Automation of shear-wave splitting parameter determination of local earthquakes at Yellowstone : application as indicator of crustal stress and temporal variation

Shear-wave splitting can be a useful technique for determining crustal stress fields in volcanic settings and temporal variations associated with activity. Splitting parameters were determined for a subset of local earthquakes recorded from 2000-2010 at Yellowstone. Analysis was automated using an unsupervised cluster analysis technique to determine optimum splitting parameters from 270 analysis windows for each event. Six stations clearly exhibit preferential fast polarization values sub-orthogonal to the direction of minimum horizontal compression. Yellowstone deformation results in a local crustal stress field differing from the regional field dominated by NE-SW extension, and fast directions reflect this difference rotating around the caldera maintaining perpendicularity to the rim. One station exhibits temporal variations concordant with identified periods of caldera subsidence and uplift. From splitting measurements, we calculated a crustal anisotropy of ~17-23% and crack density ~0.12-0.17 possibly resulting from stress-aligned fluid filled microcracks in the upper crust and an active hydrothermal system.

Charge and spin transport in nanoscale junction from first principles

Recently nanoscale junctions consisting of 0-D nanostructures (single molecule) or 1-D nanostructures (semiconducting nanowire) sandwiched between two metal electrodes are successfully fabricated and characterized. What lacks in the recent developments is the understanding of the mechanism behind the observed phenomena at the level of atoms and electrons. For example, the origin of observed switching effect in a semiconducting nanowire due to the influence of an external gate bias is not yet understood at the electronic structure level. On the same context, different experimental groups have reported different signs in tunneling magneto-resistance for the same organic spin valve structure, which has baffled researchers working in this field. In this thesis, we present the answers to some of these subtle questions by investigating the charge and spin transport in different nanoscale junctions. A parameter-free, single particle Green’s function approach in conjunction with a posteriori density functional theory (DFT) involving a hybrid orbital dependent functional is used to calculate the tunneling current in the coherent transport limit. The effect of spin polarization is explicitly incorporated to investigate spin transport in a nanoscale junction. Through the electron transport studies in PbS nanowire junction, a new orbital controlled mechanism behind the switching of the current is proposed. It can explain the switching behavior, not only in PbS nanowire, but in other lead-chalcogenide nanowires as well. Beside this, the electronic structure properties of this nanowire are studied using periodic DFT. The quantum confinement effect was investigated by calculating the bandgap of PbS nanowires with different diameters. Subsequently, we explain an observed semiconducting to metallic phase transition of this nanowire by calculating the bandgap of the nanowire under uniform radial strain. The compressive radial strain on the nanowire was found to be responsible for the metallic to semiconducting phase transition. Apart from studying one dimensional nanostructure, we also present transport properties in zero dimensional single molecular junctions. We proposed a new codoping approach in a single molecular carborane junction, where a cation and an anion are simultaneously doped to find the role of a single atom in the device. The main purpose was to build a molecular junction where a single atom can dictate the flow of electrons in a circuit. Recent observations of both positive and negative sign in tunneling magnetoresistance (TMR) the using same organic spin-valve structure hasmystified researchers. From our spin dependent transport studies in a prototypical organic molecular tunneling device, we found that a 3% change in metal-molecule interfacial distance can alter the sign of TMR. Changing the interfacial distance by 3%, the number of participating eigenstates as well as their orbital characteristic changes for anti-parallel configuration of the magnetization at the two electrodes, leading to the sign reversal of the TMR. Apart from this, the magnetic proximity effect under applied bias is investigated quantitatively, which can be used to understand the observed unexpectedmagnetismin carbon basedmaterials when they are in close proximity with magnetic substrates.

