and the looming energy crisis, there is an increasing need to effect aerodynamic design changes, which will improve fuel economy and performance. Consequently, the effects of wind tunnel flow quality must be addressed, and measurement techniques improved since the effects of adverse flow quality on potential design changes are becoming more difficult to distinguish and document. For example, as we are now concerned with very small changes in

drag count, potential sources of improvement are much more likely to be masked by adverse wind tunnel flow quality. For example, low-frequency velocity fluctuations couple with mechanical model support systems to produce dynamic model motion. These inertial effects may have a non-zero average especially in the measurement of axial force and angle of attack using accelerometers. Angle of attack errors as small as 0.011 can obscure the true test results [1]. The implications can be quite spectacular and can be estimated using the Breguet range equation. For a large high-speed transport, a single drag count translates to 1% of the payload on a long-range cruise mission, for a typical SST it translates to one passenger or 40 NM [2]. Perhaps the major and most widely recognized question is the influence of freestream disturbances on model boundary-layer transition. Fig. 1 gives some indication of this dilemma, where it can be seen that the success or failure of airfoil laminar flow control experiments can be determined by facility flow turbulence levels. Past developments in boundary-layer transition research, particularly those of the NASA Transition Study Group, [3], have stressed the dominant role that freestream fluctuations have on model boundary-layer stability at transonic and supersonic speeds. A major source of scatter in transition data can be attributed to inconsistent choice of transition ‘‘point’’ indicated by different techniques mostly locating positions near the end of the transition region which generally have a strong Mach number and unit Reynolds number dependence. A more complete picture of transition dependence on these parameters can be obtained from experiments in which the locations of the beginning and end of transition are accurately determined [4]. Although these microscopic measurements of turbulent intermittency through the transition region do help eliminate much of the transition ‘‘point’’ measurement uncertainty, freestream disturbances do have

Fig. 1. Effect of turbulence level on trailing-edge transition for wings with suction.

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Fig. 2. Variations of surface pressure distributions on a supercritical airfoil: (a) Mach number effect and (b) angle of attack effect, M ¼ 0.72.

adverse influences on flow stability. Not only do the external fluctuation amplitudes influence transition but also their energy spectra are particularly significant. However, the details of the coupling between model shear layer and freestream flow turbulence still remain largely unresolved. Consistent measurements of wind tunnel freestream environments would help in this work. Flow turbulence is three-dimensional, and streamwise turbulence produces fluctuations in dynamic pressure and local Mach number, which lead to fluctuating inviscid forces on the model. The two normal components of turbulence produce fluctuations in the angles of incidence and sideslip. Pressure distributions can be altered by these fluctuations in attitude and Mach number as small variations can produce significant changes in their shape at transonic speeds. For example, the surface-pressure distributions measured on a supercritical airfoil shown in Fig. 2, show extreme sensitivity to mean-flow Mach number and angle of attack. Hence, its true aerodynamic and aeroelastic performance could well be masked in a poor flow quality wind tunnel since unrealistically large shock wave motions could occur due not to airfoil design but driven by the freestream turbulence. Clearly there are flow quality influences in addition to the recognition that supercritical airfoils are extremely sensitive to geometric tolerances in design and fabrication as well as to the ability to account for wind tunnel wall interference effects. Flow quality issues are also important in the study of buffet onset which may occur at lower angles of attack when driven by freestream turbulence, and in the testing of high lift configurations, especially as it affects flow separation and vortex flow breakdown, which could well lead to misinterpretations of the efficiency of flow control devices such as ailerons and flaps. Wind tunnel generated turbulence and noise also affects C Lmax , transonic drag rise, skin friction drag, shock shape and shock location. Hence, wind tunnel data may not be representative of free-flight conditions. It is important, therefore, that we document the dynamic flow quality of the tunnels that are used for advanced

aerodynamic testing. In this way, available tunnels can be ranked and judgments made as to the meaningful operating ranges of adequate flow quality in each facility relative to each proposed test program. Similar judgments could be made in other research areas once we have the documented database. Measurements are also required that could be used for the identification and means for suppression of suspected sources of flow disturbances in the test section and around the wind tunnel circuit. Unfortunately, flow quality measurements are time consuming and expensive. They should only be undertaken if there has been a methodical and thorough examination of existing data, which shows that it could have an adverse impact on future test programs. Once it has been established what needs to be measured, the next challenge will be the development of reliable turbulence measurement instrumentation, with improved bandwidth and resolution and data reduction techniques applicable to wide ranges of fluid flows. However, the first order of business should be the education of the aerodynamics and ground test communities on the significance of flow quality measurements. Currently, many researchers feel they should ask for turbulence levels, but few understand their significance. It is important to lay out the significant flow quality issues for different types of testing and highlight the symptoms of poor flow quality. Until researchers understand, in regard to turbulence measurements, what information they need and why, attempts to measure flow quality will not be productive.

2. Flow quality requirements and sources of adverse wind tunnel flow quality Since it is apparent that poor flow quality can exert such significant influences on wind tunnel test results, an understanding of its sources and management is particularly relevant. Wind tunnel flow irregularities can usually be divided into four main categories, spatial nonuniformities, swirl, low-frequency

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unsteadiness and turbulence. Ideally, in an empty wind tunnel test section free from struts and fairings, the flow outside the wall boundary layers would be uniform and smooth, without cross flows or turbulence. Since this ideal is unachievable in reality, the key question becomes one of what flow quality is acceptable at a reasonable tunnel performance level and operating cost. Some of the major sources of adverse freestream flow quality are the drive system that can produce turbulence, pressure disturbances and total temperature fluctuations. Test section sidewalls produce boundary-layer noise, porous walls can generate distinct edge tones, and slotted walls can generate broadband disturbances due to shearing in the slots between the moving air and the surrounding plenum chamber. Separated flow instabilities around the tunnel circuit are a major source of poor flow quality; likely locations are in the first diffuser, first corner, fan nacelle, and contraction. Clearly, disturbances can originate from numerous locations around the entire wind tunnel circuit. In transonic wind tunnels the drive system, disturbances convected downstream from the settling chamber, and diffuser noise convected upstream into the test section are the major contributors to poor flow quality. The model and support systems can also cause significant disturbances. Wind tunnel flow irregularities are normally controlled or enhanced by the designs of the primary components of the wind tunnel circuit. Unfortunately, past policies have usually tolerated poor flow quality in most of the tunnel circuit and have only attempted to make improvements immediately upstream of the test section. In a number of cases, sudden expansions upstream of the settling chamber have been employed to enable large contraction ratios between the settling chamber and test section in attempts to reduce test section turbulence levels. This approach has been used in the RAE 4-ft  3-ft wind tunnel, the NASA Ames 12-ft transonic wind tunnel, and the National Transonic Wind Tunnel at NASA Langley. Unfortunately, these sudden expansions can create large-scale unsteady flows associated with flow separation, which produce mean gradients in the flow upstream of the screens. With mean-flow nonuniformities of only a few percent, regeneration of turbulence can occur through the screens and their efficiency reduced, thus offsetting any potential advantages of increased contraction area ratio. A better policy is to attempt to identify and eradicate poor flow quality at its source around the circuit whenever possible rather than rely on a stepwise improvement at one location. Settling chamber screens and honeycombs and the subsequent contraction cannot be relied upon to solve all test-section flow quality issues. Accordingly then, measurements are needed to determine the contribution of each significant element of wind tunnel circuits, which are to be used for advanced wind tunnel testing. In this way, the sources of poor flow quality can be identified and treatments recommended. 2.1. Review of flow quality requirements It is germane at this point to summarize previous statements of required flow quality in subsonic and transonic wind tunnels, despite some limitations inherent in such statements. Specifically, although the precise values cited cannot always be fully justified in the strictest sense, they do capture current thinking and therefore suggest the minimum required scope of measurement capability and levels of precision. In other words, facility customers will likely expect to see verification that actual flow quality levels do or do not meet these established goals, even if the goals themselves subsequently prove to be under- or overspecified. In the 1970s a comprehensive study of transonic and supersonic wind tunnel calibration procedures and techniques was

published by NASA [5] drawing on work previously conducted by NASA, the Air Force and the US Navy. Guidelines for flow quality were presented, based on results from questionnaires sent to a number of wind tunnel users. In general terms, the state of the art of measurement accuracy was represented as follows: Parameter

Value, transonic tunnel

Mach number (single point) Mach number (spatial variation) Total pressure Total temperature Flow angularity (single point) Flow angularity (spatial variation) Noise (effect of noise and unsteady flow)

70.001 70.0015 to 70.005 70.025% to 70.1% 71 to 72 1C 70.011 to 70.041 70.251 DCpo0.005

In 1986, a NASA Langley discussion of desirable attributes for a transonic wind tunnel made some mention of desirable flow quality requirements [6]: Parameter

Transonic

Turbulence (velocity turbulence) Total pressure variations

o0.05% 0.05%

In 1994, the following table, relating to a notional subsonic tunnel operating from low pressures up to 5 atm and also a notional transonic tunnel with a similar maximum operating pressure were published [7]. Parameter

Low speed

Volume for flow quality Total temperature distribution (1F) Turbulence

Fully encompasses model Fully encompasses model

Noise, rms

Stream angle deviation (deg) Dynamic pressure distribution (%) Total pressure distribution (%) Mach number distribution

Transonic

71.5

71.0

o0.08%, (10–40 kHz)

o0.07% (laminar flow tests) o0.2%, with o0.1% variation (aerodynamic testing) 95.0 dB2 (1.25–40 kHz) (laminar flow testing) 104–120 dB (1–30 kHz) (aerodynamic testing) o70.1

53.3 dB1 (1.25–40 kHz) (acoustic testing) 70 dB (1.25–40 kHz) (aerodynamic testing) o70.03 70.1 70.1

70.05 70.001

Most notable recent efforts to determine flow quality standards for low speed and transonic flow were conducted by the National Wind Tunnel Complex (NWTC) project team consisting of members from the US government, industry and academia. These requirements were adopted as goals for the NWTC flow quality characterization effort. The following table summarizes the parameters defining the flow field and accuracy requirements for both low-speed and transonic testing. Of particular note are the requirements for turbulent flow quality. Clearly, in order to achieve these goals, sources of adverse wind tunnel flow quality must be identified and eradicated to the greatest possible practical and economic degree. 1 2

Mach 0.35, 1 atm. Mach 0.8, 1 atm.

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The NWTC study, undertaken in 1993, produced the following requirements for the subsonic and transonic wind tunnels [8]. Both tunnels were pressurized (5 atm) atmospheric temperature facilities. The low speed tunnel featured a test section approximately 20  24 ft2 and a maximum Mach number of 0.6; the transonic tunnel featured a test section approximately 11 15.5 ft2 with a maximum Mach number of 1.5. Parameter

Low speed (closed jet)

Volume for flow Fully encompasses quality model 71.0 Total temperature distribution (1F) Turbulence 0.04 longitudinal

Noise, rms (dB) Stream angle deviation Stream angle gradient Mach number distribution

Tunnel stability

Acoustic levels

Low speed (open jet)

Transonic

Fully encompasses Fully encompasses model model 71.0 71.0

0.08 vertical 0.08 lateral 59.4 o70.11

0.2 longitudinal 0.12 vertical 0.12 lateral 59.4 TBD

0.08 vertical 0.08 lateral 95.0 o70.11

0.011/ft, any line

TBD

0.011/ft, any line

70.001 centerline

TBD

70.001 (Mo1); 70.01 (M41) centerline 70.001 in cross-section at model rotation center 70.0005/ft along centerline 71 psf over 10 s

70.001 in cross-section at model rotation center 70.0005/ft along centerline 71 psf over 10 s 71 psf over 10 s 70.5 1F over 10 s 70.5 1F over 10 s 70.0005 Mach over 70.0005 10 s Mach over 10 s None given Specified over 100–20 kHz

0.04 longitudinal

70.5 1F over 10 s 70.0005 Mach over 10 s Specified over 100–20 kHz

We must decide whether previously defined flow quality goals (such as those established for the proposed NWTC) are necessary and if they can be achieved in a cost-effective manner. We know for example that LFC testing at airfoil chord Reynolds numbers of 100 million requires freesteam turbulence levels as low as 0.02%. Also, the onset of light buffet can be detected only if the background pressure fluctuations (prms/q) are less than 0.5%. These are two examples of base-line cases, but are these levels necessary for routine aerodynamic testing? We also know that turbulent boundary layers can be affected by freestream turbulence and that separated and vortex flows, which are inherently unstable, can be strongly influenced by wind tunnel flow quality in complex ways.

