james h bell, edward t schairer, lawrence a hand, and rabindra...

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November 14, 2000 17:52 Annual Reviews AR117-06

Annu. Rev. Fluid Mech. 2001. 33:155–206

SURFACE PRESSURE MEASUREMENTS

USING LUMINESCENT COATINGS1

James H Bell, Edward T Schairer, Lawrence A Hand,and Rabindra D MehtaExperimental Physics Branch, National Aeronautics and Space Administration,Ames Research Center, Moffett Field, California 94035-1000;e-mail: [email protected], [email protected],[email protected], [email protected]

Key Words pressure-sensitive paints, optical measurement techniques,photogrammetry, aerodynamic loads, wind tunnel testing

■ Abstract An optical technique is described that is often used nowadays tomeasure surface pressures on wind tunnel models and flight vehicles. The techniqueuses luminescent coatings, which are painted on the model surface, excited by light ofappropriate wavelength, and imaged with digital cameras. The intensity of the emittedlight is inversely proportional to the surface pressure. Hence, the surface pressures canbe measured efficiently and affordably with a high spatial resolution. The theory andchemistry of how such coatings work and the parameters that affect them are presented.The required hardware and software are described, with emphasis on the differentmeasurement systems and procedures. The various error sources are discussed, andcorrection schemes that can be used to minimize them are presented. Sample results,covering a wide range of conditions and applications, are presented and discussed.

1. INTRODUCTION

In almost all practical aerodynamic testing or basic fluid mechanics experiments,surface pressure measurements are of fundamental importance, and they thereforeform an integral part of the measurement matrix. Surface pressure distributionsare generally integrated for “loads” analyses, either for the complete vehicle orfor specific parts of the model. Surface pressure measurements are also very valu-able in identifying and studying specific flow phenomena such as boundary layerseparation or shock wave impingement on the surface. Another critical use ofsurface pressure measurements is in validating computational codes. With rapid

1The US government has the right to retain a nonexclusive, royalty-free license in and toany copyright covering this paper.

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improvements in computational fluid dynamics (CFD), the need for accurate anddetailed pressure data has become even more urgent so that new codes can beadequately verified and tested before they are used in design processes.

The conventional methods for surface pressure measurements consist of usingeither pressure taps or transducers that are installed at discrete points on the model.Almost all wind tunnels are equipped with systems that can readily scan and recorddata from such devices, and their measurement accuracies are generally well un-derstood. However, these systems have several drawbacks. For one, measurementscan be obtained only at discrete (predetermined) locations, and there are alwayslimitations on where the taps or transducers can be installed. It is almost impossi-ble to instrument thin edges and sharp corners on a model, and these are often theareas of most interest. Furthermore, to get reasonable spatial resolution, a largenumber of taps or transducers must be installed, and this is very time-consumingand extremely expensive. Until recently, there was no alternative, and this portionof the aircraft design cycle accounted for a good fraction of the overall requireddesign time and expense.

In the 1980s, a groundbreaking aerodynamic-measurement technique wasdeveloped that eliminates the constraints of pressure taps, providing the aero-dynamicist with the ability to affordably and rapidly obtain surface pressures onwind tunnel models, with very high spatial resolution. This method, popularlyknown as the pressure-sensitive paint (PSP) technique, uses a special coating anddigital-imaging technology to obtain surface pressure information at an unprece-dented resolution. Figure 1 is a schematic diagram of a typical PSP measurementsystem, including an example of the spatial resolution that can be obtained.

PSP is a coating that consists of sensor molecules contained in a transparentoxygen-permeable polymer binder. When illuminated with light at an appropriatewavelength, the sensor molecules become excited electronically to an elevatedenergy state. The molecules undergo transition back to the ground state by one of

Figure 1 A typical pressure-sensitive paint measurement system.

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PRESSURE-SENSITIVE PAINTS 157

several mechanisms, each occurring at a different rate. The predominant mech-anisms are radiative decay (luminescence) and nonradiative decay through therelease of heat. Some materials can also return to the ground state by collidingwith an oxygen molecule, a process known as “oxygen quenching.” The rate ofquenching is proportional to the local oxygen partial pressure, which is in turnproportional to absolute pressure. Therefore, the luminescence of the PSP coatingis inversely proportional to the local surface pressure. Because this is an abso-lute measurement technique, it works more effectively for the higher-speed flows(transonic and higher), where the pressure levels and differences are a much higherpercentage of the ambient pressure.

The main advantage of the PSP technique is that, in principle, a full spatialdistribution of the surface pressures can be obtained, with the spatial accuracydetermined by the characteristics of the camera lens and charge-coupled device(CCD). In particular, PSP makes it possible to determine aerodynamic loads (byintegrating the surface pressures) without the need for a heavily instrumentedloads model. This is assuming, of course, that full optical access to all of thecritical (load-bearing) parts of the model is readily available. Another somewhatunappreciated aspect of the PSP technique is that flow features such as shocklocations and boundary layer separation and reattachment can often be observed inthe raw (unprocessed) images; thus the PSP technique can serve as an online surfaceflow visualization tool during testing. The main disadvantage is the relatively highinitial investment that is required (typically $20,000–$30,000), although this can beamortized over several tests, with the only additional cost being that for the coatingitself. Another drawback of this technique, which can significantly affect the dataaccuracy, is that all PSP coatings have some sensitivity to temperature, whichmust be accounted for in the calibrations. Data acquisition and processing timesare also generally longer than for the conventional tap measurements, although thetradeoff, of course, is the enormous increase in the number of measurements.

A detailed history of the development of PSP measurement systems, includingpersonal notes and recollections from some of the early pioneers, is given by Brown(2000); some of the more important events from this history are included here.The quenching of luminescence by oxygen was first discovered by the Germanscientists Kautsky & Hirsch (1935). Many years later, Peterson & Fitzgerald (1980)demonstrated a surface flow visualization technique based on oxygen quenching offluorescence. In the early 1980s, a team led by Martin Gouterman of the Universityof Washington (UW) developed a probe based on an oxygen-quenching porphyrinthat could measure the blood oxygen content. By the late 1980s, the idea ofusing this technique for pressure measurements on aerodynamic models had beendeveloped, and a qualitative experiment was performed at UW (Gouterman et al1990). In the summer of 1989, what was seemingly the first quantitative demon-stration of the PSP technique took place at the National Aeronautics and SpaceAdministration (NASA) Ames Research Center, using the coating developed atUW (McLachlan et al 1989, Kavandi et al 1990, Kavandi 1990, McLachlan et al1993, Gouterman 1997).

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158 BELL ET AL

Totally unknown to the western world, Russian scientists had been researchingthis topic since the late 1970s at the Central Aero-Hydrodynamic Institute (TsAGI)in the former Soviet Union. Inspired by the 1960s work of Zakharov on the oxygen-quenching properties of luminophores, Pervushin and Nevsky developed the firstpressure-sensitive coating in 1981 (Pervushin & Nevsky 1981) and obtained thefirst pressure measurements in 1982 (Ardasheva et al 1985). By the mid-1980s,another TsAGI group started work in this field, and they developed a new polymer-based PSP. They performed their first PSP experiments in 1985, on a cone-cylindermodel at supersonic Mach numbers (Radchenko 1985). Using the “lifetime” tech-nique (see Section 3.2), they found that the coating suffered from very high temper-ature sensitivity and a very long response time. The TsAGI researchers continuedto improve the system, and they went on to conduct several PSP experiments, bythen using “intensity-based” methods (see Section 3.1) exclusively (Bykov et al1992, 1993; Troyanovsky et al 1993; Mosharov et al 1997). The revelation in theWest of these Russian efforts came in the form of an advertisement for an “OpticalPressure and Temperature Measurement System” that appeared in the February12, 1990, issue ofAviation Week & Space Technology.This advertisement wasthe start of a commercialization effort by the Russians through their distributorin Italy, INTECO (Volan & Alati 1991). The INTECO measurement system wasdemonstrated in several wind tunnels in the United States and Europe in the early1990s. A complete description of the PSP system developed by the Russians, in-cluding some theoretical background, sample results, and error analysis, is givenby Mosharov et al (1997).

Over the last decade, PSP research and development has spread to aerospaceinstitutions all over the world. Among the main players are the three NASA re-search centers: Ames, Langley, and Glenn (formerly Lewis). Others include BoeingSeattle, Boeing St. Louis (formerly McDonnell Douglas), Purdue University,Arnold Engineering Development Center (AEDC), University of Florida, andthe US Air Force Wright-Patterson Laboratory—all in the United States; BritishAerospace (BAe) and the British Defence Evaluation and Research Agency(DERA) in the United Kingdom; Deutsche Forschungsanstalt fur Luft- undRaumfahrt e.V. (DLR) in Germany; Office National d’Etudes et de RecherchesAerospatiales (ONERA) in France; National Aerospace Laboratory (NAL) inJapan; and TsAGI in Russia. A complete bibliography of papers on PSP is main-tained by Purdue University, and it is available on line at http://roger.ecn.purdue.edu/∼psptsp// references/ReferencesPSPTSP.html.

Useful reviews on PSP were previously given by Crites (1993), McLachlan &Bell (1995), and Liu et al (1997). The more recent low-speed PSP applicationsare covered in a thesis by Brown (2000), and Mehta et al (2000) discuss the PSPtechnique with emphasis on how to apply it and how to accurately reduce thedata. The latest developments in PSP measurement technology are reviewed here,with emphasis on the underlying theory, application of the technique (includinghardware and software requirements), discussions of the error sources, and sampleresults covering a wide range of conditions.

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2. BASIC PRINCIPLES

The structure of a typical layer of PSP is shown in Figure 2. The active layerconsists of luminescent molecules (luminophore) immobilized in a transparentoxygen-permeable matrix (binder). Sometimes a scattering agent is added to thebinder to increase the mean optical path length in the active layer. A diffuselyreflecting base coat is frequently incorporated between the active layer and thesubstrate. The strength of the luminescence signal depends on the absorption ofthe exciting radiation and the efficiency of the luminescence process, the latterbeing sensitive to oxygen. In this section, we derive the basic working equationsof PSP from first principles of luminescence.

2.1 Absorption of Incident Light

As light passes through the active layer, the rate of absorption of photons bythe luminophore at depthz is in direct proportion to the illumination intensity(II), the effective absorption (cross-sectional) area of the luminophore (σ ), andthe concentration of the luminophore (n). The absorption per unit volume can beapproximated by the Beer-Lambert law (Lakowicz 1983):

a(z, t) ≈ −d II /dz= I I (z, t)σn, I I (z, t) = I I (0, t)exp(−σnz). (1)

Equation 1 assumes normal incidence, uniform luminophore concentration, andnegligible reflection by the base coat and/or scattering agent. Therefore, it is usuallyan oversimplification, but nonetheless a useful approximation. Time dependenceis included because some PSP techniques use a pulsed or modulated light source.

Figure 2 Pressure-sensitive paint layer structure and typical dimensions.

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160 BELL ET AL

The effective absorption area of the luminophore is dependent on excitationwavelength (e.g. Figure 3) and is customarily specified in terms of the decadicmolar extinction coefficient,ε = σ /ln(10), in standard units of liters per moleper centimeter. Typical peak values for PSPs (luminophore in solid binder) areε ∼ 2 × 104− 2 × 105 mol−1liter cm−1 (σ ∼ 5 × 107− 5 × 108 cm2 mol−1).

Luminophore/binder concentrations are typically in the rangen∼ 10−3–10−2

mol liter−1. Higher concentrations are usually counterproductive owing to detri-mental interactions (e.g. self-quenching) between the luminophore molecules. Theonset of these “concentration effects” often occurs at∼10−3 mol liter−1. At thatconcentration, the average distance between molecules is∼10 nm.

The absorptivity of a layer of thicknessd is frequently specified by the opticaldensity,εnd.According to Equation 1, the fraction of incident light that is absorbedin the layer is then 1−10−εnd. The optical density of a PSP active layer is typicallybetween 0.3 and 1 (50%–90% absorption). For the typical values ofε andn givenabove, an optical density of 1 would require an active layer thicknessd> 5 µm.A diffusely reflecting base coat can increase the effective thickness by a factor of2–3. More detailed analyses of the absorption process are given by Brown (2000)and LA Hand (manuscript in preparation).

2.2 Luminescence Processes

The general principles of luminescence are nicely presented by Parker (1968),Becker (1969), Turro (1978), and Lakowicz (1983). Gouterman (1997), Mosharovet al (1997), Sabroske & Gord (1995), and Gewehr & Delpy (1993) discuss lumi-nescence processes in the context of PSP and oxygen sensing. This description,

Figure 3 Absorption (left) and emission (right) vs wavelength for platinumtetra(pentafluorophenyl)porphyrin in fluoroacrylic polymer binder (PtTFPP/FIB) (data fromTanji 1998, Puklin et al 2000).

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which is extracted from these and other sources, is intended to be simple, butrealistic, and to provide a basis for the mathematical model that follows.

