Physical Sciences and Mathematics Commons^™

Modeling Of The Inverse Heat -Conduction Problem With Application To Laser Chemical Vapor Deposition And Bioheat Transfer, Peng Zhen

Doctoral Dissertations

This dissertation consists of two parts. Part one deals with three-dimensional laser induced chemical vapor deposition (3D-LCVD), whereas part two deals with a Pennes model of a 3D skin structure. LCVD is an important technique in manufacturing complex micro-structures with high aspect ratio. In part one, a numerical model was developed for simulating kinetically-limited growth of an axisymmetric cylindrical rod by pre-specifying the surface temperature distribution required for growing the rod and then by obtaining optimized laser power that gives rise to the pre-specified temperature distribution. The temperature distribution at the surface of the rod was assumed to be at …

Understanding Wavelet Analysis And Filters For Engineering Applications, Chethan Bangalore Parameswariah

Doctoral Dissertations

Wavelets are signal-processing tools that have been of interest due to their characteristics and properties. Clear understanding of wavelets and their properties are a key to successful applications. Many theoretical and application-oriented papers have been written. Yet the choice of a right wavelet for a given application is an ongoing quest that has not been satisfactorily answered. This research has successfully identified certain issues, and an effort has been made to provide an understanding of wavelets by studying the wavelet filters in terms of their pole-zero and magnitude-phase characteristics. The magnitude characteristics of these filters have flat responses in both …

Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara

Doctoral Dissertations

In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.

In the simulated data sets, I investigate two …

Study Of Energy Sampling Weights In The Dø Detector Using Multiparameter Fitting Method, Qun Yu

Doctoral Dissertations

The DØ calorimeter at Fermilab is a sampling calorimeter measuring the energy of particles produced in high energy proton-antiproton collisions. A set of accurate sampling weights is of significant importance to DØ research activity. The objective of this work was to obtain a set of optimized sampling weights for the DØ central calorimeter, the Inter-Cryostat Detector (ICD), the Central Calorimeter Massless Gap (CCMG), and the End Calorimeter Massless Gap (ECMG).

The foundation of the optimization method is that, in high energy physics, the ratio of energy E and the corresponding momentum P of a particle is approximately 1, in units …