Parameter estimation for transformer modeling

Large Power transformers, an aging and vulnerable part of our energy infrastructure, are at choke points in the grid and are key to reliability and security. Damage or destruction due to vandalism, misoperation, or other unexpected events is of great concern, given replacement costs upward of $2M and lead time of 12 months. Transient overvoltages can cause great damage and there is much interest in improving computer simulation models to correctly predict and avoid the consequences. EMTP (the Electromagnetic Transients Program) has been developed for computer simulation of power system transients. Component models for most equipment have been developed and benchmarked. Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Thus, transformer modeling is not a mature field and newer improved models must be made available. In this work, improved topologically-correct duality-based models are developed for three-phase autotransformers having five-legged, three-legged, and shell-form cores. The main problem in the implementation of detailed models is the lack of complete and reliable data, as no international standard suggests how to measure and calculate parameters. Therefore, parameter estimation methods are developed here to determine the parameters of a given model in cases where available information is incomplete. The transformer nameplate data is required and relative physical dimensions of the core are estimated. The models include a separate representation of each segment of the core, including hysteresis of the core, λ-i saturation characteristic, capacitive effects, and frequency dependency of winding resistance and core loss. Steady-state excitation, and de-energization and re-energization transients are simulated and compared with an earlier-developed BCTRAN-based model. Black start energization cases are also simulated as a means of model evaluation and compared with actual event records. The simulated results using the model developed here are reasonable and more correct than those of the BCTRAN-based model. Simulation accuracy is dependent on the accuracy of the equipment model and its parameters. This work is significant in that it advances existing parameter estimation methods in cases where the available data and measurements are incomplete. The accuracy of EMTP simulation for power systems including three-phase autotransformers is thus enhanced. Theoretical results obtained from this work provide a sound foundation for development of transformer parameter estimation methods using engineering optimization. In addition, it should be possible to refine which information and measurement data are necessary for complete duality-based transformer models. To further refine and develop the models and transformer parameter estimation methods developed here, iterative full-scale laboratory tests using high-voltage and high-power three-phase transformer would be helpful.

Parameter identification of a copper-zeolite SCR catalyst model using reactor data

The selective catalytic reduction system is a well established technology for NOx emissions control in diesel engines. A one dimensional, single channel selective catalytic reduction (SCR) model was previously developed using Oak Ridge National Laboratory (ORNL) generated reactor data for an iron-zeolite catalyst system. Calibration of this model to fit the experimental reactor data collected at ORNL for a copper-zeolite SCR catalyst is presented. Initially a test protocol was developed in order to investigate the different phenomena responsible for the SCR system response. A SCR model with two distinct types of storage sites was used. The calibration process was started with storage capacity calculations for the catalyst sample. Then the chemical kinetics occurring at each segment of the protocol was investigated. The reactions included in this model were adsorption, desorption, standard SCR, fast SCR, slow SCR, NH3 Oxidation, NO oxidation and N2O formation. The reaction rates were identified for each temperature using a time domain optimization approach. Assuming an Arrhenius form of the reaction rates, activation energies and pre-exponential parameters were fit to the reaction rates. The results indicate that the Arrhenius form is appropriate and the reaction scheme used allows the model to fit to the experimental data and also for use in real world engine studies.

DEVELOPMENT OF CONFOCAL IMAGING TECHNIQUES FOR PROBING INTERFACIAL DYNAMICS IN MICROSCALE, GAS-LIQUID, TWO-PHASE FLOW

Micro-scale, two-phase flow is found in a variety of devices such as Lab-on-a-chip, bio-chips, micro-heat exchangers, and fuel cells. Knowledge of the fluid behavior near the dynamic gas-liquid interface is required for developing accurate predictive models. Light is distorted near a curved gas-liquid interface preventing accurate measurement of interfacial shape and internal liquid velocities. This research focused on the development of experimental methods designed to isolate and probe dynamic liquid films and measure velocity fields near a moving gas-liquid interface. A high-speed, reflectance, swept-field confocal (RSFC) imaging system was developed for imaging near curved surfaces. Experimental studies of dynamic gas-liquid interface of micro-scale, two-phase flow were conducted in three phases. Dynamic liquid film thicknesses of segmented, two-phase flow were measured using the RSFC and compared to a classic film thickness deposition model. Flow fields near a steadily moving meniscus were measured using RSFC and particle tracking velocimetry. The RSFC provided high speed imaging near the menisci without distortion caused the gas-liquid interface. Finally, interfacial morphology for internal two-phase flow and droplet evaporation were measured using interferograms produced by the RSFC imaging technique. Each technique can be used independently or simultaneously when.