2.2. Status of flow quality measurement Since wind tunnel flow quality can adversely affect test results, accurate and consistent flow quality measurements are required, along with an understanding of the sources, characteristics, and management of flow turbulence. At the present time, there is a profound lack of standardization of approach, techniques and procedures for the assessment of flow quality in wind tunnels. Flow quality assessment in smaller facilities tends to be undertaken sporadically at best, and is carried out in larger facilities

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only rarely. There are major issues that must be addressed and overcome in order to establish a meaningful flow quality research program that will be of benefit to the ground test community. These issues include the relevance and extent of existing flow quality databases, and the achievement of a scientific consensus on the art and science of turbulence measurement over a wide range of fluid flows. Progress in each of these areas is crucial to the development of definitive ground test databases that can be exploited to help improve full-scale aerodynamic performance. Unfortunately, past wind tunnel flow quality measurements have been made with inconsistent instrumentation and analysis and over widely differing frequency ranges. Thus, an important aspect of our Phase I work was to collate and review these studies in order to provide a more complete picture of the current status of flow quality measurement technology. To illustrate this dilemma, measurements obtained in a number of wind tunnels over the past several years are shown in Table 1. These measurements illustrate the wide variety of probes and bandwidth employed in the measurements. They clearly show that there is an urgent need for precisely defined flow quality diagnostic standards that must include consistent use of properly characterized measurement probes, dynamic data acquisition equipment, and data reduction procedures. This would ensure consistent standards for comparison of measurements obtained in different facilities. The description of wind tunnel flow quality in terms of overall rms fluctuation levels is insufficient. Tunnels with identical overall levels of turbulence can produce different test results due to differences in the spectral distributions that are related to spatial and temporal length scales. Most wind tunnel spectra are dominated by large scale, low-frequency fluctuations, and the influence of these fluctuations is even more pronounced in facilities with open test sections. Clearly, the band-pass of all freestream flow quality measurements must be cited if any meaningful comparisons are to be made between facilities. It is of significance to note that, as shown in Table 1, high pass sensor filter settings have ranged from as low as 0.1 Hz during tests in several NASA facilities, to 10 Hz in the ONERA T2, to as high as 16 Hz in the RAE 5 m tunnel, and 20 Hz in ETW. Bearing in mind the large contribution of the low-frequency turbulence in these facilities, it is clear that meaningful facility classifications, based entirely on quoted turbulence levels, cannot be made. In this example, increased turbulence intensity would have been identified in the ONERA, RAE, and ETW facilities if lower band-pass filters had been used. Unambiguous measurements of the principal mode fluctuations must be made over a consistently defined bandwidth. Despite the qualitative notion that the spectral characteristics of wind tunnel fluctuations affect model performance, attempts to gain a better understanding of the quantitative effects are extremely limited. In order to put some meaning into the interpretation of turbulent flow spectra, we plan to introduce the concept of a model or wind tunnel Strouhal number, defined as fL/U, based on the spectral frequency band, f, the tunnel freestream velocity, U, and the model chord or wind tunnel hydraulic diameter, L. We will be able to consider the plausible ranges of Strouhal number influence on model performance, since we will be able to estimate the critical freestream turbulent Strouhal number ranges as they relate to representative model testing. A preliminary numerical indication of these ranges, based on unit length, is given in Table 2. Based on a model chord of unit length, and choosing critical disturbance frequencies over the appropriate Tollmien–Schlichting instability bands, the critical Strouhal number for transition

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Table 1 Survey of wind tunnel flow quality data Facility description

Measurement method

Freestream conditions

Frequency range (Hz)

Turbulence level (%)

Comments

Langley 8-ft transonic

M ¼ 0.2–0.8

Langley LTPT

Hot wire p0 probe, p0 /p Hot wire

M ¼ 0.05–0.3

0.1–25,000 0.1–5000 0.1–5000

0.1–0.4 0.007–0.35 0.02–0.08

Langley 0.3 m transonic cryogenic

Hot wire

Mo0.4

0.1–5000

0.04–0.2

ONERA F1 pressurized subsonic

Hot wire, microphone,

Mo0.4

?

0.04–0.1 1–4

AIAA 94-2503 AGARD CP 348 AIAA 84-0621 AIAA 94-2503 AGARD CP 348 AIAA 94-2503 AGARD CP 348 @1.1 bar p0 /q ICAS 1980

RAE 5 m DFVLR NWB 3.25 m  2.8 m

Hot wire Hot wire, microphone

Mo0.3 o100 m/s

16–3150 1.6–12,800

DFVLR 3 m  3 m (NWG)

Hot wire, microphone

o100 m/s

1.6–12,800

DNW

Hot wire, microphone

o 100 m/s

1.6–12,800

Ames 12 ft PWT LaRC 4 m  7 m (VSTOL) ONERA T2 Cryogenic

Hot wire, p0 probe, p0 /p

M ¼ 0.26–0.82

0.1–25,000 0.1–5000 0.1–5000 10–10,000

0.15–0.3 0.05–0.2 ? 0.38–0.75 ? 0.03–0.22 ? 0.04–0.2 0.01–0.2 0.35–4 0.1 0.3 0.02–0.15

Lewis 9  15 ft2 low speed Ames 11 11-ft2 TWT

Hot wire, hot film Hor wire Acoustic probe, C prms

M ¼ 0.05–0.2 M ¼ 0.2–0.95

?–10,000 1–16,000 1–10,000

ETW

Hot film Acoustic probe, C prms

M ¼ 0.3–0.85

20–12,000 ?–?

Hot wire Hot film, microphone, Tt probe

M ¼ 0.7–0.85 100–300 K

Table 2 Estimates of critical Strouhal numbers for aerodynamic testing Flow mode

Mach number

Total pressure (atm)

Strouhal number range

Transition Rcrit ¼ 60,000 Transition Rcrit ¼ 500,000 Transition Rcrit ¼ 10 million Turbulent flow Re ¼ 10 million Separation, buffet, flutter Model Vibration Influence on static data

0.2 0.8 0.2 0.8 0.2 0.8 0.2 0.8 0.2 0.8 0.2 0.8 0.2 0.8

1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,

58, 287 180,899 6–23, 33–115 20–72, 103–359 0.45-2.6, 2.8–13.1 1.7–8.1, 8.6–40.3 8.8, 44 27, 135 0.9, 4.4 2.7, 13.5 0.04 0.01 0.004–2 0.001–2

5 5 5 5 5 5 5 5 5 5 5 5 5 5

testing is shown in Table 2. These results clearly show the requirement for low-level fluctuations over a wide frequency range. Atmospheric transition test simulations for typical commercial surfaces in gusty streams requires clean spectra up to 25 kHz at low subsonic Mach numbers. This indicates that many of the spectral peaks that have been measured in large-scale wind tunnels (see for example [9]) are in the critical range of instability for basic laminar flow and low-drag suction airfoil testing. At the other end of the spectrum, Strouhal frequencies which are representative of large-scale flow unsteadiness are also shown in Table 2. This is the range that can produce buffet and flutter, excite model vibration, influence static forces and moments, and data acquisition times. To determine the influence of quasi-steady disturbances, we consider only those frequencies, which correspond to length scales greater than one half the chord, i.e. the

1.5–2.5 0.05–0.5 0.1–0.6 Slots taped 0.15–0.25 0.4–0.6

RAE report 1978 DFVLR report 1986 DFVLR 1986 DFVLR 1986 AGARD CP 348 AIAA 96-2204 AGARD CP 348 Mass flux P0 /q Tt0 /Tt ICIASF 1997 AIAA 95-2390 AIAA 2000-2681

AIAA 2000-2206

limiting Strouhal number is less than two. Turbulence in this frequency range produces fluctuations in dynamic pressure, Mach number, angle of attack and sideslip, which can lead to aerodynamic measurement errors. To put this problem in perspective, let us assume a measured lateral turbulence level of 0.1%, and that half of this turbulence energy is in scales corresponding to Strouhal numbers of less than two, and also that the fluctuations are normally distributed. Under these assumptions, even such a low level of turbulence corresponds to a maximum amplitude for large-scale angle of attack variations of 0.121, i.e. a model attitude bandwidth of about 0.251. This would be unacceptable since it has been shown that, at transonic speeds, angle of attack errors as small as 0.011 can obscure the true test results [1]. Unfortunately, in most large-scale test facilities, a significant amount of energy is contained in these low frequency, large-scale fluctuations. Indeed, many freestream turbulence spectra show that more than half the energy is contained in frequencies below 1 kHz [9]. Although these are preliminary computations, they could shed considerable light on the spectral ranges that could influence specific test programs. They also suggest that measured spectra should be related to a Strouhal number based on a characteristic facility length scale such as the tunnel hydraulic diameter. In this way, facility flow quality could be more effectively assessed, and better judgements made as to the meaningful operational ranges of adequate flow quality in different facilities relative to proposed test programs. Accordingly, more detailed studies and quantitative assessments based on spectral data are required. The requirement for both turbulence length scale and intensity measurement demonstrates the need for consistent flow quality documentation in facilities to be used for advanced aerodynamic testing. In summary, critical assessments must be made of current and planned wind tunnel facilities that are to be used in future advanced wind tunnel testing. We may well have reached the

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stage where the lack of suitable facilities will soon hinder and dictate the rate of progress of ground-based testing. As a first step adequate maintenance of our existing facilities is essential. Detailed and consistent flow quality documentation should be encouraged and continued. Not only will this identify appropriate wind tunnels for experiments that demand a certain flow quality, but will also lead the way to identifying sources of flow disturbances that can be targeted for improvement. This will lead the way to selective changes to improve overall flow quality and to useful classifications of our national facilities.

3. Flow quality measurement There are several major issues, which must be addressed and overcome in order to establish a meaningful flow quality research program, which will be of benefit to the ground test community. These major issues are: awareness and education within the aerodynamic community; a detailed assessment of the relevance and extent of existing flow quality databases; achievement of a scientific consensus on the art and science of turbulence measurement over a wide range of fluid flows. Progress in each of these areas is crucial to the development of definitive ground test databases, which can be exploited to help improve full-scale aerodynamic performance. To some extent, the approach to flow quality has been like that to the weather: Everybody talks about the weather, but nobody does anything about it. Editorial (attributed to Mark Twain), Hartford Courant, August 24, 1897). At the present time, there is a profound lack of standardization of approach, techniques and procedures for the assessment of flow quality in wind tunnels. Further, a proper appreciation of the importance of flow quality in the interpretation of wind tunnel data is seldom present. Finally, flow quality assessment in smaller facilities tends to be undertaken sporadically at best, and is carried out in larger facilities only rarely. Wind tunnel turbulence and noise must be measured with the highest accuracy to allow the aerodynamicist to distinguish between aerodynamic, aeroelastic, and Reynolds number effects, which may be encountered by aerospace vehicles. Current attempts to improve the quality and reliability of ground test data obtained in existing large-scale wind tunnels has greatly increased the need for reliable assessments of the potential effects of test section flow quality on the test results. Detailed and consistent measurements of wind tunnel flow quality are required in order to accurately assess the adverse effects in specific test cases. Measurements are required that could be used for the identification and means for suppression of suspected sources of flow disturbances in the test section and around the wind tunnel circuit. Wind tunnel flow quality is generally characterized by the turbulent velocity (vorticity), pressure (noise), or temperature (entropy) fluctuations. The starting point for all analysis is the fluctuating energy equation, which relates the total temperature fluctuations to the velocity, pressure and density fluctuations. In conventional wind tunnels the total temperature fluctuations are generally small so that the velocity fluctuations can be determined from hot wire and fluctuating pressure measurements, assuming negligible correlation between the hot wire and pressure probe fluctuations. If the temperature fluctuations are significant, as in cryogenic flows, they can be determined with a suitably compensated hot-wire sensor operated near the recovery temperature. If pressure fluctuations are dominant, then the

321

velocity fluctuations can be determined from the wave equation, which relates induced vorticity by pressure waves, the constant of proportionality being the wave impedance of the medium. 3.1. Hot-wire turbulence measurements Hot-wire anemometry is still the preferred technique for the investigation of wind tunnel turbulence. The hot-wire sensors for turbulence studies generally consist of platinum plated tungsten wires with diameters of 5 mm and lengths of about 2 mm (i.e. length to diameter ratios of 400). In the case of transonic, pressure tunnels, larger diameter 9-mm wires are often used to increase strength at the expense of frequency response. Hot-wire fluctuation measurements require detailed knowledge of the steady-state heat loss laws. In isothermal, incompressible flows, a hot wire responds only to velocity changes and the output can be correlated quite well over a wide range of Reynolds numbers. However, in high-speed flows, wire response is more complex since the wire recovery factor is a function of both Mach number and Reynolds number. In these flows, the derivation of the general fluctuation sensitivities of a hot wire involves the perturbation of the steady-state heat transfer law, and expressing the results in measurable electrical and fluid flow properties. Unfortunately, a single probe cannot be used to distinguish between turbulence and noise, and a hot wire operated at constant overheat cannot be used to separate vorticity and entropy fluctuations. In conventional tunnels, combined hot wire and acoustic probes must be used to separate vorticity and pressure fluctuations from the measured mass flux and total or static pressure fluctuations. Suitably compensated constant current hot-wire measurements are required for total temperature fluctuation measurements. For wire Reynolds numbers greater than 40, and Mach numbers above 1.2, the terms involving derivatives with respect to Mach number which appear in the hotwire sensitivity equations are negligible, and the sensitivities to density and velocity fluctuations are equal. However, there is conflicting experimental evidence as to whether or not the velocity and density sensitivities are equal at transonic speeds. Following Kovasnay [10], the basic equation for hot wire response in a turbulent flow may be written as  0  0  0 e0 r u T þ su ¼ sr  sT 0 0 r E U T0 where E and e0 are the mean and fluctuating hot-wire voltages, and r0 , u0 and T0 0 are the fluctuating components of the mean density, velocity and total temperature, and sr, su, and sT 0 are the hot-wire sensitivities to density, velocity and total temperature fluctuations. Morkovin [11] has given a convenient form for the hot-wire density, velocity and total temperature sensitivity coefficients. Most of the terms in these hot-wire sensitivity equations can be determined from the known physical properties of the wire material and from the measured wire voltage response at each point in the flow. However, terms that involve the determination of the variation of wire recovery factor and Nusselt number with Mach number and Reynolds number require measurements at more than one tunnel condition, or reliance on published data. 3.2. The hot wire in supersonic flow It is generally accepted that, at supersonic Mach numbers (M41.2) and wire Reynolds numbers greater than 40, the Nusselt number and recovery factor derivatives with respect to Mach number, terms that largely account for the differences between the density and velocity sensitivities, are negligible. These experimental observations allow us to assume that sr ¼ su.