The physical processes of luminescence are best described with the aid ofa Jablonski energy-level diagram (Figure 4). This diagram shows the differentexcited states of a luminophore molecule with the energy of each represented byits height above the ground state,S0. The diagram is laterally divided into thesinglet system (electronic statesS0, S1, S2, S3, ...) and the triplet system (electronicstatesT1, T2, T3, ...). The ground state of the luminophore is singlet, so there is noT0. In each electronic state, the molecule has its electrons arranged in a differentcombination of the available orbits and spin orientations—the latter distinguishingthe singlet and triplet states. Also shown in the diagram are the energy levels ofthe various vibrational states of each electronic state.

The diagram shows the relevant luminescence processes: excitation (S0→ S1andS0→ S2), vibrational relaxation (an intrastate process), internal conversion(S2→ S1 andS1→ S0), intersystem crossing (S1→ T1, T1→ S1, andT1→ S0),emission (S1→ S0 andT1→ S0), and quenching (S1→ S0 andT1→ S0). Internalconversion and intersystem crossing are represented by horizontal lines, indicatingno change in energy. All of the other processes change the molecule’s energy, butonly excitation and emission involve radiation.

Intersystem (singlet-to-triplet and triplet-to-singlet) transitions require a changein electron spin and are therefore theoretically forbidden by laws of quantum

Figure 4 Jablonski energy-level diagram showing luminescence processes for a typicalluminophore.ES, fluorescence;ET, phosphorescence.

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162 BELL ET AL

TABLE 1 Approximate energy levelsand associated wavelengths for PtTFPP

State ∆ E(eV ) λ(nm)

S2 3.1 400

S1 2.3 540

T1 2.0 620

mechanics for pure singlet and triplet states. However, spin-orbit coupling intro-duces mixing between these pure states, and these transitions thus become possiblealthough generally with low probability. The probabilities depend on molecularstructure and increase with the atomic number of the atoms involved (Turro 1978).In some inorganic luminophores containing heavy metal atoms such as platinum orruthenium, intersystem crossings can be as likely to occur as internal conversions.The intersystem radiative transitions are, however, always at least several ordersof magnitude less probable than their intrasystem counterparts (Demas 1983).

The wavelength of the radiation is related to the energy change by Planck’sequation:1E = hv = hc/λ wherehc= 1240 eV nm (1 eV= 96.5 kJ mol−1).Approximate energy levels (relative toS0) and associated wavelengths for aluminophore widely used in PSP, platinum tetra(pentafluorophenyl)porphyrin(PtTFPP), are shown in Table 1. These values are similar to those of some othermetalloporphyrins that are used as oxygen sensors, for example platinum octaethyl-porphyrin (PtOEP) and palladium coproporphyrin (Gouterman 1997, Gewehr &Delpy 1993).

The absorption spectrum for PtTFPP in the fluoro/isopropyl/butyl (FIB) poly-mer binder exhibits a global absorption maximum at 392 nm and two much lowerlocal maxima at 506 and 538 nm (Figure 3). The first maximum corresponds toexcitation toS2 and the following two toS1. [FIB is a fluoroacrylic polymer de-veloped specifically for use as a PSP binder (see Gouterman & Carlson 1999 andPuklin et al 2000).]

The absorption and emission processes generally proceed from a state of thermalequilibrium to various vibrational levels of the new electronic state. Consequently,the emission energy is less than that of the excitation, and the emission will thus beshifted to longer wavelengths relative to those of the excitation. This fundamentalcharacteristic of luminescence was first noted by Stokes (1852) and is called theStokes shift. Stokes used visual detection and a glass of wine as an optical filter toseparate the emission from the illumination.

Each of the processes indicated in Figure 4 has an associated first-order rateconstant,k. The rate at which the particular process depopulates its initial state(e.g.S1) is proportional to the instantaneous number of molecules in that state:dn/dt = −kn. When applied to a single molecule,k represents that process’s prob-ability per unit time. The probability of the processnot occurring within timetis exp(−kt). The reciprocal of the rate constant, 1/k, is often called the intrinsiclifetime of the process, which must not be confused with the observed lifetime of

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an emission. The latter generally depends on several processes acting simultane-ously.

Excitation begins in the ground state. At room temperature, nearly all of themolecules will be in the lowest vibrational state ofS0. Absorption of a photon ofsufficient energy will raise a molecule into one of the vibrational states ofS1 orS2. This process is virtually instantaneous—it occurs in∼10−15 s. From there, themolecule will relax to the lowest vibrational state of the excited electronic state bytransferring thermal energy to surrounding molecules. If the molecule is in theS2state, it will then undergo internal conversion to an excited vibrational state ofS1,and relaxation to the lowest vibrational level withinS1, all usually within∼10−12 safter excitation. If, however, the energy gap between the two states is somewhatlarger than 1 eV, relaxation is generally slower. Excitation directly to the tripletstate from the ground state is essentially forbidden, as discussed above.

Once the molecule reaches equilibrium in the first singlet state (S1), the pro-cesses slow down and there are several possibilities (Figure 4):

1. Fluorescence (ES)—a radiative transition toS0 (kES= 106–109 s−1).

2. Internal conversion (IS) to S0. Because of the large energy gap betweenS1andS0, this process is much slower than the internal conversion fromS2 toS1 (kIS = 105–109 s−1).

3. Quenching (QS)—a transition toS0 by collision with an oxygen molecule.The rate is proportional to the concentration of oxygen and can varygreatly (kQS = κQS[O2] = 0–108 s−1). The constant of proportionality,κ,is called the bimolecular quenching rate.

4. Intersystem crossing (ST) to T1. In some luminophores (e.g. platinumporphyrins and ruthenium complexes) this process can be extremely rapid(kST = 104–1012 s−1).

At this point, if the molecule has not returned to the ground state, it will be inthe first triplet state (T1) and there will be several new possibilities:

1. Phosphorescence (ET)—an intersystem radiative transition toS0. This is a“forbidden” process and consequently can be extremely slow(kET = 10−2–106 s−1). Because the energy ofT1 is lower than that ofS1, thewavelength of phosphorescence is longer than that of fluorescence.

2. Intersystem crossing (IT ) to S0 (kIT = 101–109 s−1).

3. Quenching (QT) to S0 as above (kQT = κQT[O2] = 0–108 s−1).

4. Intersystem crossing (TS) back toS1. BecauseS1 is a higher energy statethanT1, this process must be thermally activated. The rate constantdepends on the energy difference and the temperature according to theArrhenius equation:kTS = ATSexp(−1ETS/RT), whereATS = kST/3 andR = 8.314 J mol−1 K−1 = 8.616× 10−5 eV K−1 (Coyle 1999).

If the molecule still has not returned to the ground state, it will now be backin the first excited singlet state (S1), and all of the above events will again bepossible. Fluorescence occurring at this point is called delayed fluorescence. It has

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164 BELL ET AL

the spectrum of fluorescence and the decay time of phosphorescence and is highlytemperature dependent. Early Russian PSPs used delayed fluorescence (Ardashevaet al 1985, Mosharov et al 1997), but most current PSPs use phosphorescence(e.g. metalloporphyrins and ruthenium complexes) or fluorescence (e.g. pyrene).The term luminescence includes all of these phenomena.

The oxygen molecule is unusual in that its ground state is triplet and it has apair of excited singlet states at only 1.0 eV above the ground state. These charac-teristics make ground-state oxygen an extraordinarily effective quencher. (Otherparamagnetic gases are known to quench luminescence but are not found in ordi-nary air.) A quenching interaction with an excited luminophore is accomplishedby energy transfer to the ground-state oxygen molecule, which usually raises itto one of its lowest-energy singlet states (Gouterman 1997). The acquired energyis then dissipated by luminescence (λ >1240 nm) and by intersystem crossingto a vibrationally excited ground state, followed by vibrational relaxation. Thelifetime of singlet oxygen is very dependent on its environment and can vary overmany orders of magnitude (Turro 1978). However, Mosharov et al (1997) report alifetime of∼40µs in PSP applications.

It is important that the excited fraction of oxygen molecules remain small be-cause singlet oxygen does not quench luminescence. Singlet oxygen is also highlyreactive and likely to engage in irreversible chemical reactions with a susceptiblebinder or luminophore. This is a primary mechanism for PSP photodegradation(Uibel et al 1993, Gouterman 1997). Fortunately, direct photoexcitation of oxygenfrom the (triplet) ground state to the singlet state is essentially forbidden.

2.3 Kinetic Model

Assuming that no irreversible chemical reactions occur and that practically allof the oxygen molecules are in the ground state, the simultaneous action of allof the luminescence processes discussed above is described by a pair of coupledfirst-order equations for the concentrations of excited molecules and a speciesconservation equation (Mosharov et al 1997):

dnS1/dt = I I (z, t)σnS0− (kE S+ kI S+ kQS+ kST)nS1+ kT SnT1, (2a)

dnT1/dt = kSTnS1− (kET + kI T + kQT + kTS)nT1, (2b)

nS0+ nS1+ nT1 = n, (2c)

wherekQS= κQS[O2] andkQT= κQT[O2]. In the general case, both of the decoupledequations for concentrationsnS1 andnT1 will be second-order ordinary differentialequations. However, under certain conditions that are typical for PSP (see below),these equations reduce to first order:

τSdnS1/dt + nS1 = τSI I (z, t)σn = τSa(z, t), (3a)

τTdnT1/dt + nT1 = τT8T I I (z, t)σn = τT8Ta(z, t), (3b)

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where the time constantsτSandτT are called the lifetimes of the singlet and tripletstates and correspond to the observed lifetimes of fluorescence and phosphores-cence, respectively:

1/τS = kE S+ kI S+ kQS+ kST = kE S+ kI S+ κQS[O2] + kST, (4a)

1/τT = kET + kI T + kQT = kET + kI T + κQT[O2]. (4b)

Here8T is the triplet quantum yield—the fraction of absorbed photons thatultimately produces luminophore molecules in the triplet state. This is equivalentto the fraction of luminophore molecules leavingS1 that does so by intersystemcrossing toT1:

8T = kST

kE S+ kI S+ kQS+ kST= kSTτS. (5)

The assumed conditions under which Equations 3a and 3b are valid (LA Hand,manuscript in preparation) are as follows:

1. Most of the luminophore molecules are in the ground state:nS1� n andnT1� n.

2. The singlet (fluorescence) lifetime is much shorter than the triplet(phosphorescence) lifetime (τS/τT� 1). This ratio is often∼10−3.

3. The termskTSnT1 (the source of delayed fluorescence) in Equations 2a and2b are negligible.

4. The oxygen concentration varies on a timescale much larger than thelifetime of the emission being observed.

The rates of fluorescence and phosphorescence emission (per unit volume) areeF = kES nS1 andeP = kETnT1, respectively. Equations 3a and 3b can thus bewritten in terms of absorption and emission:

τSdeF/dt + eF = kE SτSa(z, t) = 8Fa(z, t), (6a)

τTdeP/dt + eP = kETτT8Ta(z, t) = φP8Ta(z, t) = 8Pa(z, t). (6b)

Here8F is the fluorescence quantum yield—the fraction of absorbed photonsthat produces fluorescence (equivalent to the fraction of molecules leavingS1 thatdoes so via fluorescence),φP is the phosphorescence quantum efficiency—thefraction of molecules leavingT1 that does so via phosphorescence, and8P is thephosphorescence quantum yield—the fraction of absorbed photons that producesphosphorescence.

An electrical circuit analogy for phosphorescence corresponding to Equations6b and 4b is shown in Figure 5 (LA Hand, manuscript in preparation). (Thecircuit analogy for the fluorescence equations is almost identical.) The currentsource corresponds to the effective rate of excitation of molecules into the tripletstate. The common voltage across all of the elements represents the number ofmolecules in the triplet state. The capacitance therefore has a dimensionless value

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166 BELL ET AL

Figure 5 Electrical circuit analogy for oxygen-quenched phosphorescence.

of 1. The resistances represent the three parallel decay channels: phosphorescence(“lamp,” 1/kET), intersystem crossing (fixed resistor, 1/kIT), and quenching (rheo-stat, 1/κQT[O2]). The phosphorescence output,eP = kETnT1, is then analogous tothe lamp current. In the following situations, which correspond to PSP measure-ment techniques, assume that the oxygen concentration increases and thus reducesthe resistance of the rheostat. If the excitation is steady, current will be divertedfrom the lamp and the phosphorescence output will be reduced. If the excitationis pulsed, the capacitor will discharge more rapidly and the phosphorescence de-cay time will decrease. If the excitation is sinusoidally modulated, the phase shiftbetween the excitation and emission will decrease. Also, notice that if the lampcurrent is to track adjustments of the rheostat, the adjustments must be made ona timescale that is large compared with the time constant of the circuit. Thus, theluminescence lifetime imposes anultimatelimit on the speed with which PSP canrespond to pressure changes. However, with present PSP technology, temporalresponse is limited by the rate of diffusion of oxygen in the binder.

