Incorporation of Hysteretic Effects in Model-Order Reduction Analysis of Magnetic Devices

The ability to predict the properties of magnetic materials in a device is essential to ensuring the correct operation and optimization of the design as well as the device behavior over a wide range of input frequencies. Typically, development and simulation of wide-bandwidth models requires detailed, physics-based simulations that utilize significant computational resources. Balancing the trade-offs between model computational overhead and accuracy can be cumbersome, especially when the nonlinear effects of saturation and hysteresis are included in the model. This study focuses on the development of a system for analyzing magnetic devices in cases where model accuracy and computational intensity must be carefully and easily balanced by the engineer. A method for adjusting model complexity and corresponding level of detail while incorporating the nonlinear effects of hysteresis is presented that builds upon recent work in loss analysis and magnetic equivalent circuit (MEC) modeling. The approach utilizes MEC models in conjunction with linearization and model-order reduction techniques to process magnetic devices based on geometry and core type. The validity of steady-state permeability approximations is also discussed.

Effect of boiling on deposition of metallic colloids

In this study the relationship between heterogeneous nucleate boiling surfaces and deposition of suspended metallic colloidal particles, popularly known as crud or corrosion products in process industries, on those heterogeneous sites is investigated. Various researchers have reported that hematite is a major constituent of crud which makes it the primary material of interest; however the models developed in this work are irrespective of material choice. Qualitative hypotheses on the deposition process under boiling as proposed by previous researchers have been tested, which fail to provide explanations for several physical mechanisms observed and analyzed. In this study a quantitative model of deposition rate has been developed on the basis of bubble dynamics and colloid-surface interaction potential. Boiling from a heating surface aids in aggregation of the metallic particulates viz. nano-particles, crud particulate, etc. suspended in a liquid, which helps in transporting them to heating surfaces. Consequently, clusters of particles deposit onto the heating surfaces due to various interactive forces, resulting in formation of porous or impervious layers. The deposit layer grows or recedes depending upon variations in interparticle and surface forces, fluid shear, fluid chemistry, etc. This deposit layer in turn affects the rate of bubble generation, formation of porous chimneys, critical heat flux (CHF) of surfaces, activation and deactivation of nucleation sites on the heating surfaces. Several problems are posed due to the effect of boiling on colloidal deposition, which range from research initiatives involving nano-fluids as a heat transfer medium to industrial applications such as light water nuclear reactors. In this study, it is attempted to integrate colloid and surface science with vapor bubble dynamics, boiling heat transfer and evaporation rate. Pool boiling experiments with dilute metallic colloids have been conducted to investigate several parameters impacting the system. The experimental data available in the literature is obtained by flow experiments, which do not help in correlating boiling mechanism with the deposition amount or structure. With the help of experimental evidences and analysis, previously proposed hypothesis for particle transport to the contact line due to hydrophobicity has been challenged. The experimental observations suggest that deposition occurs around the bubble surface contact line and extends underneath area of the bubble microlayer as well. During the evaporation the concentration gradient of a non-volatile species is created, which induces osmotic pressure. The osmotic pressure developed inside the microlayer draws more particles inside the microlayer region or towards contact line. The colloidal escape time is slower than the evaporation time, which leads to the aggregation of particles in the evaporating micro-layer. These aggregated particles deposit onto or are removed from the heating surface, depending upon their total interaction potential. Interaction potential has been computed with the help of surface charge and van der Waals potential for the materials in aqueous solutions. Based upon the interaction-force boundary layer thickness, which is governed by debye radius (or ionic concentration and pH), a simplified quantitative model for the attachment kinetics is proposed. This attachment kinetics model gives reasonable results in predicting attachment rate against data reported by previous researchers. The attachment kinetics study has been done for different pH levels and particle sizes for hematite particles. Quantification of colloidal transport under boiling scenarios is done with the help of overall average evaporation rates because generally waiting times for bubbles at the same position is much larger than growth times. In other words, from a larger measurable scale perspective, frequency of bubbles dictates the rate of collection of particles rather than evaporation rate during micro-layer evaporation of one bubble. The combination of attachment kinetics and colloidal transport kinetics has been used to make a consolidated model for prediction of the amount of deposition and is validated with the help of high fidelity experimental data. In an attempt to understand and explain boiling characteristics, high speed visualization of bubble dynamics from a single artificial large cavity and multiple naturally occurring cavities is conducted. A bubble growth and departure dynamics model is developed for artificial active sites and is validated with the experimental data. The variation of bubble departure diameter with wall temperature is analyzed with experimental results and shows coherence with earlier studies. However, deposit traces after boiling experiments show that bubble contact diameter is essential to predict bubble departure dynamics, which has been ignored previously by various researchers. The relationship between porosity of colloid deposits and bubbles under the influence of Jakob number, sub-cooling and particle size has been developed. This also can be further utilized in variational wettability of the surface. Designing porous surfaces can having vast range of applications varying from high wettability, such as high critical heat flux boilers, to low wettability, such as efficient condensers.