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Now taking the square of the hot-wire response equation, time averaging and dividing by DeT 0 we obtain:

Now, since qðruÞ qr qu þ ¼ r rU U

e0 2

We may rewrite the basic equation for hot-wire response as

!,

E2

e0 ðruÞ0 T0 ¼ sru  sT 0 0 E rU T0

s2T 0

¼

0 1 02 @T 0 A T 20

þ 2r

ðruÞ0 T 00 ðrUÞT 0

þ r2

ðruÞ0

2

!

ðrUÞ2

LTPT Hot Wire

2.7

M = 0.05

2.5

M = 0.1 M = 0.2

2.3

M = 0.3 All Mach Numbers

2.1

Linear Fit 1.9 y = 0.1886x + 2.1612 R 2 = 0.9959

1.7 1.5 -1.5

-1

-0.5

0

0.5 Ln (Re)

1

1.5

2

2.5

Fig. 3. Langley LTPT hot-wire calibration.

M = 0.05

LPTP Hot Wire Density Sensitivity

2.7

M = 0.1 M = 0.2 M = 0.3

2.5

Linear (M = 0.05) Linear (M = 0.1)

2.3

Linear (M = 0.2)

Ln (E)

Linear (M = 0.3) 2.1 y = 0.1751x + 1.5071 R2 = 0.9985

1.9

y = 0.1787x + 1.6164 R2 = 0.9976 y = 0.221x + 1.6156 R2 = 0.9988

1.7

1.5 0

1

2

,

where r ¼ sru =sT 0 . Since the wire sensitivity ratio is a function of overheat, the hot-wire response equation can be solved to obtain the values of the mass flux and total temperature fluctuations and the mass flux–total temperature correlation. In principle, this could be achieved by operating a single wire at three overheats and solving three equations for three unknowns. In practice, experimental errors lead to unacceptable errors in the calculated fluctuations and their correlation. Kovasnay [12] recommended a graphical technique, often referred to as a mode diagram, in which multiple overheat measurements are taken, and curve fits are used, to obtain more accurate values.

It is possible to calibrate a wire directly in the flow. The mass flux sensitivity can be evaluated from the wind tunnel calibration of a wire on the tunnel centerline by varying the tunnel total pressure at constant Mach numbers and constant total temperature. Slight variations in total temperature can be accounted for by maintaining a constant overheat ratio during the calibrations. The total temperature sensitivity can be calculated using the in-situ determination of the mass flux sensitivity and the determination of the parameter that relates the wire power input and temperature [11].

Ln (E)

!

3

4

Ln (rho) Fig. 4. Langley LTPT hot-wire density sensitivity.

5

y = 0.2047x + 1.7337 R2 = 0.9955

ARTICLE IN PRESS F.K. Owen, A.K. Owen / Progress in Aerospace Sciences 44 (2008) 315–348

3.3. The hot wire in transonic flow Unfortunately, in the high Reynolds number subsonic compressible and transonic flow regimes of current interest, the interpretation of hot-wire fluctuations is more complex. There has been considerable concern over the relationship between the hot-wire density and velocity sensitivities, and questions as to whether or not these hot-wire sensitivities can be assumed equal in transonic flows. Morkovin’s original calculations [11], based on data from classical sources, indicate that Nusselt number and recovery factor are functions of Mach number over a wide Reynolds number range and that the maximum recovery factor/Mach number and Nusselt number/Mach number gradients occur in the transonic range. Both terms have negative values, but since the Nusselt number/Mach number gradient is an order of magnitude higher than the recovery factor/Mach number gradient, we would expect the velocity sensitivity to be less than the density sensitivity at high-temperature loading. These results suggest that the hot-wire density and velocity sensitivities are different at transonic speeds. We can also estimate the importance of the Mach number and Reynolds number derivative terms using the more recent heat transfer and recovery factor correlations of Laufer and McClellen [13] and Behrens [14]. These results confirm that there are significant variations of Nusselt number with Mach number in the subsonic and transonic range particularly at low Reynolds numbers. But, for wire Reynolds numbers in excess of 40, and if the wire resistance overheat ratio is greater than 1.5, the Nusselt number and wire recovery factor are weaker functions of Mach number. Indeed, some atypical hot-wire calibration results have been reported [15] where it was concluded that, under these limited conditions, the hot-wire density and velocity sensitivities were approximately equal. Most recently, these claims have been disputed with data obtained over similar wire Reynolds numbers and overheat ratios [16]. In particular, it has been shown that the sensitivities of a hot wire to velocity and density fluctuations can be quite different in the high subsonic flow regime, confirming the earlier experimental results. In order to accommodate these experimental uncertainties, we have developed an analysis that allows for the fact that in general, the hot-wire density and velocity sensitivities are not equal in transonic flows, and accounts for the special cases when the hotwire density and velocity sensitivities are equal. This approach will be described later.

323

3.4. Recent flow quality measurements Contrary to the weight of the previous experimental evidence, three recent investigations of transonic wind tunnel flow quality [17–19] have assumed that the hot wire acts as a mass flux sensor i.e. sr ¼ su. However, the in-situ hot-wire calibration data of Amaya and Murthy [17] show considerable scatter that could well have masked any density and velocity sensitivity differences. In [18], no hot-wire calibration data were presented to support this assumption. In both cases, no attempt was made to determine velocity fluctuations from the mass flux measurements even though the static pressure fluctuations were measured. Additionally, in [19], the mode diagram approach was used to analyze the hot-wire data based on mass flux assumptions using a constant temperature hot-wire anemometer system (CTA). These data are clearly open to question as the CTA wire frequency response varies with overheat ratio. In fact, it approaches the frequency response of an uncompensated wire at low overheat ratios [4]. So there is a strong possibility that with this experimental approach, some of the high-frequency information is lost. Although it is experimentally convenient to assume that the hot wire acts as a mass flux sensor, it does not truly represent the physics of hot-wire response in transonic flow. 3.5. Subsonic and transonic hot-wire calibrations In light of all these experimental uncertainties, there is an urgent need to re-examine hot-wire response in low subsonic, high subsonic compressible and transonic flows. Data obtained in two NASA Langley wind tunnels [20,21] have been selected for this review. The low subsonic data were obtained in the Langley low-turbulence pressure tunnel (LTPT) at freestream Mach numbers between 0.05 and 0.3, over a unit Reynolds number range from 0.1 to 10 million/ft. The high subsonic compressible and transonic flow data were obtained in the Langley 8-ft transonic pressure tunnel (TPT) at freestream Mach numbers between 0.2 and 0.8, over a unit Reynolds number range from 0.61 to 6.1 million/ft. For consistency, the measuring probes and dynamic recording instrumentation were identical insofar as possible in each facility. Constant temperature hot-wire anemometry techniques were used with 5-mm diameter Tungsten hot wires with length to diameter ratios in excess of 50.

15 PSF

LTPT Hot Wire Velocity Sensitivity

30 PSF

3

45 PSF 60 PSF 2.5

Linear (60 PSF)

Ln (E)

Linear (45 PSF) Linear (30 PSF) 2

Linear (15 PSF) y = 0.198x + 1.4159 R2 = 0.9895 y = 0.1958x + 1.3846

1.5

R2 = 0.9942 y = 0.1833x + 1.3624 1 3

3.5

4

4.5

5

5.5

6

Ln (V) Fig. 5. Langley LPTP hot-wire velocity sensitivity.

6.5

R2 = 0.9947 y = 0.1687x + 1.2958 R2 = 0.9976

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The probes were maintained at constant overheat resistance ratios of 1.8. In our analysis, we have assumed that the fluctuations of all variables are small, so that the dynamic sensitivities can be considered to be identical to the corresponding static sensitivities obtained by steady-state in-situ calibration in a uniform stream. Accordingly, we can write the hot-wire density and velocity sensitivities as sr ¼

q ln E q ln r

! ;

q ln E

su ¼

q ln U

u;T 0

! r;T 0

Hot-wire calibration data obtained at low Mach numbers in the NASA Langley LTPT are presented in Figs. 3–5. These data were taken from the in-situ calibrations used in [20]. The measure-

ments show that hot-wire Nusselt number, which is proportional to Joule power consumed by the wire (E2), is insensitive to Mach number up to M ¼ 0.3. Indeed the coefficient of determination is greater than 0.99. The data also show that the density and velocity sensitivities are approximately equal, with numerical average values of values of 0.17 and 0.18, respectively. This confirms the tendency for these two sensitivity coefficients to approach the same value as the Mach number decreases below 0.3 according to the requirements of King’s Law. Hot-wire calibrations obtained in the NASA Langley 8-ft transonic wind tunnel are presented in Figs. 6–8. These high subsonic compressible and transonic data are taken from in-situ calibrations used in [21]. The data obtained over a Mach number range from 0.2 to 0.8 are presented in Fig. 6. These data clearly show Nusselt number variations with Mach number with

M = 0.2 M = 0.4

8-Ft. Hot Wire Calibration

2.05

M = 0.6 M = 0.8

2

Linear (M = 0.2)

1.95

Linear (M = 0.4)

Ln (E)

1.9

Linear (M = 0.6) Linear (M = 0.8)

1.85

y = 0.182x + 1.7761 1.8

R2 = 0.9959 y = 0.2002x + 1.7248

1.75

R2 = 0.9984

1.7 1.65 -0.5

y = 0.2027x + 1.6873 0

0.5

1

1.5

2

R2 = 0.9979 y = 0.2195x + 1.6267 R2 = 0.998

Ln (Re) Fig. 6. Langley 8-ft transonic pressure tunnel hot-wire calibration.

M = 0.2

8-Ft. Hot Wire Density Sensitivity

2.1

M = 0.4 M = 0.6

2

M = 0.8 Linear (M = 0.2)

1.9

Ln (E)

Linear (M = 0.4) 1.8

Linear (M = 0.6) Linear (M = 0.8)

1.7

y = 0.1835x + 0.4382 2

1.6

R = 0.9965 y = 0.201x + 0.3923

1.5

R = 0.9978 y = 0.2037x + 0.4206

1.4

R = 0.9982 y = 0.2195x + 0.3292

2

2

6

6.5

7

7.5

8

8.5

Ln (rho) Fig. 7. Langley 8-ft transonic pressure tunnel hot-wire density sensitivity.

2

R = 0.998

ARTICLE IN PRESS F.K. Owen, A.K. Owen / Progress in Aerospace Sciences 44 (2008) 315–348

1000 PSF

8-Ft. Hot Wire Velocity Sensitivity

2.05

1500 PSF 2000 PSF

2

3000 PSF

1.95

Linear (1000 PSF)

1.9 Ln (E)

325

Linear (1500 PSF) Linear (2000 PSF)

1.85

Linear (3000 PSF) 1.8

y = 0.1128x + 1.098

1.75

y = 0.1202x + 1.1381

1.7

y = 0.1128x + 1.238

1.65

y = 0.1355x + 1.1748 5

5.5

6 Ln (V)

6.5

7

Fig. 8. Langley 8-ft transonic pressure tunnel hot-wire velocity sensitivity.

LTPT Wire A

Vertical Velocity Sensitivity

0.25

0.2 M = 0.1 0.15

M = 0.2 M = 0.3

0.1 Inclined Wire Sensitivity 0.05

0 0

2

8

LTPT Wire B

0.25

Vertical Velocity Sensitivity

4 6 Unit Reynolds No. (x106)

0.2 M = 0.1 0.15

M = 0.2 M = 0.3

0.1 Inclined Wire Sensitivity 0.05

0 0

2

4 6 Unit Reynolds No. (x106)

8

Fig. 9. Langley LTPT crossed wire sensitivities.