Generally, phosphorescence is more sensitive to quenching than is fluorescence.Although oxygen is known to quench both the singlet and triplet states, the othersinglet-state decay rates (kES, kIS, andkSTin Equation 4a) are often so much greaterthan the quenching rate that the quenching effect is negligible. This is usuallytrue for PSPs that use phosphorescence. Metalloporphyrins exhibit fluorescencelifetimes of<20 ns in vacuum (Gouterman 1997). Consequently, their fluorescencequantum yield, fluorescence lifetime, and triplet yield are relatively insensitive tooxygen concentration. PSPs based on fluorescence usually use a luminophore witha very long fluorescence lifetime (e.g.τS∼ 300 ns for pyrene in vacuum) to achieveadequate pressure sensitivity.

Metalloporphyrins typically exhibit triplet yields (Equation 5),8T > 50%. Forsome platinum porphyrins (e.g. PtOEP and PtTFPP) and many ruthenium lu-minophores,8T ∼ 100% (kST is the dominant singlet-state decay rate), so virtu-ally no fluorescence is observed (Gouterman 1997, Demas 1983). The PtTFPPemission spectrum (Figure 3) shows nothing in the 540- to 600-nm range, wherefluorescence would occur. The emission shown in the 600- to 750-nm range is purephosphorescence.

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The discussion that follows deals exclusively with phosphorescence, but theanalogous development for fluorescence is nearly identical. The quasi-steady con-dition is (from Equation 6b)

eP = 8pa = 8TkETτTa = 8TkETa

kET + kI T + kQT= 8TkETa

kET + kI T + κQT[O2]. (7)

Assuming that8T , kET, kI T , and a are independent of oxygen concentrationand denoting an oxygen-free condition (e.g. vacuum) by the subscriptVAC, theemission ratio is equivalent to the ratio of lifetimes:

eP VAC

eP= τT VAC

τT= kET + kI T + kQT

kET + kI T= 1+ τT VACkQT = 1+ KSV[O2], (8)

whereKSV = τT VACκQT is known as the Stern-Volmer constant.2 Generally, thisequation is valid only if the temperatures of the vacuum and pressure conditionsare equal.

2.4 Pressure and Temperature Sensitivity

Although the triplet quantum yield(8T ) is usually relatively insensitive to oxygenconcentration (and hence pressure), it is generally temperature dependent. How-ever, if8T ∼ 1, as discussed above, then it is insensitive to both pressure andtemperature.

The temperature dependence of the phosphorescence emission rate(kET) is dueonly to the temperature dependence of the refractive index of the medium and isextremely weak (Schanze et al 1997, Gouin & Gouterman 2000a). The triplet-statedecay rate owing to intersystem crossing(kI T ) varies with temperature accordingto an Arrhenius relationship (Schanze et al 1997, Gouin & Gouterman 2000a):

kI T (T) = AI T exp

(−1EI T

RT

)∼= kI T (T0)

(1+ 1EI T

RT0

1T

T0

), (9)

where1EIT is the activation energy associated with the process (typically∼10–30 kJ mol−1), T0 is an arbitrary reference temperature, and1T = T− T0 is smallrelative toT0. The decay rateskET andkIT depend primarily on the luminophoreand, to a lesser extent, on its environment (Schanze et al 1997). Consequently, asan idealization, the vacuum lifetime,τT VAC = (kET+ kIT)−1, can be regarded asintrinsic to the luminophore.

In contrast, the bimolecular quenching rate,κQT, depends primarily on theproperties of the binder, as indicated by the Smoluchowski equation (Gouin &Gouterman 2000c, 2001):κQT = 4πNαrD, whereD is the sum of the diffusivitiesof oxygen and the luminophore (the latter is usually negligible) within the binder,r

2KSVis expressed in units of (oxygen concentration)−1. Alternate definitions ofKSVused inthe literature incorporate (as factors) the oxygen solubility (S) and sometimes the oxygenmole fraction (χ ) also (see Equation 10), thus resulting in units of (oxygen pressure)−1 (e.g.Xu et al 1994) or (air pressure)−1 (e.g. Schanze et al 1997). Let the reader beware!

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is the radius of interaction between luminophore and oxygen molecules (typically∼1 nm, luminophore dependent),α is the quenching efficiency (the probabilityof quenching once the interaction has occurred), andN = 6.023× 1023 mol−1

is Avagadro’s number. Ideally,α = 1/9 for triplet states andα = 1 for singletstates. The former value is generally appropriate for metalloporphyrins (Gouin &Gouterman 2001). However, the triplet states of many ruthenium luminophoresexhibit singlet characteristics owing to strong spin-orbit coupling (Section 2.2)and have quenching efficiencies that approach unity (Demas et al 1977).

For quasi-steady pressure variations, the oxygen concentration in the binder isproportional to the partial pressure of oxygen above it (Henry’s law). Thus, thequenching rate is proportional to pressure:

kQT = κQT[O2] = κQT Sχp = 4πNαr DSχp = 4πNαr Pχp, (10)

whereSis the solubility of oxygen in the binder,χ is the mole fraction of oxygen inthe gas (χ = 0.21 for air),p is the gas pressure,χp is the oxygen partial pressure(Dalton’s law), andP = DSis the oxygen permeability of the binder. Permeabilityvaries with temperature according to an Arrhenius relationship. Consequently,

kQT(p, T) = AQT exp

(−1EQT

RT

)χp ∼= kQT(p0, T0)

(1+ 1EQT

RT0

1T

T0

)p

p0,

(11)

where the factor 4πNαr has been incorporated into the constantAQT,1EQT is the ac-tivation energy for oxygen permeation in the binder, andp0 is an arbitrary referencepressure. Pauly (1999) has compiled oxygen diffusivity, solubility, and permeabil-ity data (including activation energies) for many different polymers. However,bulk properties may not accurately represent the effects of filled polymers in PSPbecause of potential localized interactions between the filler and the luminophore(Xu et al 1994).

Equations 9 and 11 imply that the triplet (phosphorescence) lifetime(Equation 4b) and the quasi-steady phosphorescence emission per unit volume(Equation 7) are functions of both pressure and temperature:τT = τT ( p, T ) andeP = eP( p, T, z, t). The pressure and temperature sensitivities are, respectively,

Sp ≡ p

ep

∂eP

∂p

∣∣∣∣T

= p

τT

∂τT

∂p

∣∣∣∣T

= −τTkQT = − τT VACkQT

1+ τT VACkQT, (12a)

ST ≡ T

ep

∂eP

∂T

∣∣∣∣p

= T

τT

∂τT

∂T

∣∣∣∣p

= −τT

(kI T

1EI T

RT0+ kQT

1EQT

RT0

), (12b)

where it has been assumed thatkI T is independent ofp and that8T , kET, andaare independent of bothp andT (see discussion below).

Using Equation 10, the product appearing in Equation 12a can be expressedτT VACkQT = 4πNαrτT VACPχp, thus showing the individual influences of the lu-minophore (αrτT VAC), binder (P), and operating conditions (χp). As τT VAC kQT

becomes large,Sp approaches−1. Sp values in the range of−0.5 to−0.9 (at

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atmospheric conditions) are common. Using Equations 8 and 12a, it is easy toshow thateP/eP VAC= 1+Sp. It is thus evident that pressure sensitivity is achievedat the expense of luminescence output signal. The design of a PSP for a particularpressure range is an optimization of this trade-off.

Because the Arrhenius activation energies are positive quantities, Equation 12bshows that PSP temperature sensitivity is inherently negative, as is the pressure sen-sitivity. Consequently, curves of constant luminescence emission or lifetime havenegative slope in thep-T plane. At present,ST ∼−1 for the least temperature-sensitive PSPs. It is sometimes suggested that PSP measures density rather thanpressure (i.e.eP∝ 1/ρ = RT/p). If this were true, thenSp would be−1 andST

would be+1. Thus, for a hypothetical density sensor, the sign of the temperaturesensitivity would be opposite to that for the present model and past observations.However, the magnitudes of both the pressure and temperature sensitivities wouldbe comparable to those for PSP. Therefore, the least temperature-sensitive PSPsare presently about as far from an ideal pressure sensor as is a density sensor, butin the opposite direction. Temperature sensitivity is a primary focus of current PSPresearch.

An important special case occurs when the temperature sensitivity of a paint isindependent of pressure. Such paints were described as “ideal” by the researchersat TsAGI, who first noticed the desirability of this property. It allows the effect ofmean temperature variation between test and reference conditions to be correctedby applying a single scaling factor, independent of local pressure (Puklin et al2000, Gouin & Gouterman 2000a-c, Ji et al 2000).

Table 2 gives experimentally determined phosphorescence model parametervalues for PtTFPP in both FIB and a silicone binder and for a ruthenium complex

TABLE 2 Phosphorescence model parameter values at ambient conditionsa

Luminophore PtTFPP PtTFPP RudpCl RudpCl

Medium FIB SR900 PDMS Ethanol

kET (s−1) 9.8× 103 1.1× 104 4.1× 105 1.3× 105

kIT (s−1) 1.6× 103 3.6× 103 1.4× 105 8.4× 104

kQT (s−1) 9.5× 104 4.7× 105 7.0× 106 3.3× 106

1EIT/RT 5.69 6.05 8.62 12.3

1EQT/RT 0.70 4.84 4.56 0.34

τT VAC(µs) 87.7 68.5 1.82 4.67

τT (µs) 9.40 2.06 0.13 0.28

–Sp 0.89 0.97 0.93 0.94

–ST 0.71 4.74 4.39 0.61

a T = 298 K, p = 1 atm, χ = 0.21. PtTFPP, Platinum tetra(pentafluoropheny1)porphine; RudpCl, tris-(4,7-dipheny1-phenanthroline) ruthenium(II) dichloride; FIB, fluoroacrylic polymer binder (non-annealed); SR900, sili-cone binder (no pigment); PDMS, polydimethylsiloxane (silicone binder). Data sources: PtTFPP, Gouin & Gouterman(2000a,c); RudpCl, Schanze et al (1997). Rows 8–11 computed using Equations 4b and 12.

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170 BELL ET AL

in both a silicone binder and an ethanol solution. The two luminophores are quitedifferent, as indicated by their vacuum lifetimes. The two silicone binders (SR900and PDMS) are similar to each other and are roughly an order of magnitude morepermeable to oxygen than is FIB. The higher permeability could be appropriatefor the ruthenium luminophore because of its shorter vacuum lifetime but causesexcessive quenching of PtTFPP. Presumably, the large difference in the observedquenching rates (kQT) for PtTFPP/SR900 and RudpCl/PDMS is primarily a con-sequence of the difference in the quenching efficiencies (α in Equation 10) for thetwo luminophores, as discussed above.

Also noteworthy is the effect of the binder on the temperature sensitivity. Thedata are for normal ambient conditions:p = 1 atm andT = 298 K. Temperaturesensitivities in percent per degree Celsius can therefore be obtained by dividing theST values by 2.98. For PtTFPP/FIB,ST = −0.71 (−0.24%◦C−1). This value is ingood agreement with the measured temperature sensitivity of the phosphorescencelifetime (−0.28%◦C−1) but is considerably lower than that of the phosphorescenceintensity (−0.63%◦C−1). The difference is attributed to temperature-dependentabsorption of incident light, i.e.σ = σ (T) in Equations 1, 2, and 3, anda = a(T)in Equations 1, 3, 6, and 7. This dependence was only recently discovered (Coyle1999), and it is not accounted for in Equation 12b.

2.5 PSP Working Equations

The luminescence “intensity” (counts per second) registered by a detectoris proportional to the total emissive flux per unit surface area (from Equa-tion 7):

I (p, T, t) = C∫ d

0epdz= C8TkETτT (p, T)

∫ d

0a(z, t)dz, (13)

where the constant of proportionality (C ) depends on many factors (geometry,basecoat reflectivity, absorption of luminescence within the active layer, detectoroptics and responsivity, etc) and is usually not known precisely. Also, accordingto Equation 1, the absorption per unit volume,a(z, t), is a function of incidentlight intensity and luminophore concentration, either or both of which may dif-fer from point to point on the surface. These undesirable dependencies can beeliminated by forming a ratio of intensities. For radiometric PSP measurements,the ratio is of intensities at known and unknown pressures. For lifetime mea-surements, the ratio is of intensities integrated over different time intervals (seeSection 3.2).

In radiometric PSP measurements, a reference intensity is measured at a knownpressure and temperature:I0 ( p0, T0). Another intensity measurement,I, is madeat unknown pressurep and known (or assumed) temperatureT. If the absorp-tion a is the same in both measurements and the coefficientsA andB have beenpredetermined by calibration, the following equation can then be used to solve

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for p:

I0

I= I (p0, T0)

I (p, T)= τT (p0, T0)

τT (p, T)= A+ B

p

p0

A = kET + kI T (T)

kET + kI T (T0)+ kQT(p0, T0), B = kQT(p0, T)

kET + kI T (T0)+ kQT(p0, T0).

(14)

If T = T0, thenA+ B = 1.This relationship is derived from Equations 4b, 11, and 13 and is referred to as

the Stern-Volmer equation.A andB are called the Stern-Volmer coefficients (to bedistinguished from the Stern-Volmer constant in Equation 8). Experimental datapresented asI0/I vs p/p0 are called a Stern-Volmer plot.