A study of computational methods to analyze gene expression data

The recent advent of new technologies has led to huge amounts of genomic data. With these data come new opportunities to understand biological cellular processes underlying hidden regulation mechanisms and to identify disease related biomarkers for informative diagnostics. However, extracting biological insights from the immense amounts of genomic data is a challenging task. Therefore, effective and efficient computational techniques are needed to analyze and interpret genomic data. In this thesis, novel computational methods are proposed to address such challenges: a Bayesian mixture model, an extended Bayesian mixture model, and an Eigen-brain approach. The Bayesian mixture framework involves integration of the Bayesian network and the Gaussian mixture model. Based on the proposed framework and its conjunction with K-means clustering and principal component analysis (PCA), biological insights are derived such as context specific/dependent relationships and nested structures within microarray where biological replicates are encapsulated. The Bayesian mixture framework is then extended to explore posterior distributions of network space by incorporating a Markov chain Monte Carlo (MCMC) model. The extended Bayesian mixture model summarizes the sampled network structures by extracting biologically meaningful features. Finally, an Eigen-brain approach is proposed to analyze in situ hybridization data for the identification of the cell-type specific genes, which can be useful for informative blood diagnostics. Computational results with region-based clustering reveals the critical evidence for the consistency with brain anatomical structure.

Core-level photoemission investigations of the CDTE(100) and INSB(100) surface and interfacial structures

Photoemission techniques, utilizing a synchrotron light source, were used to analyze the clean (100) surfaces of the zinc-blende semiconductor materials CdTe and InSb. Several interfacial systems involving the surfaces of these materials were also studied, including the CdTe(lOO)-Ag interface, the CdTe(lOO)-Sb system, and the InSb(lOO)-Sn interface. High-energy electron diffraction was also employed to acquire information about of surface structure. A one-domain (2xl) structure was observed for the CdTe(lOO) surface. Analysis of photoemission spectra of the Cd 4d core level for this surface structure revealed two components resulting from Cd surface atoms. The total intensity of these components accounts for a full monolayer of Cd atoms on the surface. A structural model is discussed commensurate with these results. Photoemission spectra of the Cd and Te 4d core levels indicate that Ag or Sb deposited on the CdTe(l00)-(2xl) surface at room temperature do not bound strongly to the surface Cd atoms. The room temperature growth characteristics for these two elements on the CdTe(lOO)-(2xl) are discussed. The growth at elevated substrate temperatures was also studied for Sb deposition. The InSb(lOO) surface differed from the CdTe(lOO) surface. Using molecular beam epitaxy, several structures could be generated for the InSb(lOO) surface, including a c(8x2), a c(4x4), an asymmetric (lx3), a symmetric (lx3), and a (lxl). Analysis of photoemission intensities and line shapes indicates that the c(4x4) surface is terminated with 1-3/4 monolayers of Sb atoms. The c(8x2) surface is found to be terminated with 3/4 monolayer of In atoms. Structural models for both of these surfaces are proposed based upon the photoemission results and upon models of the similar GaAs(lOO) structures. The room temperature growth characteristics of grey Sn on the lnSb(lOO)-c(4x4) and InSb(l00)-c(8x2) surfaces were studied with photoemission. The discontinuity in the valence band maximum for this semiconductor heterojunction system is measured to be 0.40 eV, independent of the starting surface structure and stoichiometry. This result is reconciled with theoretical predictions for heterostructure behavior.