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LTPT Crossed Wire Sensitivity Ratio 1.2

Sensitivity Ratio

1 0.8 M = 0.1 0.6

M = 0.2 M = 0.3

0.4 0.2 0 0

1

2

3 4 5 6 Unit Reynolds No. (x10^6)

7

8

9

Fig. 10. Langley LTPT crossed wire sensitivity ratio.

coefficients of determination greater than 0.99. These data have been re-plotted in Fig. 7 in order to determine the hot-wire density sensitivities. These results show that, within the limits of experimental uncertainty, there are some small changes in density sensitivity with Mach number. The data show a slight monotonic increase from numerical values of 0.18 at Mach number of 0.2 to a value of 0.22 at Mach number of 0.8. Although there were a limited number of points where the flow densities matched for different freestream velocities, these data are plotted in Fig. 8 to determine the hot-wire velocity sensitivity. These results show that the velocity sensitivity is independent of freestream density and has a numerical value of approximately 0.12. Clearly, the hot-wire velocity sensitivity is somewhat lower than the density sensitivity. In fact, the velocity sensitivities for all wires are consistently lower than the density sensitivities for the range of high subsonic Mach numbers investigated. These results are consistent with the cryogenic data reported in [22] where it was found that density sensitivity could be two to three times greater than the velocity sensitivity. The numerical values of density and velocity sensitivity also agree quantitatively with more recent measurements obtained in similar test conditions in high subsonic flow reported in [16]. These sensitivity differences definitively preclude the assumption that sr ¼ su for general transonic hot-wire turbulence measurements. Clearly, we must assess the consequences of assuming sr ¼ su ¼ sru in subsonic compressible and transonic flows. Particularly in cases such as [17], where the in-situ data show much more scatter, and a fixed mass flux sensitivity of 0.15 was assumed for different hot-wire freestream measurements. We must also use individual wire calibrations. The lateral turbulence components can be measured using crossed wire probes that can be calibrated in situ using the sting angle of attack capability. Examples of calibrations obtained in the LTPT are shown in Fig. 9. It is recommended that crossed wire sensitivity is obtained by changing wire angle at constant overheat ratio in a fixed freestream flow. The sensitivity varies non-linearly with Reynolds number but is independent of Mach number for Mo0.3. Calibrations should be conducted over a wide range of tunnel total pressure. The results shown in Fig. 9 also show that, for nominal 451 wires: sru

q ln E q ln E ¼ ¼ sv ¼  qy q ln ðrUÞN

So that crossed wire probes can be calibrated along side the normal wire probes with no increase of tunnel test time. Once the crossed wires have been calibrated, the lateral turbulence components can be determined from instantaneous differences between the two signals after suitable signal conditioning to account for any small differences in sensitivity such as those shown in Fig. 10. Clearly, higher freestream Mach number crossed wire effects, when sr6¼su, must be addressed. In conclusion, these studies have shown that there is an urgent need to develop a comprehensive flow quality measurement system that can be incorporated into facilities that are to be used in future advanced wind tunnel testing. Detailed and consistent flow quality documentation techniques must be developed that will help identify appropriate wind tunnels for experiments that demand certain levels of flow quality. These developments will help to identifying sources of flow disturbances that can be targeted for improvement and lead the way to selective changes to improve overall flow quality and to useful classifications of major national facilities.

4. Test techniques It is clear from this current review, and from the flow quality requirements specified previously, that unambiguous measurements of the vortical (turbulent) and acoustic disturbances must be made. Tunnel turbulence and noise generation and suppression mechanisms are quite different so it is important to separate their individual contributions. Since most flow quality data have been measured with hot-wire anemometer systems, it is necessary to separate the vorticity fluctuations from the total hot-wire signal by determining the influence of the static pressure and total temperature fluctuations on the hot-wire measurements. In order to achieve this objective, simultaneous hot wire, static pressure, and total temperature fluctuations measurements are required. However, probe selection must be based on specific experimental considerations. 4.1. Hot wire and hot film probes Care must be exercised in the selection of anemometer probes. Hot wires have a limited life in high-speed wind tunnel flows due primarily to high dynamic loads. Consequently, there is a growing

ARTICLE IN PRESS F.K. Owen, A.K. Owen / Progress in Aerospace Sciences 44 (2008) 315–348

trend to use inherently robust hot film or modified hot-wire probes for turbulence measurements in harsh environments. However, conduction losses into the supporting substrate have pronounced effects on the thermal inertia of the uncompensated probe. We have shown that an uncompensated hot wire without end losses can be modeled as a simple R-C circuit with a system roll-off of 6 dB/octave, and a maximum phase lag of 901. However, the frequency response of modified wires and film probes at low frequencies is dominated by conduction losses into the substrate that attenuate the dynamic response and invalidate the simple R-C model. At higher frequencies (typically 4100 Hz), the depth of penetration of the unsteady thermal waves into the substrate is small and the attenuation coefficient is approximately constant. However, fluctuation amplitude attenuation, compared to standard hot-wire probes, of up to 60% have been observed [23]. Although these observations shed light on the dynamic behavior of a variety of probes over a wide frequency range, they fail to predict the low-frequency behavior that can be a complex function of sensor shape and geometry and probe Reynolds number. Conventional hot-wire probes are designed to minimize these thermal feedback effects by the use of large length to diameter ratios that reduce conduction end losses. Consequently, dynamic measurements can be made using sensitivities derived from static calibrations. For modified wires and films, it is necessary to carry out separate dynamic calibrations. One such approach [24] involved the comparison of boundary-layer turbulence measurements obtained with a conventional hot wire, which served as the standard, an epoxy backed wire, a similar wire supported by a ceramic wedge, and two commercially available hot film probes. Each probe was used to measure the streamwise turbulence intensity profile through the boundary layer, using fluctuation sensitivities obtained from its static calibration. These results clearly show that mean-flow calibration of fluctuation sensitivity coefficients for modified hot wires and hot film probes must be corrected for dynamic thermal feedback effects, in some cases by up to 35%. In attempts to resolve these hot wire/hot film experimental uncertainties we have conducted tests to further resolve these differences with new hot film probes in an open return wind tunnel that has been modified to incorporate a turbulence generating screen at the entrance to the test section. The facility has a 6-in test section and operates up to M ¼ 0.4. In these experiments, hot wire and hot film probes were tested in a reproducible turbulent flow environment under high mechanical and thermal loading. The grid mesh is 3 (per inch) with a wire diameter of 0.047 in, and an open-area ratio of 73.6%. The probes can be supported at the centroid of the test section, where the turbulence produced by the grid is predicted to reach an asymptotic condition. Since stagnation-line sensor geometry generally reduces the effect of the substrate on the transfer function relative to other designs, preliminary calibrations with back-to-back fiber film probes and hot wires have been conducted in this grid-generated turbulence. These measurements show that the relative responses vary by less than 3 dB over a wide frequency range (1 Hz to 10 kHz). Thus, despite inherent calibration and frequency response problems, cylindrical hot film probes can still be used effectively for qualitative studies of the characteristics of the flow field fluctuations. Individual hot film spectra and multiple film cross-correlations can also be useful in the determination of the sources of adverse flow quality. 4.2. Constant temperature versus constant current operation Hot-wire sensitivities vary with wire temperature. In supersonic flows (M41.2) at low overheat ratio the mass flux sensitivity

327

tends towards zero and the hot-wire responds primarily to total temperature fluctuations. At high overheat ratios, when the wire is well heated, 300 1C for tungsten wires without oxidation, the two sensitivities are about equal indicating that it is not possible to achieve mass flux sensitivity alone. Thus, in flows where more than one mode fluctuation is significant, a fundamental hot-wire anemometer requirement for meaningful quantitative measurements using the mode diagram technique, is one of highfrequency response over a wide range of overheat ratios. This requirement is needed to separate velocity, density and total temperature fluctuations in compressible, non-isothermal flows. Unfortunately, this requirement exposes a basic flaw in the most widely used tool for current turbulence research, namely, the constant temperature anemometer (CTA). This inherent weakness is illustrated by the following equation for CTA frequency response: MCTA ¼ M wire =ð1 þ 2rRw GÞ where MCTA and Mwire are the time constants of the anemometer system and the uncompensated wire, twr is the wire overheat, Rw is the wire resistance, and G is the anemometer transconductance. It can be seen that the CTA frequency response is directly proportional to the wire overheat ratio, and that at low overheat ratios (twr approaching zero) the anemometer system time constant approaches the uncompensated wire time constant. Since wire time constants usually range from 1 to 5 ms, frequency response from 32 to 160 Hz, low overheat CTA measurements required for mode separation and total temperature fluctuation measurement are clearly open to question. On the other hand, with the use of compensating amplifiers, adequate frequency response can be maintained with constant current anemometer (CCA) systems, even at the lowest overheat ratios. Response restoration is accomplished by matching the 6 db/octave hot-wire amplitude/frequency roll-off with a phase matched 6 db/octave gain amplifier. Amplitude restoration can be achieved to a higher frequency than phase restoration, and the upper frequency limit is governed by the lowest wire time constants encountered in the experiment and by the amplifier signal to noise ratio. These systems have proved adequate for hot-wire mode diagram analysis in supersonic flows [12]. In many transonic wind tunnels, the total temperature fluctuations are negligible relative to the density and velocity fluctuations. In these cases, the hot wire operated at high overheat ratio directly senses the density and velocity fluctuations. If the level of the temperature fluctuations becomes a significant factor, as in the National Transonic Facility during cryogenic operations, the level may be measured using a separate suitably compensated hot-wire sensor operated at constant current near the recovery temperature. 4.3. Measurement of total temperature fluctuations The effects of temperature fluctuations on Reynolds number are generally not significant in conventional subsonic and transonic wind tunnels. However, in cryogenic wind tunnel flows, they can become extremely important. For example, in the National Transonic Facility (NTF), at the cryogenic temperatures required for full-scale Reynolds number simulations, a freestream temperature change of 1 K represents a Reynolds number fluctuation of between 2% and 3%. Thus, freestream temperature fluctuations could have significant effects on dynamic flow quality during cryogenic operation. In Ref. [25], results of temperature fluctuation measurements at ambient and cryogenic conditions were reported. A stagnation temperature probe was designed around a cold 2.5-mm diameter wire. The uncompensated bandwidth was 0–600 Hz, and the overall response was increased

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to 3 kHz by applying a suitable correction function. It was found that total temperature fluctuations increased when the temperature decreased: from 0.02% at ambient temperature to 0.14% at 100 K. Most of the energy was in low-frequency fluctuations attributed to the temperature regulation process. However, we shall see that, even during conventional wind tunnel operation, small total temperature fluctuation levels, less than 10% of the velocity fluctuation levels, can have significant effects on the calculated velocity fluctuation levels. Unfortunately, commercial off the shelf CCA systems are uncompensated, so frequency response is severely limited (o1 kHz). In order to obtain accurate total temperature measurements over a wide frequency range, a custom, low noise CCA compensating amplifier has been designed, built, and calibrated as part of our work. It was designed to compensate for low roll-off frequencies associated with larger diameter wire probes designed for the hostile transonic environment. The amplifier has adjustable wire roll-off frequency settings from 13 to 675 Hz that can account for up to seven-fold changes in wire sensor diameter variations. The amplifier has a flat 6-dB gain from d.c. to the roll-off frequency, followed by a 6-dB/octave rise to 40-dB full gain. This ensures a flat frequency response to a minimum of 5 kHz at the lowest rolloff settings, and over 50 kHz at the highest setting. The amplifier output is a low impedance circuit designed to drive high impedance data recording and signal analysis devices. 4.4. Fluctuating pressure measurement Unfortunately, hot-wire probes alone cannot be used to distinguish between turbulence and noise, and a hot wire operated at constant overheat cannot be used to separate vorticity and entropy fluctuations. In conventional tunnels, combined hot wire and acoustic measurements must be undertaken in order to separate vorticity and pressure fluctuations from the measured hot wire and total or static pressure fluctuations. Fluctuating pressure transducers can be used to measure freestream fluctuating static and dynamic pressure. The piezoelectric sensors are basically quartz transducers in which the quartz element produces a change in response to an abrupt change in applied pressure. They can be statically calibrated by applying a known differential pressure across the device. Both static and total pressure probes are usually referenced to local mean static pressure. The transducer is mounted at the tip of a pitot probe to measure unsteady total pressure fluctuations. Pressure transducers, cavity mounted within ogive-cylinder (acoustic) probes are generally used to measure fluctuating static pressure. Although the frequency range of these transducers alone is high (430 kHz), cavity mounts act as low-pass filters and will modify the probe response. Dynamic calibration over the frequency range of interest must be undertaken. Dynamic calibrations can be obtained in an acoustic chamber where the probe and a reference microphone are placed in front of a loudspeaker. This enables the probe transfer function to be determined over the frequency range of interest. Alternatively, acoustic probes can be dynamically calibrated in shock tubes where the transducer is subjected to a known transient pressure input closely resembling a step function. The pressure input produced in the shock tube can be characterized as a perfect step or a modified step, technically representing all frequencies of the spectrum. Analysis of the pressure probe response generates a useful calibration in the form of a transfer function. Acoustic pressure transducers, cavity mounted within ogivecylinder probes, have been used extensively to measure the fluctuating static pressure. Care must be exercised in locating the static pressure and reference orifices since there are significant

static pressure variations along the probe. Since the flow is brought to rest at the nose, the surface pressure is greater than that of the undisturbed flow. The flow accelerates around the nose; the surface pressure falls rapidly, and then increases again until it reaches the undisturbed static pressure. Although the static pressure is also equal to that of the undisturbed flow at some point on the nose, due to the rapid changes in static pressure in this region, pressure taps are located further aft in locations where the static pressure has re-assumed the undisturbed level. Freestream total pressure fluctuations that are generally associated with the dynamics of the tunnel drive system will also be measured using additional pressure transducers housed in the static pressure probes. The second transducer is located immediately behind a 1201 chamfered total pressure orifice drilled in the probe tip. This design is insensitive to probe angularity up to 7251, and avoids cavity resonance problems.