Equation 14 can also be used to determine the unknown pressure from a mea-sured lifetimeτT (p, T ) and a measured reference lifetimeτT ( p0, T0). There are,however, two important differences: (a) It is not required that the excitation (absorp-tion) be the same in both measurements; and (b) the reference lifetime can be pre-determined along with the calibration coefficients, thus eliminating that step fromeach measurement. If the vacuum lifetime is used as the reference (p0 = 0), a suit-able alternative form of Equation 14 can be derived from Equations 4b, 11, and 13.

Equation 14 is adequate over limited pressure ranges; however, over large rangesof pressure the Stern-Volmer plot frequently exhibits enough curvature to neces-sitate the inclusion of nonlinear terms (see Section 4.3). This can be attributedto microheterogeneity of the luminophore environment (the multiple-site model)and/or nonlinear solubility of oxygen in the binder. Microheterogeneity also affectsthe luminescence lifetime (via multiexponential decay), but nonlinear solubilitydoes not. This is a topic of recent and current research (Demas et al 1995, Hartmannet al 1995, Demas & DeGraff 1997, Hubner & Carroll 1997, Gouin & Gouterman2001).

3. MEASUREMENT SYSTEMS

Most PSP systems are intensity-based (radiometric) systems in which the modelis simultaneously illuminated by a diffuse light source (either continuous or flash)and imaged by a camera. The pressure at each point on the model is determinedfrom the ratio of the wind-off to wind-on paint intensities (I0/I ) as recorded bythe camera. This approach requires a calibration of paint intensity vs pressure todetermine the Stern-Volmer constantsA andB in Equation 14. In addition, a se-quence of corrections is required to account for nonideal conditions. Central to thesuccess of these systems has been the availability of scientific-grade CCD camerasfor measuring the paint intensities. With “lifetime” systems, pressure is determinedfrom the decay time of luminescence (Equation 14), which is found by making

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172 BELL ET AL

time-resolved measurements of luminescence, either after the paint has been ex-cited by a flash or as it is continuously illuminated by a modulated light source.Typically, decay times are determined from the ratio of intensities measured duringat least two intervals or gates. An important advantage of this approach is that thisratio is independent of illumination intensity and luminophore concentration, andthus it is unnecessary to normalize the data by measurements acquired at a refer-ence condition. The principal difficulty is simultaneously measuring the intensitytime histories at all points on the model at the timescales of luminescence lifetimes(≤20µs). Global PSP measurements have been made with cameras with extremelyshort shuttering capabilities, and these are briefly summarized below. An alterna-tive to simultaneous imaging is to make measurements sequentially, one point ata time.

The hardware and software required to implement PSP theory are discussed be-low. Emphasis is on intensity-based systems, because these are the most commonlyused and mature systems and the types with which we have the most experience.

3.1 Intensity-Based Systems

3.1.1 Detectors The uncertainty of a PSP measurement depends on how accu-rately the detector can measure small changes in light intensity. This accuracy isultimately limited by the measurement noise. In most PSP measurements there arethree important sources of detector noise: photon shot noise, dark-charge noise,and read noise. These noise contributors are statistically independent, so they addin quadrature (square root of the sum of the squares). In most PSP applications,the overall detector noise is dominated by photon shot noise.

Photon shot noise is the unavoidable statistical variation in signal intensitythat occurs because the number of photons per unit time from a steady sourcevaries according to a Poisson distribution. The resulting uncertainty in intensitymeasured by any detector is equal to the square root of the number of photoelectronscollected (Csorba 1985). Because the signal level itself is simply the number ofphotoelectrons collected, signal-to-noise ratio (SNR) also increases as the squareroot of signal level, so there is always a benefit in collecting more photons.

Dark charge is the accumulation of electrons in a detector that occurs owingto thermal rather than photon excitation. Dark-charge noise refers to statisticalvariations in dark charge that, like shot noise, equal the square root of the darkcharge level. It can be reduced to very low levels (e.g. one detector count, wherea count is the least significant bit of the detector’s analog-to-digital converter) bycooling the detector.

Read noise is introduced by the readout electronics of the detector and, withproper design, can also be minimized. Read noise generally increases with increas-ing read rate, so data transfer from low-noise detectors may also be quite slow.

The SNR, intensity resolution, and linearity required of a PSP detector dependon the desired measurement accuracy (1p = q1Cp, whereq is dynamic pres-sure andCp is pressure coefficient), the minimum (pmin) and maximum (pmax)

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pressures to be measured, and the paint Stern-Volmer constants (A andB in Equa-tion 14). Figures 6 and 7 describe the performance required of a detector if onlya single measurement is made. Referring to Figure 6, the least significant bit ofthe detector’s analog-to-digital converter (i.e. each count) must represent a changein intensity that is no greater than the intensity change (1I ) corresponding to thedesired pressure resolution. Likewise, both noise (assumed to be shot noise) anddetector nonlinearity errors must not exceed1I. Because of the inverse propor-tionality between intensity and pressure, these conditions are most critical (i.e.1I is smallest) where the pressure is highest (pmax) and the image is dimmest.Figure 7 shows the required SNR, number of bits, and allowable nonlinearity asfunctions of Mach number,M, for a representative paint. It assumes that a full-scale reading (Imax = 2# bits) occurs atpmin, and the pressures to be measured arebetween 0 and 1 atm. Detector SNR and intensity resolution (but not linearity) canbe improved by summation of a series of measurements (see Section 4.1).

Scientific-grade CCD cameras (LaBelle & Garvey 1995) are most often usedas PSP detectors. They are nearly ideal light detectors in that they have excellentquantum efficiency (photoelectrons collected per incident photon, up to 85%),shot-noise-limited SNR up to 60 dB, very linear response, and up to 16 bits ofresolution. Typically, the CCDs in these cameras are thermoelectrically cooledand temperature is regulated to within±0.05◦C to reduce dark-charge noise andto stabilize spectral responsivity. Although the spatial resolution of CCD cameras(typically 512× 512 or 1024× 1024 pixels) is much lower than for some othertypes of detectors (e.g. photographic film), it is usually more than adequate forPSP applications. The principal disadvantages of these cameras are their high cost

Figure 6 Relationship between intensity and pressure uncertainties.

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174 BELL ET AL

Figure 7 Required detector perfor-mance. Single realization,pmax = p0 =101.3 kPa;pmin = 0; A = 0.2;B = 0.8.

(∼$20,000) and low imaging rate (required to minimize readout noise, typically0.2–4 frames s−1).

Commercial video cameras were used as detectors in the earliest PSP exper-iments (Kavandi et al 1990, Engler et al 1991, McLachlan et al 1992, Andreevet al 1993, Sellers & Brill 1994). Although their SNR (∼50 dB) and intensity res-olution (typically 8 bits with conventional frame-grabbers) are much lower thanfor scientific cameras, these shortcomings can be overcome by image summation(see Section 4.1). More serious limitations, however, are nonlinear response (Snow

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et al 1993) and, because these cameras are not cooled or thermally stabilized, a largedark current and drift in the CCD response. Film cameras, which have been used inflight-test applications (Fuentes & Abbitt 1996), are inferior to CCD imagery forradiometric measurements in almost every respect except spatial resolution andshould be avoided whenever possible.

3.1.2 Illumination The illumination source should produce uniform illumina-tion at the excitation wavelength of the pressure paint (usually blue or ultraviolet)and must not introduce radiation at the emission wavelength. The illuminationmust be bright enough to produce a luminescence signal that can saturate the de-tector and thus take advantage of the detector’s SNR potential in a reasonableamount of time (several seconds), but not so bright as to saturate luminescence(II> 100 mW cm−2) or cause excessive photodegradation (II > 1 mW cm−2)(Mosharov et al 1997). At atmospheric pressure, luminescence from a PSP-coatedsurface is typically a few percent of the incident illumination (Hand 1999).

Spatial uniformity of the illumination is desirable to avoid locally low SNRwhere the illumination is dim and changes in incident intensity if the model deformsbetween wind-off and wind-on conditions. In addition, the brightness and spectralcontent of the illumination field must be repeatable (flash illumination) or remainconstant in time (steady illumination). These requirements are less severe if thepaint is calibrated “in situ” (see Section 4.3.1), because global changes in incidentlight intensity are absorbed in the calibration coefficients.

Pulsed and continuous-wave (CW) lasers have been widely used in PSP exper-iments (Morris et al 1992, Andreev et al 1993, Lifshitz et al 1993, Engler & Klein1997, Lyonnet et al 1998). The narrow-band emission from a laser can be easilydistinguished from emitted luminescence. In addition, lasers are suitable for usewith fiber optics, which can allow illumination where optical access is limited.Pulsed lasers are especially appropriate for unsteady measurements because thepulse duration can be made extremely short [e.g. 5–10 ns (Bykov et al 1995)]. Cre-ating a uniform illumination field with a laser, however, can be difficult (Morriset al 1993).

Multiple incoherent light sources avoid the safety hazards associated with lasersand provide more uniform illumination. McDonnell Douglas abandoned lasers infavor of multiple incandescent tungsten/halogen lamps (“Bud Lights”) fitted withfilters to pass blue light (Morris et al 1993, Morris & Donovan 1994). Extremelystable lamps composed of arrays of blue (460 nm) light-emitting diodes have beendeveloped and deployed at the Wright-Patterson Laboratory (Dale et al 1999). AtNASA Ames, illumination in large wind tunnels has been provided by up to twenty250-W UV metal halide lamps (McLachlan et al 1992). At AEDC, 300-W xenonlamps with feedback to stabilize output are used.

Flash illumination minimizes photodegradation of the paint and light hazardsto operators. Flash-to-flash variations in spectrum (Possolo & Maier 1998) andenergy output, however, may introduce significant errors. Flash illumination isgenerally necessary in unsteady applications or in tests of rotating machinery.

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176 BELL ET AL

Xenon flash lamps with pulse durations of≥1µs have been used at NASA Amesin tests of helicopter rotor blades and of an oscillating airfoil. Flash illuminationwas similarly applied in tests of a 25% scale model ultrahigh bypass fan at NASAGlenn (Bencic 1997) (see Section 6.3) and of a full-scale rotor (Bosnyakov et al1997, Bykov et al 1998) and propeller (Bykov et al 1995) at TsAGI.

3.1.3 Filtering/Spectral Leakage Filters must be installed in front of the lampsand detectors to minimize contamination of the luminescence signal by light fromthe illumination source. The relative error in a PSP pressure measurement causedby “spectral leakage” is roughly equal to the leakage as a fraction of the lumines-cence signal (Hand 1999). Unwanted radiation from the lamps must be attenuatedby factors of 104–105 and 108–109 to avoid errors caused by diffuse and specularreflections, respectively (Hand 1999). Two types of filters are available: absorp-tion (colored glass or gelatin) and interference filters. Absorption filters allowmuch higher transmission of passed wavelengths and much lower transmission ofblocked wavelengths and can be stacked to fine-tune their attenuation. Interferencefilters can be designed with a much narrower band pass than absorption filters andcan be used in combination with absorption filters, but not with each other.

3.1.4 Coatings Pressure-sensitive coatings should combine desirable photophy-sical and mechanical properties. Important photophysical properties include ab-sorption and emission spectra, pressure and temperature sensitivity, luminescencequantum efficiency, time response, and stability. Mechanical properties includeease of application and removal, curing time, adhesion to the test article, hardnessand damage resistance, thickness, and surface finish.

The performance of a pressure paint depends on the combined characteristicsof the binder and the luminophore. The binder must be permeable to oxygenbut not so permeable that all luminescence is quenched at pressures of interest.The radiative decay rates of the luminophore must be comparable to those ofoxygen quenching over the range of pressures of interest. For most luminescentmolecules, fluorescence occurs too quickly for oxygen quenching to occur, andphosphorescence occurs so slowly that virtually all of it is quenched. Platinumporphyrins and ruthenium complexes in polymer binders possess a combinationof desirable characteristics that make them suitable for aerodynamic testing (Coyle1999).

The first pressure paint used in the West for aerodynamic testing was developedat UW (Kavandi et al 1990). The active layer was PtOEP, suspended in a siliconeresin (Genesee Polymer Corp GP-197), and the base coat was commercial whiteenamel paint (Krylon). This paint is excited by UV light (360 nm) and luminescesat 650 nm. Undesirable characteristics include high temperature sensitivity [−2%to −4% ◦C−1 (Mosharov et al 1997, Woodmansee & Dutton 1998)], rapid pho-todegradation [≥15% decrease in intensity after illumination for 1 h, a function ofillumination intensity (McLachlan & Bell 1995)], and a significant delay beforeluminescent output reaches full strength (induction effect, Uibel et al 1993). UW

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subsequently developed an improved paint in which the active molecule is anotherplatinum porphyrin, PtTFPP, and the binder is FIB (Puklin et al 2000). This paintis also excited by UV light and emits at 650 nm; photodegradation is very low[∼1.5% h−1 (Puklin et al 2000)], and there is no induction effect. Moreover, tem-perature sensitivity is only−0.6%◦C−1 and is nearly independent of pressure [i.e.PtTFPP/FIB is nearly “ideal” (Puklin et al 2000)]. PtTFPP/FIB is commerciallyavailable and is widely used in the United States. Both UW paints dry hard andcan be polished to enhance smoothness.

