Filtered Rayleigh scattering (FRS) is a non-intrusive, optical measurement technique that can currently provide time-averaged, simultaneous planar measurements of three-component velocity, static temperature, and static density of aerodynamic flows. Development of the FRS technique has typically employed 532 nm Nd:YAG lasers coupled with the use of iodine vapor cells as the molecular filter. One method to improve the effective signal-to-noise ratio (SNR), and therefore the performance of an FRS system, is to use shorter wavelengths. This takes advantage of the dependence of the Rayleigh scattering signal on the inverse of the wavelength of the incident laser light to the fourth power: even small shifts to shorter wavelengths can offer significant gains in SNR as a result. This study explores the implementation of an ultraviolet (UV) FRS system nominally at 387 nm with the use cesium vapor as the molecular filter. The cesium absorption lineshapes (corresponding to the 62S1/2 → 82P3/2 atomic transitions around 387 nm) are considered along with camera specifications to simulate an ultraviolet filtered Rayleigh scattering (UV FRS) measurement of aerodynamic flows. A signal model is developed using numerical functions for the cesium vapor cell transmission, camera specifications, signal-dependent shot noise, and signal-independent electronic detector read noise. Using this noise-inclusive model (over a 2.4 GHz scan bandwidth with a 7.5 cm long cesium vapor cell corresponding to current Virginia Tech FRS capabilities) velocity, static temperature, and static density measurement sensitivities for this proposed configuration are analyzed by evaluating and deriving the Cramér-Rao lower bound (CRLB) for each quantity. The effects of different flow conditions, Mie and geometric scattering levels, cesium vapor cell temperature, and spectral resolution are demonstrated. It is found that the best possible theoretical measurement results are obtained for high-speed wind tunnel flow conditions with high spectral resolution, and that the CRLB for velocity, static temperature, and static density for a 387 nm system approaches or exceeds that of a 532 nm system for a given signal-to-noise ratio (SNR). / Master of Science / One type of non-intrusive measurement technique that can be applied to aerodynamic flows is filtered Rayleigh scattering (FRS). Unlike other non-intrusive techniques such as particle image velocimetry (PIV) and Doppler global velocimetry (DGV), FRS does not require that the flow be seeded with particles and can provide simultaneous measurements of three-component velocity, static temperature, and static density. Current FRS measurement systems commonly use 532 nm green-light lasers and iodine cells for filtering. However, a stronger Rayleigh scattering signal (and therefore better measurement) can be attained by using shorter laser wavelengths as the strength of the Rayleigh scattering is related to the inverse of the incident wavelength to the fourth power. This study takes advantage of this fact to propose an FRS measurement system using ultraviolet laser light at nominally 387 nm. The implementation of a commercially available 387 nm laser system with the use of cesium cells for filtering is investigated. In order to simulate the performance of the system, a signal model is developed that includes both signal-dependent shot noise, and signal-independent electronic detector read noise. The signal model is combined with the transmission profile of cesium vapor, commercially available camera specifications, and typical FRS measurement parameters to simulate a 387 nm FRS system measurement. The measurement sensitives and performance of the proposed UV FRS system at 387 nm are investigated by deriving and evaluating the Cramér-Rao lower bound (CRLB) for velocity, static temperature, and static density. The effects of different flow conditions, Mie and geometric scattering levels, cesium vapor cell temperature, and scan resolution are demonstrated. The best performance is attained at high-speed conditions with high spectral resolution, and this approaches or exceeds the simulated performance of a 532 nm system with an iodine vapor cell over the same range of conditions.

