Thesis (Ph. D.)--University of Washington, 1995. / Vita. Includes bibliographical references (leaves [187]-197).

Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Philip A. Durkee. Includes bibliographical references (p. 77-78). Also available online.

Universiẗat, Diss., 2003--Heidelberg.

La formation de poussières carbonées dans les tokamaks pose actuellement un réel problème (pertes de combustibles liées à la sécurité, pertes énergétiques …). Afin de comprendre les mécanismes de formation de ces poudres (distribution en taille, distribution spatiale et transport) et donc de trouver une méthode pour limiter leur rôle, une étude expérimentale a été réalisée dans une décharge radiofréquence Ar/C2H2. Le plasma et des poudres carbonées ont été caractérisés par différentes techniques (spectroscopie optique d’émission, diffusion du rayonnement, FTIR in-situ, caméra rapide, MEB et FTIR ex-situ). La diffusion du rayonnement polychromatique (IR et UV-visible-proche IR) a été utilisée afin d’obtenir des informations sur la distribution spatiale des poudres et l’évolution de leur distribution en taille. Un modèle, basé sur la théorie de Mie et associé à une méthode de Monte Carlo, a été développé afin de reproduire les mesures de diffusion in-situ. La comparaison entre expériences et simulations numériques à ouvert de nouvelles voies en termes d'interprétation et d'analyse des données. Cette étude est un premier pas vers la détermination en temps réel de la taille et de la densité des poussières en couplant les mesures optiques avec un modèle numérique basé sur la théorie de Mie. / The formation of carbon dust in tokamaks raises currently several real problems (safety, energy losses ...). To understand the mechanisms of these powders’ formation (size distribution, spatial distribution and transportation) and then find out a way to limit their role, an experimental study was carried out in a radiofrequency discharge Ar/C2H2. The plasma and these carbon powders were characterized by different techniques (optical emission spectroscopy, scattering of radiation, in-situ FTIR, fast camera, SEM and ex-situ FTIR). The scattering of polychromatic radiation (IR and Ultra violet-visible-near infrared) was used to obtain some information about the powders’ spatial distribution and the evolution of their size distribution. A model, based on the Mie theory and associated with the method of Monte Carlo, was developed to reproduce the optical measurements in-situ. The comparison between experiments and numerical simulations provides new roads in terms of interpretation and analysis of their results. This study is the first step to determine in real-time the dust size and density by coupling the optical measurements with the numerical model based on the Mie theory.

Infrared (IR) spectroscopy has shown potential to quickly and non-destructively measure the chemical signatures of biomedical samples such as single biological cells, and tissue from biopsy. The size of a single cell (diameter ~10-50 µm) are of a similar magnitude to the mid-IR wavelengths of light (~1-10 µm) giving rise to Mie-type scattering. The result of this scattering is that chemical information is significantly distorted in the IR spectrum.Distortions in biomedical IR spectra are often observed as a broad oscillating baseline on which the absorbance spectrum is superimposed. A spectral feature commonly observed is the sharp decrease in intensity at approximately 1700 cm-1, next to the Amide I band (~1655 cm-1), which pre-2009 was called the 'dispersion artefact'. The first contributing factor towards the 'dispersion artefact' investigated was the reflection signal arising from the air to sample interface entering the collection optics during transflection experiments. This was theoretically modelled, and then experimentally verified. It was shown that IR mapping could be done using reflection mode, yielding information from the optically dense nucleus which previously caused extinction of light in transmission mode.The most important contribution to the spectral distortions was due to resonant Mie scattering (RMieS) which occurs when the scattering particle is strongly absorbing such as biomedical samples. RMieS was shown to explain both the baselines in IR spectra, and the 'dispersion artefact' and was validated using a model system of poly(methyl methacrylate) (PMMA) of varying sizes from 5 to 15 µm. Theoretical simulations and experimental data had an excellent match thus proving the theory proposed. With an understanding of the physics/mathematics of the spectral distortions, a correction algorithm was written, the RMieS extended multiplicative signal correction (RMieS-EMSC). This algorithm modelled the measured spectrum as superposition of a first guess (the reference spectrum) which was of a similar biochemical composition to the pure absorbance spectrum of the sample, and a scattering curve. The scattering curve was estimated as the linear combination of a database of a large number of scattering curves covering a range of feasible physical parameters. Simulated and measured data verified that the RMieS-EMSC increased IR spectral quality.

Desde su introducción, los motores de combustión interna alternativos han sido desarrollados con el fin de reducir el consumo y mejorar el rendimiento y facilidad de conducción. Con el tiempo, la contaminación se ha convertido en un factor crítico para los gobiernos y como consecuencia se han introducido regulaciones para reducir las emisiones contaminantes de los motores. Con el constante progreso tecnológico requerido por las normas contra la contaminación, la inyección directa se ha vuelto indispensable en cuanto a los motores Diesel. La introducción de combustible en la cámara de combustión permite un alto nivel de control sobre la liberación de energía del proceso de combustión. Con las novedosas estrategias de combustión empleadas, el proceso de inyección se ha convertido en el tema principal y el chorro es el factor principal. El trabajo realizado a lo largo de este estudio para analizar el proceso de mezcla aire-combustible se basa en el desarrollo de técnicas láser de diagnóstico. Inicialmente, la inyección de Diesel se ha estudiado en una atmósfera isoterma para evitar la evaporación del combustible (dodecano) a través del uso de una iluminación estructurada para medir la distribución de la mezcla mediante el control de la dispersión de Mie. La aplicación de la dispersión de Rayleigh en la parte evaporada del chorro inyectado en una cámara a alta temperatura ha permitido la obtención de la distribución de combustible en una situación equivalente a la existente en un motor real. El análisis y comparación de los distintos parámetros del chorro inyectado en condiciones de baja o alta temperatura da la posibilidad de entender mejor lo que es el proceso de mezcla en los motores Diesel. Por otra parte, según el estado del fluido inyectado, líquido o gaseoso, las condiciones experimentales tendrán diferentes efectos y la mezcla aire-combustible también tendrá un comportamiento distinto. / Manin ., JL. (2011). ANALYSIS OF MIXING PROCESSES IN LIQUID AND VAPORIZED DIESEL SPRAYS THROUGH LIF AND RAYLEIGH SCATTERING MEASUREMENTS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10189 / Palancia