Paints containing ruthenium complexes (e.g. ruthenium bathophenanthroline)suspended in room-temperature-vulcanizing silicone rubber (e.g. GE RTV 118)were independently developed by TsAGI (Mosharov et al 1997, OPTROD 2000)and McDonnell Douglas and are widely used. Their temperature sensitivities are inthe range−0.3 % to−1.5%◦C−1 (comparable with PtTFPP/FIB) (Liu et al 1997,Mosharov et al 1997, Schanze et al 1997, Woodmansee & Dutton 1998). Siliconebinders, however, are soft and somewhat tacky, so these paints are susceptible tocontamination by handling and dust accumulation and cannot be polished. Surfacefinish, however, tends to be smoother than unpolished FIB (roughness= 0.25µmvs 1.0µm).

Nonpolymer binders have been developed, including thin glass coatings knownas sol-gels (Jordan et al 1999) and anodized aluminum or titanium coatings (Asaiet al 1997). Sol-gel coatings exhibit low temperature sensitivity (∼ −0.8%◦C−1)and can be heavily loaded with luminophore to produce a bright signal. In addition,pressure sensitivity can be tailored by manipulating processing variables. Anodizedaluminum surfaces include micropores into which luminophores have been appliedby electrochemical deposition. These coatings are permeable to oxygen at very lowtemperatures (unlike most polymers) and extremely porous and thus are suitablefor cryogenic and unsteady measurements (see below).

The Stern-Volmer coefficients of the paint (Equation 14) directly affect theaccuracy of the pressure measurement (Oglesby et al 1995b). Large values ofB(high pressure sensitivity) result in large changes in intensity for a given pressurechange, but also reduce the brightness and local SNR of the image where thepressure is highest. If the range of pressures to be measured is very small andthe detector is saturated where the signal is brightest, then high-pressure regionsare not so dim, and the highest possible value for the coefficientBgives the greatestaccuracy for a detector of fixed SNR. As the pressure range increases, the mea-surement accuracy becomes less sensitive to the value ofB: As B increases, gainsin accuracy owing to greater sensitivity are offset by losses owing to decreasingSNR where the image is dimmest. For pressure measurements in the range of0–1 atm, values ofB in the range 0.4–0.8 yield approximately the same accuracy,and the accuracy decreases outside this range.

Self-referencing or binary (biluminophore) paints contain a second luminophorethat is not sensitive to pressure (Oglesby 1995a, Harris & Gouterman 1995, Bykovet al 1998). The luminescence of the second luminophore is proportional to in-cident illumination and concentration of luminophore, so that, in principle, if the

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178 BELL ET AL

distributions of the two luminophores are everywhere proportional, it can be usedto account for variations in these quantities (see Section 4.2.4 below). The secondluminophore should be excited by light of the same frequency as the pressure lu-minophore, but its emission must be at a different wavelength. Care must be takento avoid luminophores that interact with each other. Temperature-compensatedbinary paints are similar to self-referencing paints but use a temperature-sensitivematerial as the second luminophore.

The frequency responses of PSPs are limited by the time required for oxygento diffuse through the binder, not by the lifetimes of luminescence. The responsetime is proportional to the square of the paint thickness and inversely proportionalto the diffusivity of oxygen in the binder (Mosharov et al 1997). Winslow et al(1996) showed that, beyond the cutoff frequency (3-dB attenuation), PSP behavesas a “1/2-order” dynamic system with an asymptotic roll-off of−10 dB decade−1

and a phase shift of−45◦. Most conventional pressure-sensitive paints with poly-mer binders do not have adequate frequency response for unsteady measurements.For example, a 22-µm layer of PtOEP/GP-197 requires∼2.5 s to achieve a 90%response to a step change in pressure (Carroll et al 1996, Baron et al 1993). Betterresponses have been observed from coatings with nonpolymer binders. Baron et al(1993) measured a 90% response in<25µs for a luminophore on a porous sil-ica, thin-layer chromatography plate. Jordan et al (1999) reported response to1 kHz for a 2-µm-thick, ruthenium-complex, sol-gel paint. Anodized coatingsdispense with the binder altogether and allow response times≥80µs (Sakaue et al1999). Dramatic improvements in the frequency response of paints with polymerbinders have been observed when high concentrations of pigment have been added(Ponomarev & Gouterman 1998; Gouin & Gouterman 2000c).

Several studies have shown that adding coatings to wind tunnel models cansignificantly alter the aerodynamics of the model by changing the model shapeand/or roughness (Engler et al 1991, Davies et al 1997b, Lyonnet et al 1998,Schairer et al 1998, Sellers 1998). Acceptable signal levels in large wind tunnelsare usually possible from paint layers as thin as≥12µm (including base coat),and the minimum paint roughness is typically 0.25µm.

3.2 Lifetime Methods

3.2.1 Point Measurement SystemsIn point-measurement systems, a pulsed oramplitude-modulated laser beam is sequentially directed to points of interest on themodel, and the time history of the luminescence signal from the paint is analyzed todetermine local pressure. In a particularly successful system at British Aerospace(Davies et al 1997a), illumination is provided by a pulsed laser, and the signal de-cay is measured by a set of boxcar integrators of known gate widths. Temperatureand pressure are simultaneously determined using a proprietary analysis method,thus allowing temperature compensation of the pressure measurements. Scanningsystems have also been developed in which a modulated CW laser instead of apulsed laser illuminates the model (Guille et al 1999). The resulting luminescence

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is modulated at the same frequency as the laser, but the phase is shifted andthe modulation relative amplitude is attenuated as pressure decreases and the life-time of the luminescence increases. The phase shift, which is a function of thelifetime and modulation frequency, is measured by a lock-in amplifier. An advan-tage of laser scanning systems is that they can be used to make both point-wiseradiometric (Hamner et al 1994) and lifetime measurements.

3.2.2 Imaging Systems Lifetime imaging systems require cameras with inte-gration times a thousand or more times shorter than can be achieved with themechanical shutters typically found on scientific CCD cameras. For example, inpulsed (flash) systems, photons must be collected during at least two intervals(gates) as luminescence decays (typically,≤20µs). Figure 8 shows how the ratioof images acquired during two equal gates can be used to determine the decay rate.Exposures of≥5 ns can be made with an intensified CCD camera by controllingthe voltage applied to the intensifier (Holst 1998). The intensifier, however, dras-tically reduces the SNR. Lifetime measurements using an intensified CCD havebeen made at AEDC (ME Sellers & L Goss, manuscript in preparation; see Section6.7 below) and at Deutsche Forschungsanstalt fur Luft-und Raumfahrt e.V. withOPTROD’s L4 paint and an integration time of 150 ns (Engler & Klein 1997).Dale et al (1997) used a prototype fast-framing CCD camera to make lifetimemeasurements on a falling body illuminated by a pulsed laser. The lifetime of theluminescence was determined from 11 sequential 8-µs images acquired after thelaser pulse. In another approach, a model was illuminated by light-emitting diodesmodulated at 150 kHz, and images were acquired by a “phase-sensitive” cameraduring two gated intervals, one in phase and the other out of phase with the lights(Holmes 1998).

Figure 8 Determining lu-minescence lifetime fromtwo time-resolved images.

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180 BELL ET AL

4. DATA REDUCTION

PSP data reduction transforms intensity data in the image plane to pressure datamapped to spatial coordinates of the model. This is a multistep process that usuallyincludes (a) calibrating the paint and converting image intensities to pressure,(b) applying corrections for nonideal, real-world effects, and (c) determining andapplying a transformation from image to model coordinates. Some corrections (e.g.“self-illumination,” see below) must be applied after the data have been mappedto the model grid.

4.1 Image Summation

When the standard deviation of the noise is greater than one least significant bit(as is usually the case in PSP measurements), summation ofN images increasesthe effective detector electron well capacity and SNR by factors ofN and

√N,

respectively, and increases intensity resolution by log2N bits. Image summation iscommonly used to reduce uncertainty in low-speed testing at the cost of increaseddata acquisition time.

4.2 Corrections

4.2.1 Tare Correction A tare image is generally subtracted from the data imagesto eliminate the effects of the camera readout bias (caused by incomplete drainageof charge from the CCD and amplifier offset), dark charge, and ambient light.The integration time of the tare image should be the same as that of the dataimages. Usually, the tare image is a “dark” image acquired with the shutter closedand includes bias and dark charge. If there is significant ambient light in thetest environment at the wavelength of the signal, however, the tare image shouldbe acquired with the shutter open and the excitation illumination turned off. Intypical applications with cooled, 14-bit CCD cameras, readout bias may be 300–500 counts and dark charge≤20 counts. Uncertainty owing to dark-charge noise istypically one count or less—so low that there is little benefit in averaging multipletare images.

4.2.2 Flat-Field Correction The flat-field correction accounts for differences inresponses of elements of a CCD array (≤6% for scientific cameras) and for the factthat lenses deposit more light near the center of an image than near the edges. Thecorrection is necessary except in the unlikely event that the model does not moveor deform between wind-off and wind-on conditions. At high signal levels, flat-field errors surpass shot noise as the most important source of image uncertainty(Mendoza 1997b). This error is corrected by normalizing each tare-corrected dataimage with a flat-field image of a uniformly illuminated scene (also corrected fortare). Flat-field images can be acquired by imaging the inside of an “integratingsphere” or, more simply, by imaging almost any scene through several sheets ofdiffusing “opal” glass. However, applying a flat-field correction to a data imageincreases overall shot noise by the factor

√1+ (1/m), wherem is the ratio of

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the number of summed flat-field images to the number of summed data images(Mendoza 1997b). Therefore, to reduce the shot noise of a flat-field–correctedimage to within 10% of the shot noise of the uncorrected image, five times asmany flat-field images must be summed as data images.

4.2.3 Image Registration and Ratioing Forming the ratio of each wind-on im-age by a wind-off image,I/I0 eliminates variations in signal intensity caused byvariations in paint thickness and excitation light intensity across the surface ofthe model. It is critical that the wind-on intensity at each point on the model benormalized by the wind-off intensity at the same point. Because models deformunder air loads, the wind-on image (corrected for tare and flat-field errors) mustbe registered or transformed so that when the images are laid over each other, thecorresponding physical points of the model are in alignment.

It is common to rely on a single global transformation between wind-off(x′, y′) and wind-on (x, y) coordinates. Two examples are the projective transform,which is valid strictly for solid-body movement of a two-dimensional object, andpolynomial transformations, which can account for any combination of modelmovement and deformation as long as the series is carried out to sufficiently highorder (Bell & McLachlan 1996):

Projective,

x = a1x′ + a2y′ + a3

c1x′ + c2y′ + 1, (15a)

y = b1x′ + b2y′ + b3

c1x′ + c2y′ + 1. (15b)

Polynomial,

x = a00+ a10x′ + a11y′ + a20x

′2+ a21y′2+ a23x′y′ + · · · , (16a)

y = b00+ b10x′ + b11y′ + b20x

′2+ b21y′2+ b23x′y′ + · · · . (16b)

The usual way to determine the coefficients is to measure, in both images, theimage coordinates (x, y) and (x′, y′) of small (3- to 5-pixels–diameter), easilyidentifiable targets distributed over the surface of the model. At least four targets arerequired to solve for the eight coefficients of the projective transform. A first-orderpolynomial transformation in both directions requires only three targets, whereasa second- and third-order transformations require 6 and 10 targets, respectively. Ifthere are more targets than required for a particular transformation (as is usuallythe case), the resulting overdetermined system of equations can be solved in aleast-squares sense for the unknown coefficients. Once the coefficients are known,they can be used to compute a new location for each wind-off pixel. These newlocations are used to transform the wind-on image; the intensity of each pixel inthe transformed image is the wind-on intensity at the position of the displacedwind-off pixel.

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Other registration methods use only local information. For example, in a methoddeveloped by Shanmugasundaram & Samareh-Abolhassani (1995), the coordi-nates of all points in each image are parametrically defined in terms of ver-tices of triangles defined by the Delaunay triangulation (Devereux et al 1990).Finally, an automated method has been developed whereby fine-grain structurewithin the images is used instead of targets to establish registration (Weaver et al1999).

The required registration accuracy depends on the magnitude of brightnessgradients in the images caused by pressure gradients and/or paint inhomogeneityand the desired accuracy of the pressure measurement (Bell & McLachlan 1996).For the same level of measurement accuracy, the required registration accuracyincreases with decreasing dynamic pressure. Fortunately, however, model dis-placement and thus the registration error also decrease with decreasing dynamicpressure. In most cases, registration errors should be<0.5 pixel. If the modelmoves as a rigid body, then the projective transform defined by at least 10 targetsis usually adequate; if the model movement is nonlinear, as with a semispan wing,a third-order polynomial transform based on at least 15 targets should be used(Bell & McLachlan 1996).