The filtered Rayleigh scattering (FRS) optical diagnostic has become an attractive technique for advanced aerodynamic measurements. The appeal of FRS is that it can simultaneously quantify density, temperature, and vector velocity. Additionally, it is entirely non-intrusive to the flow since the technique leverages how laser light scatters off of molecules naturally present in the gas. Acquired FRS data considered herein is in the form of a frequency spectrum. To process this data, a measurement model for the FRS spectrum is used, where inputs to this model are the flow field quantities of interest and the output is a representative FRS spectrum. An iterative procedure on these quantities is performed until the model spectrum matches the measured spectrum. However, as observed in certain applications of this technique, there is a range of measurement configurations where the standard methods to model this spectrum do not agree with measured spectra, even at known flow conditions. This disagreement causes large bias uncertainties in determined flow field quantities. This work leverages a data-driven approach to diagnose this disagreement by utilizing an extensive FRS database. Data analysis indicates that the widely used Tenti S6 model for the Rayleigh scattering lineshape is invalid in certain operating regions. A new Rayleigh lineshape modeling methodology, the Cabannes model, is introduced that vastly improves the agreement between measured and modeled FRS signals. Analysis of the Cabannes model indicates that one only needs to use this modeling methodology for FRS and not laser Rayleigh scattering (LRS). This improved measurement model can be used to mitigate bias uncertainties, and, in turn, improve the reliability of the FRS optical instrument. / Doctor of Philosophy / The filtered Rayleigh scattering (FRS) laser-based measurement technique has become an attractive tool for aerodynamic measurements. Leveraging the theory of Rayleigh scattering, measuring how laser light scatters off of air molecules can be used to determine the temperature, density, and velocity of the air. A specific combination of temperature, density, and velocity results in a unique, measured FRS signal. A computational model of this FRS signal is then used to go from FRS signal to those three quantities of interest. However, as observed by certain applications of this technique, there is a certain range of measurement cases where the standard methods to model this signal do not agree with measured signals at known values for temperature, density, and velocity of the air. This disagreement between modeled and measured signals causes large errors, and, therefore, decreases the reliability of this measurement for those cases. This work analyzes an extensive FRS database to determine the source of this disagreement. The conclusion from this data analysis is that the widely used computational model in the community is not correct for certain applications of this FRS measurement. A new method to model FRS signals is proposed in this work, which vastly improves the agreement between measured and modeled signals. This improved computational model can be used to remove the large errors seen in this FRS measurement system that were previously caused by modeling errors. This, in turn, will improve the reliability of this technique across the whole application space of applied aerodynamic measurements.

Doctor of Philosophy / Filtered Rayleigh scattering (FRS) is a laser-based measurement technique that makes use of the scattering of light off particles that are much smaller than the wavelength of light that hits them (i.e., Rayleigh scattering of air molecules). The scattered laser light is altered after encountering particles in predictable ways that can be related to changes in velocity, temperature, and density. However, other sources of scattered light interfere with the pure Rayleigh scattering signal such as Mie and background scattering. Mie scattering is the scattering of light off particles that are much bigger than the wavelength of light that hits them (i.e., dust particles suspended in air). Background scattering is the laser light scattered off physical objects that reflect back into the region of interest. The different types of scattering are accounted for with intensive modeling and iterative fitting schemes where the error between simulated data and experimental data is minimized. This fit allows for velocity, temperature, and density information to be extracted from the measured scattered light. This iterative scheme is then applied to experimental measurements on the ground with mini turbojet engines as well as full-scale turbofan engines. A data grouping technique is derived such that the total measured force using FRS can be divided into individual contributions from different parts of the engine. These developed techniques have laid the foundation for future in-flight measurements of engine forces.

Foundational approaches for realizing practical, non-intrusive measurements using filtered Rayleigh scattering (FRS) are presented and analyzed for the multi-property quantification of internal flow fields. Validation is challenging in applying computational fluid dynamics (CFD) solutions to real-world scenarios, necessitating benchmark measurements with well-defined uncertainties. The ideal instrument for achieving the required measurements should be non-intrusive and require no particulate or gas seeding. One approach that satisfies these requirements is filtered Rayleigh scattering. FRS is a laser-based optical diagnostic technique that allows for the simultaneous, non-intrusive measurement of three-component velocity, static temperature, and static density everywhere within a two-dimensional plane illuminated by laser light without using any form of flow seeding. The major disadvantage of FRS is that it is very susceptible to signal contamination from particles and surfaces illuminated by the probing laser source. The effects of these contamination sources of the FRS signal are quantified as a function of their intensity relative to the Rayleigh scattered light. As the most significant contributor to Rayleigh scattering contamination, methods for reducing geometric or background contributions were investigated. Structured illumination was applied in cross-correlation Doppler global velocimetry to reduce geometric scattering contributions in image acquisition, demonstrating the removal of background scattering biases in an FRS-similar technique. For multi-property measurements, it is shown that with only an order of magnitude estimate of Mie and geometric scattering, a range of wavenumbers termed the rejection region can be pre-defined such that molecular iodine absorbs the contamination. At the same time, Rayleigh scattered light can pass through. Mie and geometric scattering contributions are reduced to negligible