Radially rotating miniature heat pipes for turbine blade cooling applications

Aerospace turboengines present a demanding challenge to many heat transfer scientists and engineers. Designers in this field are seeking the best design to transform the chemical energy of the fuel into the useful work of propulsive thrust at maximum efficiency. To this aim, aerospace turboengines must operate at very high temperatures and pressures with very little heat losses. These requirements are often in conflict with the ability to protect the turboengine blades from this hostile thermal environment. Heat pipe technology provides a potential cooling means for the structure exposed to high heat fluxes. Therefore, the objective of this dissertation is to develop a new radially rotating miniature heat pipe, which would combine the traditional air-cooling technology with the heat pipe for more effective turboengine blade cooling. ^ In this dissertation, radially rotating miniature heat pipes are analyzed and studied by employing appropriate flow and heat transfer modeling as well as experimental tests. The analytical solutions for the flows of condensate film and vapor, film thickness, and vapor temperature distribution along the heat pipe length are derived. The diffuse effects of non-condensable gases on the temperature distribution along the heat pipe length are also studied, and the analytical solutions for the temperature distributions with the diffuse effects of non-condensable gases are obtained. Extensive experimental tests on radially rotating miniature heat pipes with different influential parameters are undertaken, and various effects of these parameters on the operation of the heat pipe performance are researched. These analytical solutions are in good agreement with the experimental data. ^ The theoretical and experimental studies have proven that the radially rotating miniature heat pipe has a very large heat transfer capability and a very high effective thermal conductance that is 60–100 times higher than the thermal conductivity of copper. At the same time, the heat pipe has a simple structure and low manufacturing cost, and can withstand strong vibrations and work in a high-temperature environment. Therefore, the combination of the traditional air-cooling technology with the radially rotating miniature heat pipe is a feasible and effective cooling means for high-temperature turbine blades. ^

Statistical analysis and optimal classification of blood cell populations using Gaussian distributions

This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gaussian distributions through a novel concept that relates the Fisher distance to the percentage of data overlap. The derivations are expanded to provide a generalized mathematical platform for determining an optimal separating boundary of Gaussian distributions in multiple dimensions. Real-world data used for implementation and in carrying out feasibility studies were provided by Beckman-Coulter. It is noted that although the data used is flow cytometric in nature, the mathematics are general in their derivation to include other types of data as long as their statistical behavior approximate Gaussian distributions. ^ Because this new figure of merit is heavily based on the statistical nature of the data, a new filtering technique is introduced to accommodate for the accumulation process involved with histogram data. When data is accumulated into a frequency histogram, the data is inherently smoothed in a linear fashion, since an averaging effect is taking place as the histogram is generated. This new filtering scheme addresses data that is accumulated in the uneven resolution of the channels of the frequency histogram. ^ The qualitative interpretation of flow cytometric data is currently a time consuming and imprecise method for evaluating histogram data. This method offers a broader spectrum of capabilities in the analysis of histograms, since the figure of merit derived in this dissertation integrates within its mathematics both a measure of similarity and the percentage of overlap between the distributions under analysis. ^

Multidimensional classification and diagnosis of leukemia in flow cytometry

This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

The effect of weathering processes on the vertical turbulent dispersion characteristics of crude oil spilled on the sea

Since the Exxon Valdez accident in 1987, renewed interest has come forth to better understand and predict the fate and transport of crude oil lost to marine environments. The short-term fate of an Arabian Crude oil was simulated in laboratory experiments using artificial seawater. The time-dependent changes in the rheological and chemical properties of the oil under the influence of natural weathering processes were characterized, including dispersion behavior of the oil under simulated ocean turbulence. Methodology included monitoring the changes in the chemical composition of the oil by Gas Chromatography/Mass Spectrometry (GCMS), toxicity evaluations for the oil dispersions by Microtox analysis, and quantification of dispersed soluble aromatics by fluorescence spectrometry. Results for this oil show a sharp initial increase in viscosity, due to evaporative losses of lower molecular weight hydrocarbons, with the formation of stable water-in-oil emulsions occurring within one week. Toxicity evaluations indicate a decreased EC-50 value (higher toxicity) occurring after the oil has weathered eight hours, with maximum toxicity being observed after weathering seven days. Particle charge distributions, determined by electrophoretic techniques using a Coulter DELSA 440, reveal that an unstable oil dispersion exists within the size range of 1.5 to 2.5 um, with recombination processes being observed between sequential laser runs of a single sample.