Reliably identifying targets in images is the principal bottleneck in automatedPSP data reduction. Many fast and automatic algorithms are available for locatingtargets and establishing the correspondence of targets in wind-off and wind-onimages (Le Sant et al 1997). Few algorithms, however, are robust enough to besuccessful>90% of the time, and an error in locating a single target can have aglobal effect on the transformed image.

4.2.4 Illumination Compensation Illumination compensation is desirable tocorrect for differences in model illumination between wind-off and wind-on condi-tions (Bell & McLachlan 1996). In the earliest attempts at illumination compensa-tion, small patches of pressure-insensitive reference luminophore were distributedover the surface of the model, and changes in the intensity of the patches wereused to estimate changes in the incident light field between wind-off and wind-onconditions (Bykov et al 1993, Morris et al 1993, OPTROD 1996). Another methodinvolved directly measuring the illumination intensity field and applying correc-tions based on measurements of the model’s position (OPTROD 1996, Schairer &Hand 1997).

To date, self-referencing binary pressure paints have been the most successfulapproach to illumination compensation. Each image acquired at the wavelengthof the pressure-sensitive luminophore (Ip) is normalized by a reference imageacquired at the wavelength of the pressure-insensitive luminophore (Ir). This cor-rectsIp for variations in both illumination intensity and luminophore concentrationand, in principle, eliminates the need for wind-off pressure images (I0)p. There-fore, additional benefits of self-referencing paints include shorter data acquisitiontimes, becauseIp andIr can be acquired simultaneously, and smaller registrationerrors, because the model position is the same forIp andIr. Also, self-referencing

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paints could minimize temperature errors if the temperature responses of the twoluminophores offset each other.

The full benefits of self-referencing pressure paints have yet to be realizedbecause of the difficulty in finding suitable reference luminophores. Referenceluminophores developed to date have been crystalline rather than molecular andthus have not been soluble in the paint binder (Harris & Gouterman 1995, Fonovet al 1999). This causes significant differences in the spatial distribution of thereference luminophore compared with the pressure luminophore once the painthas been sprayed. In addition, the ratioIp/Ir has shown a dependence on paintthickness owing to radiative energy transfer between the luminophores (Harris &Gouterman 1998). These undesirable effects can be eliminated by normalizingboth Ip and Ir with corresponding wind-off images and forming the “ratio-of-ratios” (I0/I )p/(I0/I )r (McLean 1998). The ratio-of-ratios is fully compensatedfor spatial and temporal variations in incident light intensity but, because wind-offimages are required, lacks important advantages of a perfect self-referencing paint.Furthermore, because of the larger number of images required, forming the ratio-of-ratios increases the overall uncertainty in much the same way that applyinga flat-field correction does. Finally, this procedure requires two stages of imageregistration: (a) registration of both wind-on images to corresponding wind-offimages; and (b) registration of reference images to pressure images. An alternativeto the second stage is to form the ratio of pressure and reference intensities inmodel, rather than image, coordinates.

4.2.5 Temperature CompensationTemperature compensation depends on thepaint calibration technique (see Section 4.3 below). With in situ calibration, tem-perature effects are absorbed in the calibration coefficients, and spatial variationsin temperature are averaged out among all points included in the calibration. Itis important that both wind-off and wind-on images be acquired after the modeltemperature has stabilized (Brown et al 1998, Brown 2000). If the temperatures ofdifferent parts of the model are significantly different, then separate, local calibra-tions can be computed on the various parts as long as pressure taps are available.A priori calibration allows complete pixel-by-pixel temperature compensation be-cause the relationship between intensity, temperature, and pressure is predeter-mined from measurements in a calibration chamber. The temperature distributionon the model, however, must be either measured [e.g. with temperature-sensitivepaint (TSP) (Bencic 1997, Asai 1999)] or estimated [e.g. by satisfying the uniquerelationship between pressure and recovery temperature on an adiabatic flat plate(Bykov et al 1993, Lyonnet et al 1998)]. Finally, the “k-fit” method of paint cali-bration uses a single parameter to account for differences in temperature betweenwind-off and wind-on conditions.

4.2.6 Freqency Response CompensationFrequency response compensation isrequired in unsteady applications where inadequate paint frequency responsecauses attenuation and phase shift of the unsteady component of the PSP

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184 BELL ET AL

signal. Mosharov et al (1997) have determined amplitude and phase correctionsthat are functions of frequency and paint thickness, diffusivity, and optical density(see also Fonov et al 1998).

4.2.7 Self-Illumination Corrections Self-illumination refers to luminescencethat is reflected between two or more painted surfaces, thus increasing the bright-nesses of the reflecting surfaces. It is most likely to occur on complex models withsurfaces at right or acute angles to each other (e.g. wing/body junctures, empen-nage) and can offset pressure measurements by as much as 10%. The pressureerror is usually small if the pressures on the affected surfaces are nearly uniform(Ruyten 1997c). Ruyten (1997a,b) has developed an analytic correction methodthat assumes diffuse reflections from all painted surfaces. It requires determina-tion of influence coefficients among elements of a surface grid on the model andmeasurement of surface reflection coefficients at the luminescence wavelength.More accurate methods account for directional reflections but require significantlymore calibration and computational effort (Ruyten 1997b,c; Merienne & Le Sant1999). Wind-off and wind-on images must be mapped to the model geometry(see Section 4.4 below) before self-illumination corrections are applied.

4.3 Calibration

Paint calibration involves using independent pressure and temperature measure-ments to establish the relationship between image intensity ratio, pressure, andtemperature. This can be done either in situ, using data from pressure taps in themodel, or a priori, whereby the intensity of a painted “coupon” in a calibrationchamber is measured over an appropriate range of temperatures and pressures.If the model is tested in a pressurized wind tunnel, the wind tunnel itself cansometimes serve as the calibration chamber, although in most tunnels indepen-dent control of wind-off temperature is not available (Bykov et al 1993). Hybridmethods that combine the two approaches have also been developed.

4.3.1 In Situ Calibration With in situ calibrations, the pressure measured byeach pressure tap in the model is correlated to the PSP intensity ratio measuredat or near each tap location. Generally, pressure is represented as a polynomialfunction of intensity ratio,p = c0 + c1 · I0/I + c2 · (I0/I )2 + · · · , and a least-squares fit of the data establishes the calibration coefficients. There is no explicittemperature dependence; temperature effects are absorbed in the coefficients. Thestandard deviation of the data from the best-fit curve is a measure of the accuracyof the PSP calibration. In many applications, a simple linear fit is adequate, whichleads toA = −c0/c1 andB = p0/c1 (A, B,andp0 are from Equation 14).

A necessary step for in situ calibration is determining the PSP intensity ratios atthe pressure taps. Pressure taps are often too small to be seen in the images. Con-sequently, photogrammetry (see Section 4.4 below) is commonly used to computethe image coordinates of the taps based on their known spatial coordinates.

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Figure 9 shows an in situ calibration of PtTFPP/FIB on a semispan wing testedin the High Reynolds Number Channel 2 at NASA Ames. Test conditions wereM = 0.8, angle of attack (α) = 2.75◦, total pressure (pt) = 689 kPa, and total tem-perature= −6◦C. Wind-on data were acquired at atmospheric conditions beforethe run.

4.3.2 A Priori Calibration The intensity of a painted coupon is measured as afunction of pressure and temperature in a calibration chamber. Incident light in-tensity should be monitored and the data corrected if necessary. It is also importantthat the temperature measured is that of the paint, which may differ from the tem-perature of the coupon substrate and/or the surrounding air if sufficient time is notallowed for temperatures to equalize.

It is convenient to express the measured pressure in the calibration chamber as abiquadratic function of measured intensity ratio and paint temperature (Mosharovet al 1997):

p = a00+ a01 · Ire f /I + a02 · (Ire f /I )2

+ a10T + a11 · T · Ire f /I + a12 · T · (Ire f /I )2

+ a20T2+ a21 · T2 · Ire f /I + a22 · T2 · (Ire f /I )2,

(17)

whereIref is the coupon intensity at arbitrary reference condition (pref, Tref). For afull biquadratic representation, the coupon intensity must be measured at nine ormore combinations of temperature and pressure to solve for the nine coefficients.

Figure 9 In situ calibration of platinum tetra(pentafluorophenyl)porphyrin in fluoroacrylicpolymer binder (PtTFPP/FIB) on a semispan model in NASA Ames Research Center HighReynolds Number Channel 2.

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186 BELL ET AL

If the reference condition (pref, Tref) is the same as the wind-off condition (p0,T0), thenIref/I becomes I0/I, and Equation 17 can be used to computep directlyfrom measuredI0/I and measured (or assumed)T. When the calibration referencecondition differs from the wind-off condition, measured intensity ratios on themodel,I0/I, must be adjusted by the factorIref/I0 before Equation 17 can be usedto determine model pressures. The intensity ratioIref /I0 is found by substitutingp0 andT0 for p andT in Equation 17 and solving the resulting quadratic equationfor Iref /I0.

The procedure is the same for intensity-compensated binary paint, except thatIref in Equation 17 refers to the intensity of the reference luminophore (for idealbinary paint). On the other hand, if ratio-of-ratios is used,Iref/I is replaced by(Iref/I )p /(Iref/I )r, where the subscriptsp andr refer to the pressure and referenceluminophores, respectively.

Figure 10 shows an a priori biquadratic calibration of an experimental OPTRODpressure paint used in tests at NASA Ames. Note thatIref/I increases (i.e.Idecreases) with increasing temperature, as predicted by Equation 12b.

4.3.3 Hybrid Techniques The k-fit method, developed by MJ Morris (Wood-mansee & Dutton 1998), is a hybrid between in situ and a priori calibrations.Pressure sensitivity of the paint at a single temperature is determined a priori ina calibration chamber and is expressed as a second-order polynomial inI0/I. Afactor,K, accounts for differences in temperature between wind-off and wind-on

Figure 10 A priori calibration of OPTROD paint used at NASA Ames Research Center( pref = 101.3 kPa;Tref = 20◦C).

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conditions and is adjusted in situ to provide a best fit of the pressure-tap data:

p/po = C1+ C2

(K · I0

I

)+ C3

(K · I0

I

)2

. (18)

This method is particularly useful with ideal paints in situations where the rangeof pressures measured by pressure taps does not span the range encountered bythe paint.

4.4 Resectioning

A transformation is required between the image-plane (x, y) and model (X, Y, Z )coordinate systems to allow extraction of PSP data from the images at physicalpoints of interest on the model, for example intensity ratios at pressure taps for insitu calibration or pressure coefficients at nodes of a computational fluid dynamicsgrid. Most transformations are based on central projection: Light from the modelpasses through an optical center and is projected onto the image plane. This leads tothe colinearity equations of photogrammetry, which include parameters describingthe internal (principal distance,c, and principal point,xp, yp) and external (positionXc, Yc, Zc and rotation anglesω,φ, κ) orientations of the camera (Marzan & Karara1976):

x − xp +1x = −cm11(X − Xc)+m12(Y − Yc)+m13(Z − Zc)

m31(X − Xc)+m32(Y − Yc)+m33(Z − Zc),

y− yp +1y = −cm21(X − Xc)+m22(Y − Yc)+m23(Z − Zc)

m31(X − Xc)+m32(Y − Yc)+m33(Z − Zc),

(19)

wheremij are elements of the rotation matrix and are trigonometric functions ofthe rotation angles. Corrections1x and1y may be applied to account for real-world deviations from this simple model. All methods require that the camera becalibrated, typically by imaging an object with targets whose spatial coordinatesare known. This object may be the model itself, or it may be a special calibrationobject (Donovan et al 1993, Schairer & Hand 1997). In general, more complexmethods require more extensive camera calibration.

Direct linear transformation (DLT) is a particularly simple reformulation of thecolinearity equations (Abdel-Aziz & Karara 1971):

x +1x = − L1X + L2Y + L3Z + L4

L9X + L10Y + L11Z + 1,

y+1y = − L5X + L6Y + L7Z + L8

L9X + L10Y + L11Z + 1.

(20)

1xand1yare corrections that, in the simplest implementation, may be set to zero.The 11 coefficients,L1–11, are various groupings of the external and internal orien-tation parameters, and they are generally found by imaging at least six noncoplanartargets whose spatial coordinates are known. The resulting overdetermined set of

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188 BELL ET AL

12 or more equations is linear in the unknown coefficients,L1–11, and thus canbe directly solved in a least-squares sense. For high-quality lenses of normal orlonger focal length, the DLT method can yield image coordinates to an accuracy of0.01% of the image size (0.1 pixels of a 1024× 1024 image) and requires no initialguess or information about the camera position or internal configuration. Accuracycan be improved by including corrections1x and1y to account for lens distor-tions, which increase with the use of wider-angle lenses. A single cubic term isoften sufficient to account for the dominant, symmetrical lens distortion (Karara &Abdel-Aziz 1974). With this enhancement, the equations become nonlinear, butthey can be solved iteratively.

A more complex solution of the colinearity equations uses separate, coupledsolutions for the internal and external orientations (Liu et al 1999b). Internal ori-entation parameters are sought that are most nearly invariant over the range ofcalibration targets; external parameters are found by successive approximations ofa least-squares problem much as for the nonlinear DLT method. This method allowsorientation parameters, including parameters for lens distortion, to be determinedfrom a single image and, like the DLT method, does not require an initial guess.Other nonlinear methods include those of Donovan et al (1993) and Le Sant &Merienne (1995).

