Title: Source Parameters of Microearthquakes and their Uncertainty Author: Jan Michálek Department: Department of Geophysics Supervisor: Doc. RNDr. Tomáš Fischer, PhD., Institute of Hydrogeology, Engineering Geology and Applied Geophysics, Charles University in Prague Abstract: The aim of this thesis is to analyze the spectral methods used for the determination of the earth- quake source parameters like the seismic moment M0 and the corner frequency fc and to apply these meth- ods to seismic data from the West Bohemian region. Considering some assumptions about the source the other important parameters like the source radius r or the stress drop in the source ∆σ can be evaluated. Determination of the parameters is performed in the spectral domain by comparing a simple Brune's source model (non-causal slip on a circular rupture; spectral slope ω−2) with the displacement of the P or S wave. The methods were applied to 56 selected earthquakes of the West Bohemian swarms from 2000 and 2008 by the absolute and relative approach in several modifications. The absolute method allows to determine not only the source parameters but also the quality factor Q (attenuation), which significantly affects the deter- mination of fc. Therefore, the absolute method was applied also as the joint inversion when Q is stabilized....

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Supersonic jet exhaust plumes produce noise in jet engines, which has been a problem in the aerospace field. Researchers are working on ways to reduce this turbulent mixing noise, with little modification to the engine and nozzle. Prior work has shown that total temperature non-uniformity is a noise reduction technique which introduces a stream of cold flow into the heated jet. This method has been shown to cause changes in the exhaust plume and result in a 2±0.5 dB reduction of peak sound pressure levels. The goal of this work is to reveal underlying changes in the spatial-temporal structure of plume instability and turbulence caused by non-uniform total temperature distributions. Studies have demonstrated several methods of jet noise reduction by modifying the turbulent mixing in the exhaust plume. Large-scale turbulent structures have been shown to be the dominant source of noise in heated supersonic jets, especially over long, streamwise distances. Therefore, a large field-of-view measurement is desirable for studying these structures. Time-Resolved Doppler Global Velocimetry (TR-DGV) with a sampling frequency of 50 kHz is used to collect flow velocity data that is resolved in both time and space. The experiments for data collection were performed on a heated supersonic jet at the Virginia Tech Advanced Propulsion and Power Laboratory. A converging-diverging nozzle with a diameter Reynolds number of 850,000 was used to generate a perfectly expanded, heated flow of Mach 1.5 and a nozzle pressure ratio (NPR) of 3.67. The unheated plume was introduced at the center of the nozzle, with a total temperature ratio (TTR) of 2. Comparison of the mean velocity fields shows that the introduction of the cooler temperature flow in the thermally non-uniform case results in a velocity deficit of about 10% compared to the thermally uniform case. The method of spectral proper orthogonal decomposition (SPOD) was used to reveal the large-scale, coherent noise producing mechanisms. SPOD results indicate that the thermally non-uniform case showed a decrease in turbulent kinetic energy compared to the uniform case at all frequencies. Coherent fluctuations start developing further upstream in the thermally non-uniform case. The addition of the unheated plume results in a disruption in the propagation of the Mach waves from the shear layer into the ambient. The results indicate that the total temperature non-uniformity results in a modified exhaust plume and mean flow distribution at the nozzle exit, compared to that of a thermally uniform flow, which past studies have indicated is a method to reduce jet noise. / Master of Science / Supersonic jet exhaust plumes produce noise in jet engines, which has been a problem in the aerospace field. Researchers are working on ways to reduce this turbulent mixing noise, with little modification to the engine and nozzle. Traditionally, nozzles produce a single stream of uniform temperature flow. This work identifies a method of reducing jet noise, known as thermal non-uniformity. A stream of cold flow is introduced at the center of the nozzle. Applying this method to jet engines can result in quieter aircraft. Large-scale turbulent structures are the dominant noise producing source in supersonic free jets. To further understand the relationship between coherent structures and acoustic jet noise, spectral analysis is used to educe these structures from the flow. This study uses velocity data collected using Time-Resolved Doppler Global Velocimetry (TR-DGV). The study compares the results of a thermally uniform and a thermally non-uniform heated supersonic jet of Mach 1.5. The goal of this study is to determine the effects of thermal non-uniformity on large-scale coherent structures using a modal decomposition analysis known as spectral proper orthogonal decomposition (SPOD). The results from this study show that the thermally non-uniform cases contained less turbulent kinetic energy compared to the thermally uniform cases. Coherent fluctuations start developing further upstream in the thermally non-uniform case. The addition of the unheated plume results in a disruption in the propagation of the Mach waves from the shear layer into the ambient. The results indicate that the total temperature non-uniformity results in a modified exhaust plume and mean flow distribution at the nozzle exit, compared to that of a thermally uniform flow, which past studies have indicated is a method to reduce jet noise.