5. Wind tunnel instrumentation and testing Bearing all these experimental considerations and limitations in mind, the following instrumentation is recommended for wind tunnel flow quality investigations. Constant temperature and constant current hot-wire anemometry and acoustic measurement techniques described earlier should be used to determine vorticity fluctuation and sound pressure levels and spectra. Hot-wire turbulent fluctuations should be measured with 5 mm diameter platinum-coated tungsten wires, in order to avoid any possible wire oxidation effects at high overheat ratios (41.8). Wires with length/diameter ratios greater than 100 will help reduce end losses and increase sensitivity. Individual wire probes should be calibrated prior to, and during each test sequence. The wires should be operated as compensated constant temperature probes with negligible amplitude or phase distortion up to at least 20 kHz. Care should be taken to match the bridge R-C characteristics to the wire time constant, as the high-frequency roll-off is dependent on time constant compensation effects. If the setting is too fast, there is a rise in levels at high frequency. If the setting is too slow, the spectra decay faster than they should. Total temperature fluctuations should be measured with 2.5-mm diameter tungsten wires operated at or just above the wire recovery temperature. For these probes, constant current, low noise 40 dB, compensating amplifiers (6 dB/octave) will ensure constant current wire frequency response of up to at least 5 kHz as described previously. As there is limited access in most large-scale wind tunnels, long instrumentation cable runs will be unavoidable. Identical cables should be laid alongside the primary instrument cables in order that any changes in cable resistance with tunnel operational conditions can be precisely monitored and accounted for in the hot wire overheat settings. Shorting probes should be used to balance out any lead resistance changes that might occur due to changes in tunnel total temperature. For backup, thin film fiber probes should also be used to determine freestream flow fluctuation levels. These probes should be calibrated in pilot facilities to account for low-frequency amplitude and phase variations due to thermal feedback into the substrate as discussed previously. Cross-wire probes should be comprised of two geometrically identical hot-wire sensors inclined at 7451 to the mean flow. Any sensitivity differences should be accounted for by suitable relative amplification. Instantaneous voltage differences should be averaged and used to measure the transverse components of turbulence (v0 and w0 ). The instantaneous voltage summations should be averaged to obtain redundant measurements of the

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fluctuating mass flux. Spectral measurements from these probes will also serve as a check on probe vibration effects as they are at essentially the same point in the flow. Since noise spikes generally occur at different frequencies for different wires, while contributions from unsteady flows show up in both spectra, only vibrations of the probe stem or the probe holders or rake would show up at the same frequency. This will help isolate and identify any frequencies related to flow turbulence, and to the drive system, blade passing frequencies and their harmonics that are contained in the hot-wire spectra. Acoustic pressure transducers, cavity mounted within ogive-cylinder probes, should be used to measure total pressure and static pressure fluctuations. Static and dynamic calibrations have been performed at an excitation voltage of 20 V. These static calibrations were performed over a 74 psid range, and will be repeated before and after each test run. The dynamic calibrations were performed at 130 SPL from 50 to 5000 Hz. This was achieved by using a progressive wave tube driven by two electrodynamic drivers powered by a 100-W amplifier. A reference test section microphone was used to control the amplifier through a servo oscillator to produce a constant 130 dB SPL at all frequencies. Comparisons between the probe output and reference microphone have shown that there was negligible amplitude or phase distortion over the test frequency band. These probes are dynamically calibrated before installation, and statically calibrated in-situ prior to each test sequence. A Pitot static probe, total temperature probe, and a four-hole flow angularity pressure probe should be included in the test rake to aid accurate in-situ hot-wire calibration. An accelerometer should also be mounted on the test rake to help identify any probe or rake motion or vibration. Complete characterization of wind tunnel test environments is an enormous task, due to the very wide range of operational conditions achievable, in terms of speed, pressure, and temperature, as well as the range of test configurations, including full model and half model testing. Consequently, initial testing should be conducted with an empty test section, other than the required probe or rake supports. Test plans should adopt a building block approach where tunnel dynamic pressure and Mach number are incrementally increased to challenge probe integrity and data interpretation procedures in order to extend the boundaries of confidence in transonic turbulence measurement. In order to limit tunnel occupancy time, pre-test instrumentation cables should be installed, and self-contained data acquisition and software systems should be assembled prior to tunnel occupancy. Even in large wind tunnels, minimally intrusive measurements are critical if we are to accurately assess base-line flow quality. For the initial measurements, the probes should be mounted on a small centerline rake. This will help to minimize rake induced flow disturbances and provide minimum turbulence base-line values, since the modified flow around larger rakes and test models can introduce considerable additional turbulence and noise. Also, any test section slots should be taped to provide an additional solid wall base line from which the effects of the slots could be determined. Any strut/sting cavities should also be covered as they can produce significant turbulent and acoustic fluctuations. 5.1. Data acquisition A crucial aspect of hot-wire probe calibration is that the same equipment used in the calibration should be the same equipment used during the test. So, whenever possible, in-situ wire calibrations should be obtained. This means that the same

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anemometers, cables, signal conditioners, filters, and analog-todigital converters will remain the same from calibration to test. The hot-wire calibration data should be acquired in the same manner that is used to collect the actual test data. The sampling rates, anti-alias filter settings, and number of data points should be the same for both calibration and actual test data acquisition. In-situ calibration will alleviate any concerns raised by equipment irregularities from calibration to test. The calibration curves should be constructed using the mean voltages obtained from the voltage–time histories obtained during tunnel operation as described earlier. Any hot-wire probe vibrations that may occur particularly at the higher tunnel dynamic pressures will be identified and removed by spectral comparisons of hot wire and film signals and by analysis of the X wire probe spectra. Spurious signals at multiples of the power line frequency (60 Hz) should be removed by appropriate choice of data sampling frequency. Sound pressure levels should be determined directly from the static pressure probe measurements. Velocity fluctuations should be reduced from simultaneous measurements of the hot-wire voltage fluctuations, the pressure fluctuations determined from the acoustic probes, and the total temperature fluctuations measured with the constant current hot-wire anemometer. Data should also be presented in terms of directly measured hot-wire quantities; i.e. mass flow fluctuations and velocity fluctuations that can be calculated assuming negligible pressure fluctuations. Estimates of the vorticity fluctuations due to sound should be made using a fixed source, plane wave assumption. The hot wire and pressure fluctuation measurements should also be used to estimate dynamic pressure and Mach number fluctuations. Many sources of wind tunnel noise have Strouhal-type dependence on wind speed. For example fan speed, blade passing frequencies and their harmonics, and high-speed diffuser disturbances. Spectra will be measured over a wide frequency range in order to identify sources of poor flow quality. As discussed previously, turbulence frequency spectra should be normalized in terms of an effective tunnel Strouhal number (St ¼ fL/U), where L is a length describing the tunnel test section, p typically, L is taken ffiffiffi as the tunnel hydraulic diameter, or L ¼ 0:1 A where A is the cross-sectional area of the wind tunnel test section. The high pass filters should be set to a cut-on frequency of about 0.2 Hz in order to be able to investigate any large-scale unsteady effects, circuit resonances and drive control instabilities. The instrumentation for conditioning, recording, and processing the signals from the unsteady pressure transducers should consist of an excitation supply and line drivers, variable gain amplifiers, a high-speed data acquisition system, and a spectrum analyzer for spectral analysis of the processed data. The signal processing equipment should be capable of providing fast response, low noise operation over the frequency range from less than 1 Hz to at least 20 kHz or higher. We will also compare pressure/hot-wire spectra to identify fluctuating pressure contribution to total hot-wire signals as described previously. 5.2. Data reduction In order to accommodate the transonic hot-wire calibration uncertainties discussed previously, we have developed an analysis that allows for the fact that, in general, the hot-wire density and velocity sensitivities are not equal in transonic flows, and that accounts for the special cases when the hot-wire density and velocity sensitivities are equal. The starting point for this analysis is the fluctuating energy equation that relates the total temperature fluctuations to the velocity, static pressure, and density fluctuations.

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We begin by writing the energy equation as cp T 0 ¼ cp T þ

1 2 2U

Now T¼

p p gp a2 ¼ ¼ ¼ rR rðcp  cv Þ rðg  1Þ g  1

Since a2 ¼ gp/r and g ¼ cp/cv   1 g p cp T 0 ¼ U 2 þ 2 ðg  1Þ r Differentiating   g r dp  p dr ðg  1Þ r2   dU g p dp p dr þ  2 ¼ U2 U ðg  1Þ rp r   dU g p dp dr þ  ¼ M 2 a2 U ðg  1Þ r p r

cp T 0 ¼ U dU þ

So that    dU 1 dp dr þ  cp dT 0 ¼ a2 M 2 U ðg  1Þ p r multiplying by (g1)/a2 we obtain: ðg  1Þ dU dp dr þ þ cp dT 0 ¼ ðg  1ÞM 2 U p r a2 and since   ðg  1Þ 1 ðg  1Þ 2 M c ¼ 1 þ p T0 2 a2 The fluctuating energy equation may be written as   ðg  1Þ 2 T 00 u0 p0 r0 M 1þ ¼ ðg  1ÞM 2 þ  2 r T0 U p In the general case where sr6¼su in the high Reynolds number compressible subsonic and transonic flow regimes of current interest, we may use the fluctuating energy equation to substitute for r0 =r in the basic hot-wire response equation to obtain:  0  0  0 e0 p u T þ s0u ¼ sr  s0T 0 0 p E U T0

hot-wire voltage fluctuations and the independently measured static pressure and total temperature fluctuations. However, in the transonic case, the velocity fluctuations are not uniquely related to the measured mass flux fluctuations as is the case when the hot wire acts as a mass flow sensor for Mo0.4 and 41.2. In the compressible subsonic and transonic flow regimes, 0.4oMo1.2, the hot-wire senses velocity and density fluctuations separately, not mass flux. Incorrectly assuming a fixed hot-wire mass flux sensitivity can lead to serious errors in the estimation of velocity fluctuations in transonic flows. For example, let us take the simplest case where we can neglect the total temperature fluctuations so that we may write: " !#, u0 2 e0 2 p0 2 ¼  ðsr Þ2 ðs0u Þ2 p2 U2 E2 where s0 u ¼ su+(g1)M2sr. Clearly, in the general case where sr6¼su, the determination of the velocity variance is extremely sensitive to freestream Mach number and hot-wire sensitivity ratio, and to the magnitude of the density sensitivity since it serves to amplify the influence of the static pressure fluctuations. If the density and velocity sensitivities are not defined, substantial errors in the calculation of velocity fluctuation levels can occur at transonic speeds. In the special transonic test cases where the hot wire appears to act as a mass flux sensor, i.e. sr ¼ su ¼ sru, which is also valid for M41.2, we can reduce the hot-wire data in terms of mass flux fluctuations. If we add and subtract u0 =U from the RHS of the fluctuating energy equation, and assume g ¼ 1.4, we obtain  0  0  0 e0 u p T  s0T 0 0 ¼ s0ru þ sru p E U T0 where s0 u ¼ sru(1+(g1)M2) and s0T 0 ¼ sT 0 þ sru ð1 þ 0:5ðg  1ÞM 2 Þ. So that, neglecting cross-correlation terms as before, the mean square hot-wire equation, may be written as 0 1 ! ! 02 02 02 e0 2 2 p 0 2 u 0 2 @T 0 A þ ðsru Þ þ ðsT 0 Þ ¼ ðsru Þ 2 2 2 p E U T 20 In these special cases, where the hot wire directly senses the mass flux fluctuations, the pressure probe measures the static

where s0 u ¼ su+(g1)M2sr and s0T 0 ¼ sT 0 þ ð1 þ 0:5ðg  1ÞÞsr . So that the mean square hot-wire equation may be written as 0 1 ! ! 2 e0 2 p0 2 u0 2 T0 ¼ ðsr Þ2 þ ðs0u Þ2 þ ðs0T 0 Þ2 @ 0 A p2 E2 U2 T 20 ! !  0 0 u0 T 00 r0 T 00 0 up 0 0 0  2su sT 0 þ 2sr su  2sr sT 0 Up UT 0 rT 0 In transonic wind tunnels the velocity, pressure and total temperature fluctuations are usually uncorrelated since they are generated by unrelated mechanisms. In our previous work, we have found that the velocity fluctuations generally result from large-scale flow unsteadiness, originating at different points around the wind tunnel circuit, that is modified by screens, honeycomb, cooler coils, and contractions. On the other hand, the pressure fluctuations are primarily generated by the drive system, and by the test section boundary layer and at the strut and in the diffuser. Also, in many transonic wind tunnels, and for noncryogenic NTF operation, it can be assumed that the total temperature fluctuations are relatively small. Even under cryogenic test conditions, the primary source of ‘‘frozen’’ temperature fluctuations is the incomplete mixing of streams of different temperature. Thus we may neglect the last three terms, and the velocity fluctuations can be determined from the measured

Fig. 11. Comparison of turbulence levels measured in the test section of the LaRC/ 4  7 m and LaRC/LTPT.