Once image-plane data have been mapped onto the model geometry, “virtual”images (i.e. views from camera vantage points different from those actually usedto acquire data) may be created (Le Sant & Merienne 1995). Values are assumedfor external and internal orientations of a virtual camera, and these values are usedto map data from the model geometry to pixels in the virtual image.

4.5 Software Packages

As PSP technology has matured and been applied in production wind tunnels,standardized software with easy-to-use graphical user interfaces has evolved thatallows automatic analysis of the many hundreds of images that may be acquiredduring a typical test. In the United States, the most widely used software of thistype is Green Boot (The Boeing Company 1997), developed jointly by McDonnellDouglas, NASA Ames, and Sterling Software. Green Boot uses database meth-ods that allow simultaneous access to all images, geometry data, and other con-figuration inputs for an entire test sequence. It also features a powerful macrolanguage with logical flow control commands. Green Boot is designed to operateunder Unix/X-11 family operating systems and runs most efficiently on scientificworkstations.

TsAGI markets a comprehensive PSP software package known as OMS. Thisapplication, which runs on personal computers under Windows 95/NT, enablesnear-real-time analysis of single-luminophore and binary-paint data and has manyconvenient data analysis and data viewing options, including data animation (Fonov1999). ONERA has developed a similar software package, AFIX2, that also runsunder Windows 95/NT (Merienne & Le Sant 1999).

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5. MEASUREMENT UNCERTAINTY

Sources of uncertainty fall into three groups (Bykov et al 1993): Group 1 includesuncertainties in characterizing the response of the paint (e.g. calibration errors),group 2 includes uncertainties introduced by the measurement system (e.g. detectoruncertainties, spatial and temporal variations in illumination, and spectral leakage),and group 3 includes uncertainties in signal analysis (e.g. incomplete compensationfor errors and resectioning errors).

Paint calibration errors (group 1) occur because mathematical representationsof PSP response are not exact. Examples of uncertainties for in situ (1p/pt =0.012) and a priori (1p = 0.148 kPa) calibrations are shown in Figures 9 and10, respectively. With in situ calibration, the calibration uncertainty is a measureof the overall PSP uncertainty within the range of conditions at the pressure tapsand assumes that the pressure-tap data are exact. Effects that are not explicitlyaccounted for (e.g. temperature and illumination changes, registration errors, etc)create scatter in the calibration, but not a bias offset. If the pressure taps do not spanthe full range of pressures on the model, the calibration must be extrapolated, andthe actual uncertainty will likely exceed the calibration uncertainty. Extrapolationuncertainty is minimized if the temperature sensitivity of the paint is independentof pressure, that is, if the paint is ideal. In our experience, in situ calibrationuncertainties in transonic tests are typically∼1% ofpt. Brown et al (1998) showedthat in situ calibration uncertainty for very low-speed flows could be reduced to0.04% ofpt when images were summed to increase SNR and special care wastaken to minimize relative model motion and temperature and illumination errors(see Section 6.2).

With a priori calibration, the calibration error represents a minimum uncertaintyover the range of calibration temperatures and pressures and does not includeother sources of error. Neglected effects (e.g. photodegradation, humidity, andcontamination) can introduce a bias error because the response of the paint on themodel will, in general, be slightly different from that of the calibration coupon.In addition, to achieve the uncertainty shown in Figure 10, the model temperaturedistribution must be known [which is rarely the case (see group 3 errors below)],and other errors (e.g. flat-field and registration) must be corrected.

The principal contributor to uncertainty in group 2, detector shot noise, isunavoidable, and it represents the minimum measurement uncertainty. As longas the flat-field error is adequately corrected (Mendoza 1997b), however, shotnoise can be reduced by summing many images (N ) (SNR ∝ √N). 1Cp for agiven shot noise-limited SNR can be computed from the equation in Figure 7a.Figure 11 shows1Cp vsM for a typical paint at atmospheric conditions and SNRscorresponding to video (single-frame= 50 dB) and scientific CCD cameras (sin-gle frame= 60 dB; 16 frames= 72 dB). Forming the ratio of two images, asrequired for both radiometric and lifetime methods, decreases overall SNR by√

2. Figure 11 is consistent with the nearly1/M2 behavior of1Cp described byMendoza (1997a) and is similar to error estimates presented by Liu et al (1999a)

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190 BELL ET AL

Figure 11 Uncertainty in pressure coefficient caused by detector shot noise, wherepmax= p0 = 101.3 kPa;pmin = 0; A = 0.2;B = 0.8.

for a ruthenium paint. In other error analyses, Sajben (1993) showed that1Cp is≥10-fold as large as1I/IVAC at stagnation conditions, where SNR is lowest, andincreases dramatically asM decreases from an optimum atM = √2. Mosharovet al (1997) approximate1p/p = √2/(SNR· B) for cases in which the pressuremeasurement range is small.

The illumination source introduces uncertainty owing to spatial and temporalvariations in intensity (which, in principle, can be corrected—see Section 4.2.4)and temporal variations in spectrum. Bell & McLachlan (1996) estimated that for asingle-point-source illuminator, a 0.5% change in distance between the model andthe illuminator changes the relative illumination of two widely separated points onthe model by 0.1%. Maintaining lamp stability within 1% requires special attentionto the lamp design. For example, the output of the stock metal halide lamps used atNASA Ames varies by as much as 1%–2% in the first hour. Sajben (1993) estimatedthat illumination uncertainty of 0.5% accounts for 3.4% of the overall pressureuncertainty with an early McDonnell Douglas paint (sources of uncertainty wererestricted to illumination and luminescent intensities, temperature, and referencepressure; the assumed uncertainty of each was 0.5%). Possolo & Maier (1998)estimated that the spectral variability of xenon flash lamps created a pressureuncertainty of1Cp = 0.01 in transonic tests at Boeing.

Failure to fully compensate for temperature effects (group 3) is by far the largestsource of uncertainty in PSP measurements. This failure is usually caused by un-certainty in the paint’s temperature, not its temperature response (which may beknown from calibration). Assuming no heat transfer, spatial variations in surface

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December 1, 2000 9:20 Annual Reviews AR117-06


temperatures of models in transonic flow can be as large as 10◦C. According toSajben’s (1993) analysis, a temperature uncertainty of 1.5◦C (= 0.5% of 300 K)accounted for 93% of the pressure uncertainty. Surface temperatures can be mea-sured by temperature-sensitive paint to an accuracy of 0.2◦–0.8◦C (Liu et al1999b). Other group 3 uncertainties (dark-charge noise, flat-field, registration,self-illumination, resectioning, etc) can by reduced to levels far below those of themain contributors by the methods described in Section 4.

6. SAMPLE RESULTS AND DISCUSSION

This section presents and discusses results from PSP tests conducted under a widevariety of conditions by researchers both within and outside of NASA. The samplesbegin with a simple test using the classical intensity-based method, followed byapplications under more unusual conditions. Next, some results with mapped PSPdata are shown, and, finally, examples of lifetime and biluminophore methods arepresented and discussed.

6.1 Intensity-Based PSP Measurements

In a typical application of the intensity-based technique, wind-off (Figure 12a) andwind-on (Figure 12b) PSP images were taken during a test of a high-speed civiltransport (HSCT) model in the NASA Ames 7×10-ft wind tunnel. The model wasmounted with wings vertical in the test section, illuminated from both sides with250-W UV lamps, and viewed (again from both sides) with Roper Scientific (for-merly Princeton Instruments) TEA/CCD-1024TKB cameras. The wind-on imagewas taken at a dynamic pressure ofq = 5.5 kPa, corresponding to a flow speed of96 m s−1, orM = 0.28. This tunnel is unpressurized, so total pressure (pt ) is fixedat 1 atm. To increase SNR, the images were formed by summing 16 individualexposures of 4.5 s each. Round black targets, applied to the wing for image regis-tration, can be seen easily in both images. However, there is little visible differencebetween the two images. Brightness changes caused by variations in illuminationintensity across the model are far greater than those caused by pressure changesbetween the wind-on and wind-off conditions.

These data were reduced by the methods described in Section 4. Theflat-field image, shown in Figure 13, is the sum of 256 exposures. It is domi-nated by the effect of the lens, which deposits most light at the center of thefocal plane. Image registration was performed using a third-order polynomial inbothx andy (Equation 16). The ratio of wind-off to wind-on images is shown inFigure 14. Pixel intensities in this image are linearly proportional to pressure, inagreement with Equation 14. In this case the image is false colored, so that bluerepresents regions of relatively low pressure, and red represents relatively highpressure. The ratioed image was calibrated in situ (Section 4.3) by reference to 20pressure taps installed on the model. The image shows that the pressure distribution

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192 BELL ET AL

Figure 12 Raw images of a high-speed civil transport model with (a) wind off and(b) wind on. Flow temperature is 33◦C; α = 12◦.

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Figure 13 Flat-field image used forthe high-speed civil transport modeltest.

is dominated by suction caused by the leading-edge vortices, which have not burstat this relatively low angle of attack (α = 12◦).

The raw and ratioed data are compared in more detail in Figure 15, which showspixel data along a chordwise line drawn on the image at roughly three fourthssemispan (i.e. about midway along the outer panel of the wing). Both the wind-onand wind-off data show the same general trend in brightness, except for an offsetcaused by the lower mean pressure in the wind-on image. It is only when thesedata are ratioed, however, that the pressure distribution emerges. To demonstratethe effect of flat-field correction, Figure 15 shows the ratioed data derived bothwith and without flat-fielding. Flat-fielding notably improves the smoothness of

Figure 15 Chordwise line cut showing raw data and ratioed values with and withoutflat-fielding.

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194 BELL ET AL

the data. One significant error in the ratioed values can be seen at the trailing edge,where there is a sudden change in the ratioed data. This occurs because raw paintbrightness levels drop significantly in the trailing-edge region (see Figure 12).Therefore, small errors in measuring paint brightness or in registering the wind-onimage to match the wind-off image can have a large effect on the final ratioedresult. In practice, the raw images are usually thresholded to remove dim pixelsfrom which inaccurate ratioed data might result.

An image resection transform (Section 4.4) was computed from the knownlocations of the 19 targets visible on the model, using Equation 19. The imagedata were projected onto a model surface grid of∼30,000 grid points (Figure 16).A coarse mesh is drawn over the surface data to show the parts of the modelcovered by the mapped image. Note that the lower wing root and aft fuselage arenot colored, because no data from Figure 14 map to those parts of the model. Thefinal step in the PSP data reduction is to map data from the three other cameraswith overlapping views; a total of four cameras were used in this test to obtaincomplete coverage of the model.

6.2 Measurements at Very Low Flow Speeds

Low-speed (M < 0.1) PSP measurements can be quite difficult, owing to the highSNR required. When care is taken, however, reasonably accurate PSP measure-ments can be made even at very low flow speeds. Figure 17 (from Brown 2000)shows the flow over the upper surface of an NACA 0012 airfoil atα = 5◦, freestream velocity,U = 20 m s−1 (thusq = 0.24 kPa, a small fraction ofpref =101.3 kPa= 1 bar). In this false-colored image, the low-pressure suction regionnear the leading edge of the airfoil is shown in blue. Pressure values were obtainedby means of an in situ calibration to a linear fitting function, based on 16 pressuretaps located along the wing centerline. The error in the fit is 0.16 inCp units or16% ofq. The 23-cm–span airfoil did not fully span the 30.5-cm test section widthof the small tunnel in which it was tested. Thus, flow around the tips of the model,which leads to the formation of the wing-tip vortices, produces the edge effectsthat can be seen in the image.

To produce these results, special care was taken to minimize model motion andtemperature changes between the wind-off and wind-on conditions. To minimizerelative motion, the model, camera, and lamps were all firmly bolted to the windtunnel structure. Bright illumination was used to reduce exposure time, because16 exposures were summed to reach acceptable SNR in each image. The tunnelwas run for 60 min before wind-on images were taken to allow it to reach anequilibrium temperature. The tunnel was then stopped, and the wind-off imageswere taken immediately to minimize the model temperature change. Clearly, shortimage acquisition times are desirable to minimize tunnel temperature drift, butthe requirement for high SNR argues for large photon collection and thus longacquisition times. This trade-off is discussed in more detail by Brown (2000).

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6.3 Measurements on Rotating Models

The application of PSP to rotors and turbomachinery is of interest because the useof conventional pressure sensors on rotating parts requires complex systems forpassing data through a slip ring. Figure 18 (from Bencic 1997) shows the pressuredistribution on the suction surface of the same fan blade at three different mass-flow rates. The blade model was illuminated with a xenon flash system that wasfast enough to freeze the rotation of the blade, which was maintained at a tip speedof 235 m s−1. Individual flashes were not bright enough to produce a sufficientlyhigh SNR, so the camera shutter was left open and the blade was flashed repeatedlyas it came into position, building up a phase-averaged image on the CCD. The PSPdata were corrected for temperature sensitivity by using an image of TSP appliedto another blade. The individual pictures in Figure 18 show mass flow increasingfrom left to right. At the lower mass flows (closer to stall), the tip trailing edgeindicates a separated area that was predicted by computations.