levels within the rejection region, allowing for unbiased temperature and density measurement. Additionally, a method for determining only Doppler shift, desirable due to its increased processing speed and spatial resolution, was developed and shown to be robust to at least one order of magnitude greater Mie and geometric scattering than other methods. The biases associated with sampling a statistical average of the flow using time-averaged FRS were also investigated. The result is that measuring flow properties with the "constant in time" assumption is valid up to a turbulent intensity of 20%, resulting in biases in velocity and temperature greater than 10% of the measurement uncertainties predicted without these contributions. These advancements allow researchers to optimize measurement parameters and predict uncertainties before integrating them into a facility. These methods were implemented in a turbulent, highly distorted internal flow environment with Mie and background scattering present. Measurement uncertainties for vector velocity components, static temperature, and static density are predetermined using a 95% confidence interval on the Monte Carlo simulation results. Derived measurement uncertainties are calculated by propagating the results of the Monte-Carlo simulation. Measurements are compared to reference five-hole probe and particle image velocimetry measurements to assess the validity of the predicted uncertainty bounds. The results from this study show good agreement in the measurement of axial velocity and derived circumferential and radial flow angles when compared to reference measurements. These comparisons typically yield measurements that measure the same value as the five-hole probe data within the pre-defined uncertainty bounds of 9 m/s, 1.0°, and 3.8°, with significant deviations occurring at radii greater than 71% for tangential flow angle and radii greater than 55% for radial flow angle. Compared to facility average measurements, static density and static pressure data collected over the entire plane show RMSD values comparable to predicted measurement uncertainties of 0.043 kg/m^3 and 4.0 kPa, respectively. For the same comparison, temperature measurements show a greater RMSD than the predicted uncertainty of 8.4 K. While additional work remains to identify sources of bias error in some measurements, this work lays the foundation for FRS-based diagnostics to be used as a replacement or supplemental measurement technique in quantifying the state of fluid flow fields. / Doctor of Philosophy / Rayleigh scattering is a process that results from the interaction of light with microscopic particles that, whether we know it or not, we experience every day. When sunlight interacts with air molecules, the light scattered to our eyes is blue. The fact that the sky appears blue indicates a key property of Rayleigh scattering in that it is most efficient for the shortest wavelengths. What isn't apparent is that a whole host of other properties can be extracted from observed scattering by imaging it with a camera and a specialized filter when illuminated by a narrow wavelength laser. The problem is that a few dust particles, small enough to pass through a household air filter, can scatter more light than all the air molecules in a shot glass, with laser light scattering off large surfaces even more intense. The primary focus of this dissertation is to define Foundational approaches for realizing practical, non-intrusive filtered Rayleigh scattering techniques and methods necessary so that the light scattered from air molecules can be measured while avoiding the scattering from particles and surfaces. These approaches enable the measurement of the three-component velocity, temperature, and density of the gas being illuminated without the measurement affecting the flow itself. Because all these properties can be measured simultaneously, Rayleigh scattering provides one of the most comprehensive experimental measurement techniques available to researchers, making it highly desirable in quantifying gaseous flows and validating computational fluid dynamics calculations. Measurements collected with the techniques outlined in this work are validated experimentally using reference measurements in a large-scale internal flow facility, providing the groundwork for future applications of Rayleigh scattering-based diagnostics.

<p dir="ltr">From transonic to hypersonic regimes, the characterization of high-speed flow dynamics is critical for the development, testing, and improvement of launch and reentry vehicles, boost-glide vehicles, and thermal protection systems. The design of this technology often relies on computational/empirical models for predictions which make quantitative thermodynamic measurements crucial for numerical validation. Laser diagnostic techniques facilitate non-intrusive, <i>in situ</i> measurements of fluid dynamic properties as well as visualization of flows, shocks, and boundary layer interactions. However, many diagnostics rely on seeding the flow with foreign materials to make measurements, such as the application of particle image velocimetry (PIV), Doppler global velocimetry (DGV), and planar laser-induced fluorescence (PLIF). Molecular filtered Rayleigh scattering (FRS) diagnostics are attractive for flow characterization due to the fact that pressure, temperature, density and velocity measurements can be made directly from air or N₂ molecules without the need for seeding materials. The development of the burst-mode laser (BML) has enabled high-energy pulses generated at the rates necessary to resolve phenomena such as instabilities in boundary-layers and shock-wave evolution using Rayleigh scattering methods. The goal of this dissertation is to advance molecular burst-mode FRS for quantitative, high resolution, multi-parameter measurements. For fixed-wavelength FRS measurements, the spectral characteristics of a BML system were investigated and improved by integrating an etalon for spectral-gating. For multi-parameter measurements, two strategies for wavelength-agility, the ability to quickly switch between two or more laser wavelengths, of the BML were explored: frequency-scanning and frequency-shifting. The frequency-scanning FRS (FS-FRS) technique measurement rate was increased to 1 kHz and demonstrated for 1-ms pressure, temperature, and radial velocity measurements in an underexpanded jet flow. Building upon this, an acousto-optic modulator-based method was implemented to generate frequency-shifted pulses. The rapid frequency-shifting increased the effective FRS multi-parameter measurement rate to 25 kHz and planar pressure, temperature, and radial velocity measurements were captured in an overexpanded jet flow. Finally, design tools for the laser configuration of wavelength-agile FRS were developed for the optimization of relative absolute measurement errors.</p>