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pressure fluctuations, and the total temperature fluctuations are measured with a frequency compensated low overheat constant current anemometer. Order of magnitude assessment of the key terms that appear in the fluctuating energy equation is an important step in the data analysis. For test cases where the total temperature fluctuations are negligible, we may write: u0 2 U2

¼

" e0 2 E2

 ðsru Þ

2

p0 2

!#, ðs0ru Þ2

p2

where s0 ru ¼ sru(1+(g1)M2). So in this special case, the velocity fluctuations can once again be determined directly from the hot wire and static pressure probe measurements. In the general case, where sr6¼su, we may also use the unsteady energy equation to determine density fluctuations. Following the above procedures we may write:  0  0  0 e0 r su p T0 0   s ¼ s0r T0 r E T0 ðg  1ÞM2 p where s0r ¼ sr  su =ðg  1ÞM2 and s0T 0 ¼ sT 0  ð1 þ 0:5ðg  1ÞM 2 = ðg  1ÞM 2 Þsu . So that, neglecting total temperature fluctuations we may write: r0 2

2

02

e ¼4  r2 E2

su ðg  1ÞM 2

!2

!3, p0 2 5 ðs0r Þ2 p2

where s0r ¼ sr þ su =ðg  1ÞM 2 .

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In the special case where sr ¼ su ¼ sru, we may also write 2 !2 !3, sru r0 2 4e0 2 p0 2 5 ¼  ðs0ru Þ2 ðg  1ÞM2 r2 p2 E2 where s0ru ¼ sru ð1 þ ð1=ðg  1ÞM 2 Þ. Clearly, all flow situations must be judged on a case-by-case basis. If no simple assumptions are valid, then all measured quantities must be included and error bounds placed on the inferred fluctuation values. For example, based on the present hot wire in-situ calibrations, a dimensionless static pressure fluctuation level equal to the dimensionless velocity fluctuation level leads to a 30% error in the calculated rms velocity fluctuation. Assuming that the total temperature sensitivity is approximately equal to the density sensitivity at high overheat ratios, a dimensionless total temperature fluctuation of just 10% of the dimensionless velocity fluctuations gives rise to a 30% rms velocity fluctuation error. These are important considerations that must be addressed in hot-wire calibration and flow quality studies. Further insight as to the nature of the fluctuating variables can be obtained from the spectra and cross-correlations of the three measured quantities as described earlier. In many cases ([9] for example) it has been found that in good flow quality transonic wind tunnels, the primary disturbances are those due to the acoustic field, and pressure fluctuations are dominant. Oscillations in total pressure can generate waves that move through the test section causing changes in static and dynamic pressure. If Dp=p51, then changes in freestream velocity and density can be determined by the simple wave equation applied in a frame of reference moving with the undisturbed field. The wave equation relates induced vorticity by pressure waves, the constant of proportionality being the wave impedance of the

Fig. 12. Turbulence measurements around the Langley-VSTOL.

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medium, i.e. ra. Therefore Du Dp Dr Du Du ¼ and ¼ ¼ M gMp a r U U

pressure sensor arrays. Standing waves are indicated by zero phase differences. Simple two sensor configurations have been used to identify the sources of pressure fluctuations in several wind tunnels, and are described in [26].

Hence, fluctuations in dynamic pressure can be determined as Dq Dr Du Du ð2 þ MÞ Dp ¼ þ2 ¼ ð2 þ MÞ ¼ gM q r p U U Furthermore, variations in Mach number due to total pressure fluctuations can be evaluated from: DM Du Da ¼  a M U pffiffiffiffiffiffiffiffiffiffi Since a ¼ gp=r, it is found that     Da 1 Dp Dr 1 Dp 1 Dp Dp ¼  ¼  ¼ 0:143 a 2 p 2 p g p r p Hence,   1 Dp Du  0:143 ¼ ð1  0:143gMÞ gM p U

DM ¼ M

Phase velocity measurements have been used to validate the dominance of the pressure fields of turbulent test section side wall boundary layers or shear layers, and flow separations that often occur at the model support struts, and in the high-speed diffusers. The phase velocity and direction is determined from time averaged cross-correlation spectra using spatially separated

Fig. 14. Freestream turbulence fluctuation levels in the Ames 2  2 ft2 transonic wind tunnel.

Fig. 13. Comparison between velocity fluctuations in test section of Ames 12-ft and Langley 8-ft tunnels.

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Fig. 15. Vorticity fluctuation levels at 12/9 blade angle setting.

6. Review of flow quality measurements Over the years, considerable efforts have been made to document the flow quality in several NASA wind tunnels. These

efforts consisted of wire hot turbulence and pressure fluctuation measurements carried out as described earlier in this paper. For consistency, the measurement probes and dynamic recording instrumentation was identical in each facility. Some of this work

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Fig. 18. Free-stream dynamic pressure variations measured in Ames 2  2 ft2 transonic wind tunnel.

Fig. 16. Cross-correlation of pressure fluctuations measured at test-section wall of Langley 8-ft tunnel.

Fig. 17. A comparison of rms pressure fluctuations. Fig. 19. Comparison between pressure fluctuations in Langley 8-ft tunnel with test section choked and slots closed.

that was conducted in the test facilities described in Appendix A will be summarized here. At low subsonic speeds, pressure fluctuations are generally small and the major source of freestream disturbances are the vorticity fluctuations that are convected from the settling chamber, through the contraction, into the test section. In these cases, well-designed screens, honeycomb, and contraction can affect sufficiently low turbulence for even the most exacting flow stability and transition testing. Measurements in low-speed facilities confirm that large-scale, low-frequency vorticity fluctuations are the primary source of test section disturbances, and that there can be large differences in freestream turbulence intensity dependent on wind tunnel geometry and design. For example, a comparison between test section turbulence levels in the Langley low-turbulence pressure wind tunnel (PWT) and those measured in the Langley VSTOL wind tunnel is shown in Fig. 11. These results show that the freestream turbulence levels in the VSTOL facility are about an order of magnitude higher than those measured in the LTPT facility. Clearly, the incorporation of superior flow quality management devices, nine screens and a

cooler/honeycomb in the LTPT helps to produce superior flow quality. However, major differences can be attributed to unsteady flow development in the VSTOL facility. Data obtained around the NASA Langley VSTOL tunnel (Fig. 12) show that the dominant turbulence inputs are large-scale velocity fluctuations generated by unsteady separations in the primary diffuser, separations in the second and third diffusers, with subsequent side loading on the fan, and to a lesser extent by turbulence generated by the fan itself. As expected, the principal turbulence intensity and scale reductions occur across the settling chamber and debris catcher screens. In such cases, significant flow quality improvements could be made by flow treatment in the diffuser and downstream of the fan. Free-stream velocity fluctuations obtained in the Langley 8-ft TPT and Ames 12-ft PWT are compared in Fig. 13. These results show a general increase in turbulence level with increases in both Mach number and unit Reynolds number. At low subsonic speeds the turbulence levels, measured with strut slots covered in the Ames tunnel, are low, and remain low even at Mach numbers up to 0.6. In contrast, the turbulence levels in the Langley facility are

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consistently a factor of 2–2.5 times greater than those measured in the Ames facility over the entire Reynolds number range. The primary difference in turbulence levels between the two facilities can be attributed to the lack of turbulence suppression

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devices in the Langley facility, although the cooler does act somewhat as a honeycomb-screen combination so that the measured differences were not as large as expected. This will be discussed later. In the high subsonic, transonic, and low supersonic range, the data obtained in the Ames 2-ft by 2-ft TPT (Fig. 14) show consistent trends of increasing turbulence levels with increasing Reynolds number, i.e., increasing tunnel power levels. However, the rate of increase is considerably greater in supersonic flow. In the subsonic range, turbulence levels also increase with Mach number, but supersonically there is an initial reduction due to choking of the flow downstream of the test section which blocks diffuser generated disturbances from propagating upstream into the test section. However, as the Mach number is further increased, particularly at the higher Reynolds numbers, the turbulence levels once again increase primarily the result of increasing power levels and increased noise radiation from the turbulent tunnel sidewall boundary layers. However, even at moderate subsonic speeds, the acoustic mode dominates, and alternative flow quality improvement

Fig. 20. Spectra from hot-wire measurements in test section of Ames 12-ft tunnel. Strut slots closed.

Fig. 21. Comparison of measured freestream spectra in the Ames 2  2 ft2 transonic wind tunnel test section-using acoustic and hot-wire probes.

Fig. 23. Ratio of pressure and velocity fluctuation levels with strut slots open and closed.

Fig. 22. Test section spectra in the 12-ft PWT with strut slots covered and exposed.

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options must be considered. Flow quality data obtained in the NASA Ames 12-ft PWT illustrate this problem. Sample test results plotted in Fig. 15 clearly show the dominance of the acoustic mode even at relatively low Mach numbers. Obviously, acoustic remediation is required in this case since honeycomb and screen treatment alone would be inadequate above a freestream Mach number of 0.25. Increasing tunnel drive power also causes a significant increase in fluctuating pressure level. Fig. 15 shows that, for given fan blade angle settings, there is a rapid increase in tunnel noise with increased drive power. Measurements obtained in the Langley 8-ft TPT confirm these observations. The data again show the dominance of the acoustic mode even at moderate Mach numbers. Such levels were considered so high as to make it difficult to conduct meaningful low-drag airfoil and basic transition research at high subsonic Mach numbers in both facilities. However, before acoustic treatments can be formulated, the sources and character of the acoustic disturbances must be identified. In a number of cases, the acoustic sources have been traced to unsteady flows over model support struts and in the first diffuser immediately downstream of the test section. At subsonic speeds, these disturbances propagate upstream into the test section. This has been confirmed by cross-correlation measurements of the acoustic fluctuations in the test section and diffuser in several test facilities. Measurements obtained in the Langley 8-ft TPT are shown in Fig. 16 to illustrate the results. It can be clearly seen that, at subsonic freestream Mach numbers, and with the output from the downstream diffuser probe delayed, it was determined that there were coherent acoustic disturbances that propagated upstream into the test section from the diffuser. The upstream propagation velocity, determined from the probe spatial separation and time delay for optimum correlation, was approximately equal to the speed of sound minus the free-stream velocity. When sonic flow existed in the test section upstream of the diffuser, all correlation between the probes disappeared and the test section pressure fluctuations were markedly reduced. A comparison of the pressure fluctuations measured in the Ames 12-ft PWT test section and diffuser confirm these observations. Fig. 17 shows that the levels at both locations increase with increasing Mach number up to M ¼ 0.75. At that point, the test section level drops dramatically even though the level in the

Fig. 24. Seal mismatch simulation.

diffuser continues to rise. This drop in test section level is associated with the disappearance of space–time correlation between the two probes. Choked flow prevents diffuser disturbances from propagating upstream into the test section. Noise measurements obtained in the Ames 2-ft by 2-ft TPT clearly show the same choking effect (Fig. 18). In fact most high-speed test facilities have a transonic noise peak. All these measurements suggest that diffuser flow quality improvements, that could be achieved by the installation of vortex generators or some other form of flow separation control device, could significantly improve test section flow quality at moderate subsonic speeds. At high subsonic and transonic speeds, flow quality improvements could be achieved by the installation of carefully designed sonic throats installed between the test and diffuser.

Fig. 25. Disturbances introduced by Boeing rake.

Fig. 26. Measured hot-wire rms voltage variations across the test section of the Ames 2  2 ft2 transonic wind tunnel with different wire sensitivities.

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Fig. 27. Comparison between setting-chamber turbulence levels in Ames 12-ft and Langley 8-ft tunnels.