6.4 Measurements on Icing Models

A particular advantage of PSP is its ability to obtain measurements that werepreviously considered impossible. One example is the measurement of surfacepressures on models in an icing tunnel, which simulates flight through icingconditions. Because the aerodynamic surface of interest is defined by the irregu-lar ice shape, which grows on the model during the test, pressure measurementscannot be made with conventional techniques. Figures 19–21 (from Bencic 2000)show how PSP can be used in this situation. First, the tunnel was run wet togrow an ice shape on the surface of a GLC 305 airfoil model. Then the tunnelwas stopped, and a special PSP formulation was applied to the ice surface, asshown in Figure 19. As part of this process, a slot was cut through the ice shapeso that its cross-section could be traced, as shown in Figure 20. The cross sectionreveals the ice shape to be highly irregular and grossly different from an efficient

Figure 20 Cross section through leading edge of iced airfoil, obtained by tracing iceshape removed from slot seen in Figure 19. Ice is shown inblack(from Bencic 2000, withpermission).

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aerodynamic shape. After the paint was applied, the tunnel was run under dry, coldconditions, and data were obtained using a conventional wind-off/wind-on ratioapproach. A sample reduced image is shown in Figure 21 for the conditionsα =3.6◦, U = 103 m s−1, andpt = 1 atm (and thusq = 6.3 kPa). The image shows adeep, low-pressure trough behind the ice “horn” (Figure 20) where a reverse-flowbubble occurs.

6.5 Interpretation of Mapped PSP Data

Once mapped, it is useful to integrate PSP-derived pressure data to obtain forceand moment measurements on the model. A simple method is to regard the modelsurface grid as a collection of flat panels whose corners are the grid points (Bell1999). The pressure on any panel is evaluated by taking the mean of the pres-sures at its corner points, and the force on a panel is simply the product ofpressure and panel area. An example of this technique is shown in Figures 22and 23. Figure 22 shows calibrated PSP data mapped onto a surface grid for awing-body model tested in the NASA Ames 11-ft transonic wind tunnel. PSPwas applied to the model, and data were obtained with two cameras, imagingboth the upper and lower wing surfaces. PSP and balance data were obtained at

Figure 23 Comparison of pressure-sensitive paint- and balance-derivedforces on a transonic wing model,(a) normal forces, (b) axial forces.

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M = 0.84 for a range of angles of attack (−8◦ ≤ α ≤ 8◦). The results show thenormal (Figure 23a) and axial (Figure 23b) force coefficients obtained from thepressure integration, as well as those obtained from the balance. For normal force,the PSP and balance data agree quite well, to within 5%. The large difference inaxial force is ascribed to two causes. Most obvious is that the PSP cannot measuresurface shear stresses, which act mostly in the axial direction. A second source oferror is poor camera coverage at the leading edge of the wing, where significantforce is applied in the axial direction. When making force and moment measure-ments with PSP, it is critical to adequately view even relatively small surfaces, ifthey might make a significant contribution to the forces.

Even when integration is not desired, mapped PSP data can be quite use-ful because they allow the pressure distributions at different model conditionsto be compared directly. For example, Figure 24 shows pressure distributionsover a high-lift wing tested in the NASA Ames 12-ft pressure wind tunnel attwo slightly different angles of attack. The left-hand image shows the wing ata high (but still prestall) angle of attack, whereas the right-hand image showsthe same wing at an angle of attack just 0.5◦ higher. The two images appearquite similar, and noticeable differences are not apparent until a point-by-pointdifference between the two data sets is formed. The resulting difference image(Figure 25) shows that although pressure levels are unchanged over most of thewing, there are two areas, on the inboard flap and outboard leading edge, wherepressure has increased with angle of attack. These areas are the first parts ofthe wing to stall. This information is difficult to obtain with conventional pressuretaps; indeed, on this wing the pressure tap rows pass on either side of the partsof the wing that are stalling first. By mapping PSP data onto a surface grid, theinfluence of viewing angle is removed, and even results at very different modelpositions can be compared directly.

6.6 Biluminophore Paints

Figures 26–28 (from Lyonnet et al 1998) show an application of biluminophorePSP to the wing of an Airbus model tested in the transonic test section of theONERA S2MA tunnel at Modane. This paint (OPTROD LPS-B1) was developedat TsAGI in Moscow. The false-colored raw PSP images shown in Figure 26illustrate that there is a qualitative change at the pressure-sensitive wavelength ofthe paint (blue images) between wind-on and wind-off conditions. The change atthe reference wavelength is much smaller and mostly driven by the motion of themodel with respect to the lamps between the two conditions. To obtain intensity-ratio data, the ratio of the wind-off and wind-on pressure images was divided bythe ratio of the reference images (Section 4.2.4). The temperature sensitivities ofthe two luminophores partially offset each other, yielding a net sensitivity of only0.1%◦C−1. The intensity-ratio images were converted to pressure using an a prioricalibration; further temperature correction was achieved by estimating the expectedmodel temperature with the computed temperature for an adiabatic flat plate. Data

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Figure 28 Chordwise line plots of biluminophore pressure-sensitive paint data at three spanwiselocations, compared with pressure tap data at the same spanwise position (from Lyonnet et al 1998,with permission).

processing was done using software developed by ONERA; the resulting imageis shown in Figure 27, and line plots from the image are given in Figure 28,together with pressure-tap data. Within the supersonic region of the flow, agree-ment between the taps and PSP data is∼0.02 inCp units. The taps were locatedon the wing opposite the one that was actually painted. Because the test was per-formed without boundary layer transition strips on the wings, the paint roughnessmay have caused small differences in shock location between the wings, whichwould be responsible for the discrepancies observed between PSP and pressure-tapresults.

6.7 Comparison of Lifetime and Intensity Measurements

Luminescent lifetime measurements allow PSP data to be obtained without require-ment for a wind-off reference. This is an advantage in production wind tunnels,where it may not be feasible to take wind-off images until hours after wind-on im-ages were obtained, with the concomitant possibility of error caused by temperatureeffects, photodegradation, and equipment failure. Recently, lifetime and intensity-based techniques were compared in a large production facility, the AEDC 16Tpropulsion wind tunnel (ME Sellers & L Goss, manuscript in preparation). Inthis test, jointly sponsored by AEDC, the Lockheed Martin Aeronautics Com-pany, and Innovative Scientific Solutions Inc, an F-16 model was coated with UWPtTFPP/FIB paint. Although this paint is generally used with intensity-based PSP

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systems, its relatively long lifetime (τVAC = 85µs) makes it suitable for lifetimemeasurements as well. To make the lifetime measurements, a Roper ScientificTEA/CCD–1024TK camera was modified with a lens-coupled image intensifier.The intensifier was used as a fast shutter that could be opened and closed repeat-edly while the camera CCD was collecting charge. Illumination was provided bya Xenon Corporation flash unit, which had a flash duration of∼2 µs. To takedata, the intensifier was gated to allow passage of light for only a certain timeinterval after the flash was fired. To acquire enough photons for acceptable SNR,images were formed by exposing the CCD to several hundred sequential flashesat the same time interval. Images at two different time intervals were ratioedto measure the PSP lifetime and thus pressure, as shown in Figure 8. A cali-brated image from the lifetime system is compared to a similar intensity-basedPSP image (taken during a separate run) in Figures 29 and 30. Limitations of theintensifier-lens coupling available at the time of the test reduce the field of viewand spatial resolution of the lifetime system relative to the intensity-based system.In addition, the area of satisfactory illumination with the single flash lamp was lim-ited to the left wing. Despite these limitations, the lifetime results compare wellwith those from the intensity-based system. Furthermore, the image in Figure 29was acquired without recourse to wind-off runs, as required for Figure 30, and datareduction was simplified by the lack of image registration requirements.

7. CONCLUSIONS

The PSP technique, which was invented independently in both the former SovietUnion and in the United States in the 1980s, is now widely used at researchestablishments all over the world. Surface pressure measurements in both basicfluid mechanics studies and production-type aerodynamic testing are now oftenmade using this technology. The technique is being applied to a variety of windtunnel and flight models over a wide range of testing conditions.

The initial development of the PSP measurement technique was the result of afortuitous confluence of several technologies, each at a very opportune stage of itsown development. The concept of oxygen quenching had already been observed,but the idea of adding a porphyrin to a transparent oxygen-permeable polymerbinder to form a paint was only realized in the 1980s. The development of digitalcamera technology reached a point at which affordable scientific-grade CCDsbecame available, and the rapid increase in computing power made large-scaleimage processing and data reduction in reasonable times more viable.

The main advantage of the PSP technique is the enormity of the spatial resolutionthat can be obtained. Also, once the initial investment in the system is made, it isrelatively easy and cost-effective to operate. Thus far, the PSP technique has provedvery useful for qualitative visualization of critical flow phenomena such as shockwave location and boundary layer separation. Of even more importance, accuratequantitative data can now be obtained by both in situ and a priori calibration

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methods. However, the technique is not mature enough to completely eliminatethe need for conventional loads models.

Intensity-based systems are more widely used, and they have seen many im-provements, although the full benefits of a reference or binary paint, whereby theneed for wind-off images is eliminated, have yet to be realized. Lifetime-basedsystems are gaining popularity, mainly because they do not suffer from problemsthat arise because of model deflection or deformation under air loads. With bothtypes of systems, the sensitivity of PSPs to temperature continues to plague theoverall accuracy of the measured data.

Improvements continue to be made to all aspects of the PSP measurement sys-tem, including paint development, illumination and imaging techniques, and dataacquisition and reduction procedures. In particular, corrections required becauseof effects such as model movement and self-illumination can now be applied moreaccurately. Among the main advances in PSP applications are the successful use invery low-speed (M < 0.2) flows, in rotating systems, such as turbomachinery androtorcraft, and in icing studies. Other notable areas of new PSP applications, whichare not specifically discussed here, include measurements in cryogenic and hyper-sonic wind tunnels and in flight tests. The ultimate goal of exclusively using PSPfor surface pressure measurements is perhaps not as elusive as it once appeared.

ACKNOWLEDGMENTS

This article is dedicated to Martin Gouterman, our guru and mentor on pressure-sensitive paint chemistry and development, on the occasion of his retirement fromthe Department of Chemistry, University of Washington, Seattle. We deeply thankall of our colleagues at NASA Ames Research Center who reviewed an earlierdraft of this article. We express our gratitude to Marianne Lyonnet (Office Nationald’Etudes et de Recherches Aerospatiales), Marvin Sellers (Arnold Engineering De-velopment Center), Larry Goss (Innovative Scientific Solutions Inc), Larry Lydick(Lockheed Martin Aeronautics Company), Tim Bencic (NASA Glenn ResearchCenter), and Owen Brown (Stanford University) for their kind permission to re-produce their PSP results.

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Figure 14 Ratioed image from high-speed civil transport model test. Image is false-colored, so that low pressure isblue, and high pressure isred.

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Figure 16 Pressure-sensitive paint image data mapped onto model surface grid. False-colored using same scale as in Figure 14.

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Figure 17 Pressure distribution over upper surface of an NACA 0012 airfoil atα = 5◦,U = 20 m s−1 (from Brown 2000, with permission).

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Figure 18 Pressure-sensitive paint images of a fan blade at three different fan loadingswhile running at the same speed–accomplished by varying back pressure (from Bencic1997, with permission).

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Figure 19 Photograph showing iced airfoil with pressure-sensitive paint (PSP) applied.Leading edge is atleft; PSP ispink areaon leading edge andpink strip. The dark lineperpendicular to the leading edge is a slot that was cut to produce Figure 20 (from Bencic2000, with permission).

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Figure 21 Pressure-sensitive paint image of iced region of airfoil shown in Figure 19(from Bencic 2000, with permission).

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Figure 22 Pressure-sensitive paint data mapped to surface grid for transonic wing.

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Figure 24 (Left) Upper surface of high-lift wing at a high (prestall) angle of attack. (Right) Uppersurface of high-lift wing at an angle of attack 0.5◦ higher than wing on left.

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Figure 26 Raw images of biluminophore pressure-sensitive paint applied to Airbus A300wing tested atα = 2◦, M = 0.8. Blue imagesare pressure sensitive, andred imagesarepressure insensitive (from Lyonnet et al 1998, with permission).

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Figure 27 Calibrated image of A300 wing from biluminophore pressure-sensitive paintdata shown in Figure 26 (from Lyonnet et al 1998, with permission).

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Figure 29 Upper surface of F-16 model atM = 0.8, α = 10◦, taken with lifetime-basedpressure-sensitive paint (PSP) system.Gray areas at nose and tail indicate absence of PSP data(from Sellers & Gross, paper in preparation).

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Figure 30 Upper surface of F-16 model atM = 0.8,α = 10◦, taken with conventional intensity-based pressure-sensitive paint system (from Sellers & Gross, paper in preparation).

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