This report presents an investigation and development of the methods for orbital object identification. Two goals were accomplished in this master’s thesis; the development of a method of inverting material proportions from an object’s combined spectrum, and the investigation of methods and initialization of measurement of space environment effects on spectral features of common spacecraft materials. A constrained least squares approach was chosen for inverting spectral proportions from the combined spectra. The final results fall within 1 - 15% of the original spectrum, depending on the quality and noise levels of the original spectrum. Additionally, the effects of outgassing and atomic oxygen erosion were measured using the vacuum chamber facilities at California Polytechnic State University and are to be used as a basis for future identification of orbital debris. To have a fully functional model for accurately identifying space objects, both parts are needed: a set of space environment effect measurements as a basis for the identification model (for use on objects exposed to the space environment), and the identification model to mathematically determine the best fit set of materials.

In today's highly competitive and deregulated electricity market, companies in the generation, transmission and distribution sectors can all benefit from collecting, analyzing and deep-understanding their customers' load profiles. This strategic information is vital in load forecasting, demand-side management planning and long-term resource and capital planning. With the proliferation of Advanced Metering Infrastructure (AMI) in recent years, the amount of load profile data collected by utilities has grown exponentially. Such high-resolution datasets are difficult to model and analyze due to the large size, diverse usage patterns, and the embedded noisy or erroneous data points. In order to overcome these challenges and to make the load data useful in system analysis, this dissertation introduces a frequency domain load profile modeling framework. This framework can be used a complementary technology alongside of the conventional time domain load profile modeling techniques. There are three main components in this framework: 1) the frequency domain load profile descriptor, which is a compact, modular and extendable representation of the original load profile. A methodology was introduced to demonstrate the construction of the frequency domain load profile descriptor. 2) The load profile Characteristic Attributes in the Frequency Domain (CAFD). Which is developed for load profile characterization and classification. 3) The frequency domain load profile statistics and forecasting models. Two different models were introduced in this dissertation: the first one is the wavelet load forecast model and the other one is a stochastic model that incorporates local weather condition and frequency domain load profile statistics to perform medium term load profile forecast. 7 different utilities load profile data were used in this research to demonstrate the viability of modeling load in the frequency domain. The data comes from various customer classes and geographical regions. The results have shown that the proposed framework is capable to model the load efficiently and accurately. / Ph. D.

Fault Detection and Diagnosis (FDD) constitutes an essential aspect of modern life, with far-reaching implications spanning various domains such as healthcare, maintenance of industrial machinery, and cybersecurity. A comprehensive approach to FDD entails addressing facets related to detection, invariance, isolation, identification, and supervision. In FDD, there are two main perspectives: model-based and data-driven approaches. This thesis centers on model-based methodologies, particularly within the context of control and industrial applications. It introduces novel estimation strategies aimed at enhancing computational efficiency, addressing fault discretization, and considering robustness in fault detection strategies. In cases where the system's behavior can vary over time, particularly in contexts like fault detection, presenting multiple scenarios is essential for accurately describing the system. This forms the underlying principle in Multiple Model Adaptive Estimation (MMAE) like well-established Interacting Multiple Model (IMM) strategy. In this research, an exploration of an efficient version of the IMM framework, named Updated IMM (UIMM), is conducted. UIMM is applied for the identification of irreversible faults, such as leakage and friction faults, within an Electro-Hydraulic Actuator (EHA). It reduces computational complexity and enhances fault detection and isolation, which is very important in real-time applications such as Fault-Tolerant Control Systems (FTCS). Employing robust estimation strategies such as the Smooth Variable Structure Filter (SVSF) in the filter bank of this algorithm will significantly enhance its performance, particularly in the presence of system uncertainties. To relax the irreversible assumption used in the UIMM algorithm and thereby expanding its application to a broader range of problems, the thesis introduces the Moving Window Interacting Multiple Model (MWIMM) algorithm. MWIMM enhances efficiency by focusing on a subset of possible models, making it particularly valuable for fault intensity and Remaining Useful Life (RUL) estimation. Additionally, this thesis delves into exploring chattering signals generated by the SVSF filter as potential indicators of system faults. Chattering, arising from model mismatch or faults, is analyzed for spectral content, enabling the identification of anomalies. The efficacy of this framework is verified through case studies, including the detection and measurement of leakage and friction faults in an Electro-Hydraulic Actuator (EHA). / Thesis / Candidate in Philosophy / In everyday life, from doctors diagnosing illnesses to mechanics inspecting cars, we encounter the need for fault detection and diagnosis (FDD). Advances in technology, like powerful computers and sensors, are making it possible to automate fault diagnosis processes and take corrective actions in real-time when something goes wrong. The first step in fault detection and diagnosis is to precisely identify system faults, ensuring they can be properly separated from normal variations caused by uncertainties, disruptions, and measurement errors. This thesis explores model-based approaches, which utilize prior knowledge about how a normal system behaves, to detect abnormalities or faults in the system. New algorithms are introduced to enhance the efficiency and flexibility of this process. Additionally, a new strategy is proposed for extracting information from a robust filter, when used for identifying faults in the system.