This latter approach for transonic flow has been confirmed in the Langley 8-ft TPT. Fig. 19 shows a comparison of the measured free-stream pressure fluctuations for a range of Mach numbers with and without choke plates installed between the test section and diffuser. Also shown for comparison are the measured settling chamber pressure fluctuations ahead of the contraction. It can be seen that both choke configurations block the diffuser noise and that the remaining disturbances are relatively low-level pressure fluctuations propagating from the settling chamber and turbulent test section sidewall noise. Further flow quality improvements can then come from installation or alterations to screens, honeycomb, and acoustic baffles ahead of the contraction and removal of the turbulent boundary layer on the test section walls. As we have discussed previously, not only do fluctuation amplitudes affect wind tunnel model performance, but also spectral characteristics are also important. Measurements in low speed facilities confirm that large-scale, low-frequency vorticity fluctuations are the primary test section disturbances. Estimates of the integral length scales around the Langley 4-m by 7-m wind tunnel circuit for a tunnel dynamic pressure of 30 psf have been made using area ratios at each station to estimate local mean velocity. This simple calculation shows that the axial length scales upstream of the settling chamber screens are about 6 feet, less than 2 feet at Station 19, and less than 3 feet in the test section. In the diffuser and at Station 10, the scales increase to almost 12 feet, due to large-scale flow separations. They are 4 feet behind the second corner catcher screen and almost 6 feet after the fan nacelle. These estimates show that the dominant turbulence inputs are large-scale fluctuations generated at the diffuser and to a lesser extent across the fan. As expected, principal scale reductions occur across the settling chamber screens and to a lesser extent across the catcher screen. Representative variations of the free-stream spectra from hotwire measurements obtained in the Ames 12-ft PWT test section over a wide Mach number range are shown in Fig. 20. Also shown

Fig. 28. Comparison of screen effectiveness in several test facilities.

are the calculated fundamental drive fan blade frequency and the integrated fluctuation levels. These results show a significant increase in the relative energy at high frequencies as the Mach number increases. There are also several discrete frequencies present in the spectra. These probably come from the fan and from disturbances generated at the strut and in the diffuser that propagates upstream into the test section. However, even at high free-stream Mach numbers, most of the energy is confined to low frequency, large-scale velocity and pressure fluctuations. At high Mach numbers, spectra obtained in the Ames 2-ft by 2-ft TPT show that there is an increased high frequency (small-scale)

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contribution with increasing unit Reynolds number. The hot-wire spectra also show significant energy peaks, which become more pronounced with increasing tunnel power level. It is apparent, by comparisons of the hot-wire data with freestream static pressure probe fluctuation data, that these peaks are acoustic tones as shown in Fig. 21. An inspection of the settling chamber spectra shows that these tones propagate around the entire wind tunnel circuit. They are present at all Mach numbers, although their exact source could not be determined. Clearly, spectral characteristics are important and can provide evidence of the sources of the test section disturbances. In general, hot wire and pressure spectra measurements show that the dominant energy is associated with large-scale, low frequency fluctuations although the high-frequency, small-scale contribu-

tion increases with increasing Mach number and Reynolds number. In many instances, the presence of acoustic tones, blade passing frequencies, and disturbances associated with other sources are also evident. Clearly, spectra measurements can provide significant insight into the nature of the sources and magnitude of the test section disturbances. Other sources of adverse wind tunnel flow quality have also been measured [27]. For example, measurements have been made to determine the effects of exposed strut slots on test section flow quality in the Ames 12-ft PWT. The data shown in Fig. 22 show that with the strut slots covered, there is evidence of disturbances at the fan blade passing frequencies, although the spectrum is broadband with 90% of the energy contained in frequencies below 600 Hz. However, with the strut slots exposed, significant pressure

Fig. 29. Vertical trolley scan upstream of screens, M ¼ 0.2, pres ¼ 30 in.

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and velocity fluctuations are generated by strut slot edge tone disturbances and by the unsteady flow interaction of the shear layer and the slots. At low Mach number they occur at clearly defined resonant frequencies, which scale with the free-stream velocity. At higher Mach numbers, the interactions become more complex with the appearance of higher and lower frequency modes. These slot-induced fluctuations greatly increase the freestream turbulence levels as shown in Fig. 23. Test section trip ring tests have also been undertaken to simulate the effects of isolation valve/test section discontinuities in facilities with multiple test sections. The results for small trip ring heights located at the entrance to the Ames 12-ft PWT test section are shown in Fig. 24. Clearly, the potential effects of seal mismatch could adversely affect test section flow quality. Further examinations of the spectra suggest that the increased fluctuation levels are broad-

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band, but that there are apparent acoustic tones imbedded in the spectra. The modified free-stream flow around a conventional flow survey rake can also account for significant increases in test section turbulence, especially at low Mach numbers, as shown in Fig. 25. Obstructions around the wind tunnel circuit can also be a source of adverse flow quality in the test section. For example, hot-wire turbulence measurements across the test section of the Ames 2-ft by 2-ft TPT shown in Fig. 26, show obvious increases as the sidewall boundary layer is approached. However, there are significant increases off the centerline, which can be traced to turbulent wakes generated by the tunnel survey tube holder located in the settling chamber. Clearly, these spanwise turbulent energy variations could have significant effects on full span airfoil test results. All these test results clearly show the need to remove all obstructions around the wind tunnel circuit, to cover all

Fig. 30. Horizontal trolley scan upstream of screens, M ¼ 0.2, pres ¼ 30 in.

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Fig. 31. Vertical trolley scan downstream of screens, M ¼ 0.2, pres ¼ 30 in.

possible slots, holes and surface discontinuities, and to continuously monitor flow quality for disturbances introduced during specific model testing. Unfortunately, the management of turbulence in large-scale facilities is a difficult proposition. Skewed flow, spatial variations in flow angularity, and turbulence length scale variations make treatment uncertain and lead to large differences between smallscale laboratory simulations and the in-situ, full-scale performance of turbulence suppression devices such as screens, honeycomb and contractions. Fig. 27 shows a summary of the turbulence levels measured with hot wires at several locations in the settling chambers of the Langley 8-ft TPT and the Ames 12-ft PWT wind tunnels for a range of tunnel dynamic pressures.

Initially, in the Langley tunnel, the turbulence levels are high and the levels are not substantially changed across the cooler. However, spectral measurements obtained across the cooler show that there is a substantial reduction in turbulence length scale across the cooler. These data show that the cooler acts as a honeycomb/screen combination in that it generates small-scale turbulence. The faster natural decay of these small-scale structures is apparent in the subsequent turbulence decay downstream of the turning vanes and in the settling chamber. But it is clear that additional turbulence control devices could further improve flow quality. Such modifications have been made with the installation of honeycomb and screens. Initial measurements have been made and are discussed subsequently. In the Ames tunnel,

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Fig. 32. Horizontal trolley scan downstream of screens, M ¼ 0.2, pres ¼ 30 in.

the settling chamber screens reduce the incoming turbulence levels by a factor of about 6 over the dynamic range shown. These results clearly show the importance of screens for turbulence suppression prior to the contraction. Screen efficiency calculations have been made using measurements obtained across the settling chamber screens in several test facilities. These results are summarized in Fig. 28. Clearly, full-scale screen performance in most cases is far from satisfactory. However, it must be borne in mind that all theoretical predictions assume isotropic turbulence upstream of the screens, although this is not generally the case in large-scale test facilities. There are several possible causes for poor screen efficiency that include mean-flow non-uniformity ahead of the screens, high

screen solidity, and the effect of acoustic disturbances on hot-wire data interpretation. These effects have been documented in the Ames test facility. Examples of a vertical scan upstream of the screens are shown in Fig. 29. These data show that there is a central core of relatively constant turbulence level with a substantial outer annulus of highly turbulent, large-scale unsteady flow. This annulus is the remnant of the separated flow that occurs at the sudden expansion into the settling chamber. Clearly, the area of uniform flow ahead of the screens is only half of the total cross-sectional area of the settling chamber. This implies that the actual contraction ratio, which the flow experiences, is substantially lower than the physical tunnel dimensions. The corresponding results of a horizontal scan

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Fig. 33. (a) Turbulence reduction across the screens, vertical traverse, M ¼ 0.2, pres ¼ 30 in. (b) Reduction across the screens, horizontal traverse, M ¼ 0.2, pres ¼ 30 in.

upstream of the screens are shown in Fig. 30. Once again an annular region of high intensity turbulence is evident, along with a central spatial gradient, which is associated with the measured spatial mean velocity gradient. However, in this case, the outer unsteady annulus is skewed by centrifugal effects. Corresponding measurements obtained downstream of the screens are shown in Figs. 31 and 32. These results clearly demonstrate the variation of screen effectiveness across the test section. The test data presented in Fig. 33 show that there are significant spatial variations of screen effectiveness due to skewed flow, spatial changes in flow angularity, and turbulence length scale variations upstream of the screens. The high solidity screens in the Ames facility were deliberately chosen in an unsuccessful attempt to remove the effects of the flow separations in the settling chamber upstream of the screens. Experience with turbulence suppression

devices and analysis suggests that these screens have a solidity that is too high. Decreasing the solidity by cleaning the screens did increase the porosity, but their performance was still poor. More detailed measurements, shown in Fig. 34, show evidence of turbulent wakes from the screen seams. However, since the turbulence length scales downstream of the screens are small, these wakes dissipate quickly and were not observed in the test section. However, past reliance on hot-wire measurements alone may well have underestimated screen efficiency. A more detailed study of hot wire and pressure fluctuation settling chamber spectra shows that acoustic disturbances can influence measured screen performance. Comparisons of hot wire and pressure spectra across the 12-ft PWT screens show that vorticity fluctuations dominate the upstream flow and that sound dominates the downstream flow fluctuations. These data, shown in Figs. 35 and 36, show that, as expected, the level and spectra of the pressure fluctuations are unaffected by passage through the screens. On the other hand, the hot-wire spectra clearly show that, although the acoustic fluctuations are dominated by the vorticity fluctuations upstream, vorticity reductions through the screens increase the relative acoustic contribution to the total hot-wire signal. Integration of the hot-wire spectra downstream of the screens, where the contribution of the acoustic mode can be clearly identified, reveals that the acoustic contribution to the total hot-wire signal can be up to 60% at high subsonic test section Mach numbers. Evidently, past measurements, based solely on hot-wire techniques, have underestimated screen performance, particularly at high Mach numbers where there is increased acoustic contribution to the total hot-wire signal. In Fig. 37, the acoustic contribution to the total hot-wire signal has been removed and the data show a significant increase in screen effectiveness, the axial reduction being close to that predicted for the pressure drop associated with screens in series rather than that for an equivalent single screen. It is likely that most previous screen efficiency measurements are subject to similar errors and that new assessments should be undertaken. Contraction performance data can also be influenced by noise and unsteady separated flow effects. Fig. 38 shows the results of an assessment of the longitudinal turbulence transmissibility through contractions in a number of large-scale test facilities. These data indicate that there are significant differences in levels and trend for given tunnel contraction ratios. Contrary to theoretical predictions, the turbulence reduction factors decrease with increasing Mach number and are well below simple area ratio predictions at high subsonic Mach numbers. However, we have seen that the measured hot-wire values are contaminated by sound, particularly at transonic speeds. But, even at low speed, where the contribution of sound to the overall hot-wire signal is small, contraction ratio performance cannot generally be estimated from simple geometric area considerations since in many facilities large-scale unsteady separated flows upstream of the contraction reduce the effective area ratio. For example, although the dense mesh screens do a reasonable job in eliminating the large mean velocity gradients in the upstream flow in the Ames 12-ft PWT, the hot-wire data still show evidence of an outer flow displacement annulus downstream of the screens. Thus, it is evident that the flow does not expand at the sudden expansion into the settling chamber to fill the entire settling chamber crosssectional area, so that the effective contraction area is considerably reduced. At high subsonic Mach numbers, the increased contribution of pressure fluctuations to the test section hot-wire measurements account to a large extent for the apparent degraded contraction performance in the transonic regime. In many cases it could be expected that the turbulence reduction through the contraction will be impacted by large-scale

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Fig. 34. Turbulence measurements in Ames 12-ft wind tunnel at Mach ¼ 0.2, downstream of screens.

unsteady flow separations that decrease the effective contraction area ratio and by the influence of acoustic disturbances on the hot-wire measurements.

7. Flow quality management recommendations A review of flow quality test results from several wind tunnel facilities suggests that, at transonic speeds, significant flow quality improvements could be effected by the introduction of carefully designed sonic choke sections and mean flow and turbulence manipulators installed downstream of the test section. These devices can improve diffuser flow unsteadiness, and block diffuser generated disturbances from propagating upstream into the test section. However, the performance of turbulence management devices is a strong function of input mean-flow gradients, and turbulence length scale and intensity, which are difficult to match in small-scale test rigs. Extreme caution should be exercised when attempting to predict full-scale performance from small-scale test results. In most cases, full-scale screen performance falls well below that predicted from the measured pressure drop. This is primarily due to flow nonuniformities in the mean flow and large-scale turbulence that are generated around the wind tunnel circuit. Lack of screen porosity optimization also contributes to the problem. Although dense screens can be used to help remove mean gradients in the flow, screens with open-area ratios below about 0.57 can cause flow instabilities through the pores, which may cause the emerging flow to coalesce into random patterns which produce spanwise variations in the flow. On the other hand, large open-area ratios do not provide sufficient resistance at full-scale Reynolds numbers for effective turbulence reduction with a practical number of screens. Screens can also be used to reduce the turbulent length scales ahead of the contraction. Turbulence length scale can be optimized by reducing the mesh size as the flow passes through a combination of screens. But, the full effects of multiple screens will only be achieved if they are

Fig. 35. Hot-wire spectra across the screens, M ¼ 0.4, pres ¼ 30 in.

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Fig. 38. Effect of nozzle contraction on turbulence transmissibility in several test facilities.

Fig. 36. Pressure spectra across the screens, M ¼ 0.4, pres ¼ 30 in.