This work addresses the problem of rendering clouds. The task of rendering clouds is important to film and video game directors who want to use clouds to further the story or create a specific atmosphere for the audience. While there has been significant progress in this area, other solutions to this problem are inadequate because they focus on speed instead of accuracy, or focus only on a few specific properties of rendered clouds while ignoring others. Another common shortcoming with other methods is that they are not integrated into existing rendering pipelines. We propose a solution to this problem based on creating a point cloud to represent the cloud volume, then calculating light scattering events between the points. The key insight is blending isotropic and anisotropic scattering events to mimic realistic light scattering of anisotropic participating media. Rendered images are visually plausible representations of how light interacts with clouds.

As the planetary climate continues to evolve, it is important to build an accurate long-term climate record. State-of-the-art atmospheric science requires a variety of approaches to the measurement of the atmospheric structure and composition. This thesis supports the possibility of inferring cloud properties from sun photometer observations of the cloud solar aureole using an artificial neural network (ANN). Training of an ANN requires a large number of input and output parameter sets. A cloud radiance model is derived that takes into consideration the cloud depth, the mean size of the cloud water particles, and the cloud liquid water content. The cloud radiance model derived here is capable of considering the wavelength of the incident sunlight and the cloud lateral dimensions as parameters; however, here we consider only one wavelength—550 nm—and one lateral dimension—500 m—to demonstrate its performance. The cloud radiance model is then used to generate solar aureole profiles corresponding to the cloud parameters as they would be observed using a sun photometer. Coefficients representative of the solar aureole profiles may then be used as inputs to a trained ANN to infer the parameters used to generate the profile. This process is demonstrated through examples. A manuscript submitted for possible publication based on an early version of the cloud radiance model was deemed naïve by reviewers, ultimately leading to improvements documented here. / Master of Science / The Earth's climate is driven by heat from the sun and the exchange of heat between the Earth and space. The role of clouds is paramount in this process. One aspect of "cloud forcing" is cloud structure and composition. Required measures may be obtained by satellite or surface-based observations. Described here is the creation of a numerical model that calculates the disposition of individual bundles of light within water clouds. The clouds created in the model are all described by the mean size of the cloud water droplets, the amount of water in the cloud, and cloud depth. Changing these factors relative to each other changes the amount of light that traverses the cloud and the angle at which the individual bundles of light leave the cloud as measured using a device called a sun photometer. The measured amount and angle of bundles of light leaving the cloud are used to recover the parameters that characterize the cloud; i.e., the size of the cloud water droplets, the amount of water in the cloud, and the cloud depth. Two versions of the cloud radiance model are described.

Surface plasmon resonance has become a widely investigated phenomenon in the past few years. Initially descriptive of light interactions with metallic films, research has branched out to encompass the nanoparticles as well. Generation of the maximum surface plasmon resonance for nanostructures is based on the resonance condition that the oscillatory behavior of the 'free' electrons on the surface of the particle become equivalent to the frequency of the excitation light; for films this required a specific geometry. Metallic nanoparticles have also interested researchers because of their unique optical properties. Depending on the metal, observations of quenching as well as fluorescence enhancement have been reported. Based on the phenomenon of surface plasmon resonance as well as the properties of metallic nanoparticles, this research reports the interaction of gold and silver nanoparticles in an aqueous dye solution. Our research is the basis for developing an optical sensor used for water treatment centers as an alarm mechanism. Due to the inefficiency of the fluorophore used in similar optodes, sufficient fluorescence was not obtained. With the addition of the nanoparticles, we hoped to observe the transfer of energy from the nanoparticle to the fluorophore to increase the overall intensity, thereby creating a sufficient signal. Using the excitation theories discovered by Raman, Mie, and Forster and Dexter as our foundation, we mixed a strongly fluorescent dye with gold nanoparticles and aagain with silver nanoparticles. After taken measurements via fluorescence spectroscopy, absorption spectroscopy, and photoluminescence excitation, we observed that the silver nanoparticles seemed to enhance the fluorescence of the dye while the gold nanoparticles quenched the fluorescence. / Master of Science

Increased efficiency and reduced emissions from gas turbine (GT) engines are of consistently growing concern for the current gas turbine community and for the political environment. GT engines commonly produce undesirable emissions such as Carbon Monoxide (CO), Carbon Dioxide (CO₂), Nitric Oxides (NO_x), and Unburned Hydrocarbons (UHC), which all pose various threats to the environment. Lean premixed combustion of hydrogen provides a potential solution to these concerns. A key component of successful lean hydrogen combustion is the fuel-air mixer. A facility and methodology for the evaluation of such a hydrogen-air mixer is developed and discussed in this thesis. The facility developed utilizes three experimental techniques: Mie scattering flow visualization, schlieren flow visualization, and Laser Doppler Velocimetry (LDV) to characterize and evaluate mixer performance. Results from the two flow visualization experiments illustrate the effectiveness of the established facility. The results from the Mie scattering experiment are post processed and overlaid on CFD predictions of mixer performance and many similarities are found. Capability of the LDV to measure two components of mean velocity is also demonstrated. / Master of Science