The magnitude of damage caused to the United States (US) coast due to hurricanes has increased significantly in the last decade. During the period 2004-2005, the US experienced seven of the costliest hurricanes in the country's history (NWS TPC-5, 2007) leading to an estimated loss of ~ $158 billion. The present method for predicting hurricane losses, HAZUS (HAZard US), is solely based on hurricane hazard and damage caused to building envelopes only and not to structural systems (Vickery et al., 2006). This method does not take into account an intermediate step that allows for better damage estimates, which is structural response to the hazards that in turn can be mapped to the damage. The focus of this study was to quantify the uncertainty in response of structures to the hurricane hazards associated with hurricanes from performance based engineering perspective. The study enumerates hazards associated with hurricanes events. The hazards considered can be quantified using a variety of measures, such as wind speed intensities, wave and surge heights. These hazards are quantified in terms of structural loads and are then applied to a structural system. Following that, structural analysis was performed to estimate the response from the structural system for given loads. All the possible responses are measured and they are fitted with suitable probability distribution to estimate the probability of a response. The response measured then can be used to understand the performance of a given structure under the various hurricane loads. Dynamic vs. static analysis was performed and results were compared. This will answer a few questions like, if there is any need to do both static and dynamic analysis and how hurricane loads affect the structural material models. This being an exploratory study, available resources, research, and models were used. For generation of annual or extreme values of hazard, various available wind speed, storm surge, and wave height models were studied and evaluated. The wind field model by Batts et al. (1980) was selected for generation of annual wind speed data. For calculation of maximum storm surge height, the Sea, Lake Overland Surges from Hurricane (SLOSH, Jelesnianski et al., 1992) program was used. Wave data was acquired from a National Oceanic and Atmospheric Administration (NOAA) database. The (extreme or annual) wind speed, surge height, and wave height generated were then fitted by suitable probability distributions to find the realizations of hazards and their probabilities. The distribution properties were calculated, correlations between the data were established, and a joint probability distribution function (PDF) of the parameters (wind speed, wave height, and storm surge) was generated. Once the joint distribution of extreme loads was established, the next step was to measure the dynamic response of the structural system to these hazards. To measure the structural response, a finite element model of three-story concrete frame were constructed. Time histories of wind load were generated from wind net pressure coefficients recorded in a wind tunnel test (Main and Fritz, 2006). Wave load time histories were generated using laboratory basin test (Hawke's et al., 1993) wave height time history data and were converted into wave loads using Bernoulli's equation. Surge height was treated as a hydrostatic load in this analysis. These load time histories were then applied to the finite element model and response was measured. Response of the structural system was measured in terms of the mean and maximum displacements recorded at specific nodes of model. Response was calculated for loads having constant mean wind speed and surge/wave and different time histories. The dominant frequency in the wind load time histories was closer to the natural frequency of the structural model used than the dominant frequency in the wave height time histories. Trends in the response for various combinations of mean wind speed, wave height, and surge heights were analyzed. It was observed that responses are amplified with increase in the mean wind speed. Less response was measured for change in mean surge/wave height as the tributary area for wave forces was less compared to wind force. No increase in dynamic amplification factor was observed for increase in force time histories case.

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