Fig. 37. Hot-wire measurements of screen effectiveness with noise removed.

installed far enough apart for the turbulence in the wire wakes of one screen to decay before the flow encounters the next screen. In most cases, screen spacing of about 500 wire diameters is sufficient. If screen wire Reynolds number exceeds 80, the wire wakes will become turbulent with very small spatial scales, which are likely to decay to unnoticeable levels in the test section. In many applications, screen geometries such as those with 20 mesh, 0.0103-in diameter and 30 mesh, 0.0065 diameter, with open-area ratios of 0.63 and 0.648, respectively, would be suitable. A total of five screens would provide optimum turbulence reduction for the pressure loss incurred. Honeycomb can also be an effective means of reducing swirl, turbulent length scales, and mean-flow gradients. It also reduces the lateral turbulence components that are inhibited by the cells. But honeycombs also shed turbulence, the strength of which is proportional to the shear layer thickness in the cells. For this reason, the cell length should be kept short, and the cell size should be smaller than the smallest anticipated lateral velocity turbulence length scales. In theory, almost complete removal can be achieved in a length equivalent to 6–8 cell diameters. In practice we have found that, although newly installed honeycomb in the Langley 8-ft PWT did significantly reduce the turbulence length scales, the axial turbulence was unchanged, and the lateral components were reduced by less than one-third. This is in stark contrast to many theoretical predictions and the small-scale measurements. Based on our full-scale testing experience, provided the mean-flow incidence does not exceed 101, the cells should be 0.5 in diameter and 4 in long, made of thin wall (0.05 in) hexagon stainless steel or aluminum mounted on 4-ft by 4-ft supporting grids. A large open-area screen (0.63) made of 20 mesh; 0.010-in diameter wire mounted immediately behind the honeycomb will break up and substantially reduce any turbulence generated by the honeycomb. The honeycomb should be installed at least 2-feet ahead of the turbulence reduction screens to allow time for the remaining turbulence to further decay before it reaches the screens. We have also found that most coolers act like a honeycomb/screen combination in that they produce small-scale turbulence that serve to help reduce the axial and lateral turbulence levels downstream in the settling chamber. Alternate forms of continuous finned cooler coils with dimensions and spacing optimized to treat the incoming turbulence length scales, followed by a coarse mesh screen, could remove the need for a separate honeycomb.

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In general, measurements also show that wind tunnel contraction performance falls well below theoretical predictions, and significantly lower than even simple area ratio considerations would suggest. In theory, large contractions are attractive since, in principle, they reduce the fluctuating velocity to a smaller fraction of the local mean and permit the installation damping screens and other turbulence suppression devices in the settling chamber without excessive energy loss. However, in practice, a contraction

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with a large area ratio and a practical length must have large wall angles, and consequently large curvature, which can result in local flow separations. It has long been recognized that turbulence reduction effectiveness of a contraction decreases with increasing area ratio. In fact, large contractions (greater than 15:1) have been found to produce increases in test section flow turbulence. Based on these measurements and observations, it should be possible to reduce the contraction ratio and still effect significant

Fig. A1. Sketch of the Langley 8-ft transonic pressure tunnel and measuring stations.

Fig. A2. Sketch of the Ames 12-ft pressure wind tunnel and measurement stations.

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Fig. A3. Langley low-turbulence pressure tunnel.

improvements in flow quality. This size reduction should also significantly reduce material and labor construction costs. Based on our measurements of the effectiveness of turbulence control devices in large-scale wind tunnel facilities, we can estimate the probable test section flow turbulence, excluding the acoustic contribution that must be treated separately by blocking diffuser noise, for an optimally designed facility. The estimates of test section turbulent flow quality for such a facility can be made as follows: across the cooler, 3:1, across the honeycomb and screens, 25:1, and through the contraction 12.5:1. This results in test section velocity fluctuation levels as low as 0.01% for a measured settling chamber input turbulence level of 10%. This would be significantly lower than current levels and would be comparable to free-flight conditions. In summary, critical assessment must be made of current and planned wind tunnel facilities, which are to be used in future, advanced wind tunnel testing. We may well have reached the stage where the lack of suitable facilities will soon hinder and dictate the rate of progress of ground-based testing. As a first step adequate maintenance of our existing facilities is essential. Detailed and consistent flow quality documentations should be encouraged and continued. Not only will this identify appropriate wind tunnels for experiments that demand a certain flow quality, but it will also lead the way to identifying sources of flow disturbances that can be targeted for improvement. This will lead the way to selective changes to improve flow quality and to useful classifications of our national facilities.

8. Concluding comments There is an international need to develop new technology, which will improve our capabilities for civil and military aerospace systems. These new instructional initiatives and flow quality instrumentation will provide sufficient flow quality awareness and in-situ measurement accuracy to assess the effects of subtle design changes which could be masked by current measurement techniques. Thus, these new capabilities will be a powerful aid in future wind tunnel test programs. The innovative

Fig. A4. Ames 2  2 ft2 transonic wind tunnel.

technology generated to develop these new instrumentation capabilities will be directly applicable to other wind tunnel test facilities in the public and private sectors. These novel capabilities will have a direct impact on the testing of new military and commercial concepts designed to improve efficiency and performance. They will help to provide the aeronautics industry with superior test capabilities at competitive cost and so help attract a viable customer-testing base, which will be required for costeffective facility operations. Finally, there is an urgent need for ‘‘in situ’’ measurements to expand our wind tunnel flow quality data base with detailed measurements of the full-scale performance of turbulent and noise suppression devices. Therefore, a major technical objective of this proposal is to develop measurement techniques and generate wind tunnel data, which will help diagnose and give insight into methods to suppress noise and turbulence, which are the major flow-generated disturbances in large-scale wind tunnels. These measurements of the performance of turbulence and noise suppression devices will lead to cost-effective improvements of wind tunnel flow quality which will be needed to help design and ground test the proposed new generation of fuel

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Fig. A5. Plan view of the Langley 4  7 m2 wind tunnel.

efficient transports for the new millennium. The insight gained and experimental techniques developed during this research program will help establish a viable wind tunnel design and documentation capability for a wide variety of wind tunnel test facilities.

Acknowledgement The authors wish to thank the National Aeronautics and Space Administration (NASA) for its continued support of this research. In particular, the support of the NASA Aeronautics Test Program (ATP) through SBIR Phase I and Phase II contracts is gratefully acknowledged.

Appendix A. Flow quality test facilities Langley 8-ft TPT—A sketch of the Langley 8-ft TPT is shown in Fig. A1. The circles with crosses indicate the type and locations where flow quality measurements were made. Further details can be found in Ref. [7]. The test section had a rectangular crosssection with slotted top and bottom walls. The facility was similar to most transonic tunnels except for the presence of a cooler, consisting of eight staggered rows of finned tubes, located in the corner just upstream of the 36-ft diameter-settling chamber. There were no turbulence suppression screens in the settling chamber, and the nozzle contraction ratio 20:1. For comparison purposes with the Ames 12-ft PWT, which has solid test section walls, the Langley 8-ft TPT test section wall slots were covered with 0.25-in thick metal plates that were beveled and mounted over the slots. Measurements were made with and without slot covers. Ames12-ft PWT—A sketch of this facility is shown in Fig. A2. The circles with crosses indicate where measurements were made across the screens, in the test section and in the diffuser. The facility has a rapid expansion (area ratio 2.0) ahead of a 60-ft diameter-settling chamber with eight screens in series spaced about 8 in apart. The most upstream screen has a mesh of 16 and is followed by seven screens with a mesh of 12. Porosity of the

screens is 0.462 and 0.490, respectively. The nozzle contraction ratio is 25:1. The model support strut is located at the circular test section exit and high-speed diffuser entrance. The strut has some blockage effects and is provided with vertical slots, which go completely through the strut for translation of the model sting. Except when noted, the present tests were conducted with 0.025 in thick cover plates mounted over the strut slots to eliminate flow-generated disturbances from the normally exposed slots. Ames 2-ft by 2-ft TPT—A sketch of this facility is shown in Fig. A3 along with an indication (crossed circles) of the locations where measurements were made. The tunnel is a closed return, variable density facility with a 2-ft2 test section. It has an adjustable flexible-wall nozzle and a slotted test section to permit transonic testing. The nozzle has a contraction ratio of 16:1 and there are no turbulence suppression screens or acoustic baffles in the settling chamber. Langley LTPT—This facility was designed especially for research on wing sections. A low-turbulence air stream was desired in which systematic investigations of large numbers of airfoils could be made at flight value Reynolds numbers. The tunnel shown schematically in Fig. A4 is of welded steel construction to permit operations at up to 10 atm. The test section is 3-feet wide, 7.5-feet high and 7.5-feet long. The nozzle contraction ratio is 17.6:1. A cooler/heater is available to control the tunnel air temperature, and is made of two rows of tubes. The tubes are 0.75-in in diameter with 0.013-in thick fins pressed over the tubes with a fin spacing of eight fins per inch. The total thickness of the cooler in the flow direction is 5-in. There are nine screens installed in the settling chamber 18-in downstream of the cooler. The screens are of 39 mesh having wires of 0.005-in diameter. The individual screens are 3-in apart and the most downstream screen is 15-in upstream of the entrance to the nozzle. Langley 14-ft by 22-ft (VSTOL) wind tunnel—A sketch of this facility is shown in Fig. A5. It is a continuous flow, closed-circuit wind tunnel with a contraction ratio of 9:1. There were two screens at the inlet to the contraction. The tunnel can be operated as a closed tunnel with slotted walls or in one or more open configurations by removing the sidewalls and ceiling to allow extra testing capabilities such as flow visualization and acoustic

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testing. Measurements were made around the entire wind tunnel circuit in the closed configuration as indicated by the circles with crosses.

References [1] Owen FK, McDevitt TK, Morgan DG, Owen AK. Wind tunnel angle of attack measurements using an optical model attitude system. AIAA 2000-0414, 2000. [2] Treon SL, Steinle FW, Hofstetter WR, Hagerman JR. Data correlation from investigations of a high-subsonic speed transport aircraft model in three major transonic wind tunnels. AIAA 69-794, 1969. [3] Recent Developments in Boundary Layer Transition Research-NASA Transition Study Group. Reprints of Articles in AIAA Journal, vol. 3(3), March 1975, based on Papers Presented at AIAA 12th Aerospace Science Meeting, February 1975. [4] Owen FK. An assessment of flow field simulation and measurement, AIAA Invited Paper, 83–1721, 1983. [5] Reed TD, Pope TC, Cooksey JM. Calibration of transonic and supersonic wind tunnels. NASA CR-2920, November 1977. [6] Barnwell RW, Edwards CLW, Kilgore RA, Dress DA. Optimum transonic wind tunnel. AIAA 86-0755, March 1986. [7] Day RA. Future test facility requirements and the role of heavy gas, in wind tunnels and wind tunnel test techniques. Royal Aeronautical Society conference, London, England, 1994. [8] National Wind Tunnel Complex, Facilities Study Office, Criteria and Requirements Document for Concept D-Option 5. Final Report, December 1993. [9] Owen FK, Stainback PC, Harvey WD. A program for the evaluation and improvement of flow quality in NASA wind tunnels. AGARD CCP 348, September 1983. [10] Kovasnay LS. The hot wire anemometer in supersonic flow. J Aeronaut Sci 1950;17(9).

[11] Morkovin MV. Fluctuations and hot wire anemometry in compressible flows. AGARDograph 1956;24. [12] Kovasnay LSG. Turbulence in supersonic flow. J Aeronaut Sci 1953;20(10). [13] Laufer J, McClellan R. Measurements of heat transfer from fine wires in supersonic flows. J Fluid Mech 1956;1(3). [14] Behrens W. Total temperature thermocouple probe based on recovery temperature of circular cylinder. Int J Heat Mass Transfer 1971;14. [15] Horstman CC, Rose WC. Hot wire anemometry in transonic flow. AIAA J 1977;15(3). [16] De Souza F, Tavoularis S. Hot wire response in high subsonic flow. AIAA paper no. 99-0310, 1999. [17] Amaya MA, Murthy SV. Flow quality measurements in the Ames upgraded 11-by 11-Ft transonic wind tunnel. AIAA paper no. 2000-2681, 2000. [18] Quest J. ETW—high quality test performance in cryogenic environment. AIAA paper no. 2000-2206, 2000. [19] Zinoviev V, Lebiga V, Chung KM, Miau JJ. Application of hot wire technology in a blowdown type transonic wind tunnel. AIAA paper no. 2001-0308, 2001. [20] Owen FK. An assessment of flow field simulation and measurement. AIAA paper no. 83-1721, 1983. [21] Stainback PC, Owen FK. Dynamic flow quality measurements in the Langley low turbulence pressure tunnel. AIAA paper no. 84-0621, 1984. [22] Harvey WD, Stainback PC, Owen FK. Evaluation of flow quality in two large NASA wind tunnels at transonic speeds. NASA TP 1737, 1980. [23] Stainback P.C., Owen F.K., Hot wire anemometry in transonic flows and cryogenic conditions. Second cryogenic review meeting, DFVLR, 1988. [24] Acharya M. On the measurement of turbulent fluctuations in high speed flows using hot wires and hot films. NASA TM 78535, 1978. [25] Mignosi A, Archambaud JP, Caruana D, Seraudie A. Measurement techniques developed for cryogenic environment in T2 transonic wind tunnel. 17th ICIASF, 1997. [26] Owen FK. Study of disturbance measurements around wind tunnel circuits. AIAA 97-0226, 1997. [27] Owen FK, Owen AK. Detailed study of flow quality in the NASA Ames 12-Ft pressure wind tunnel. AIAA 96-2204, 1996.