In this dissertation, we present the theory and application of polyspectral signal analysis techniques for interharmonics in shipboard power systems. Interharmonics are generated from various kinds of adjustable speed drives (ASD) in such power systems. ASDs are highly nonlinear devices due to the use of rectifiers and inverters. Since interharmonics can seriously hamper the normal operation of electric ships in many different ways (e.g., excitation of undesirable electrical and/or mechanical resonances, misoperation of control devices, and light flicker), the detection and analysis of interharmonic-related events is a critical issue in assessing power quality in an all-electric ship. Standard signal analysis techniques for regular harmonics are not immediately applicable to interharmonics due to their small amplitude and uncertain frequency of occurrence. Hence, we propose the use of alternative polyspectral analysis techniques such as higher-order spectra (the cross bispectrum/bicoherence) for the detection and analysis of the ASD-generated interharmonics. First, we develop the interharmonic application specific definitions of the cross bispectrum and the cross bicoherence. The statistical characteristics and frequency domain symmetries are also investigated. We apply the modified cross bispectrum to interharmonic detection problems. Due to their small amplitudes, the detection of interharmonics is sensitive to many undesirable factors such as spectral leakage and measurement error. Our analysis results demonstrate that the detection performance of the conventional DFT-based method is seriously degraded in the presence of noise. Hence, we develop a constant false alarm rate (CFAR) interharmonic detector based on the modified cross bispectrum. Our analysis and experimental results show that our method can provide more robust detection performance than conventional methods in the presence of noise. We also develop an ASD condition monitoring method based on the cross bicoherence. The key idea is to diagnose the status of the load side of an ASD from observations made at the source side. In this dissertation, we apply our method to detection and analysis of phase imbalance at the load side of the ASD. Our experimental results demonstrate that the proposed method provides a unique interharmonic signature for detection and classification of asymmetric impedance associated with the phase imbalance. Furthermore, the proposed method shows a more sensitive detection performance compared to the conventional imbalance measurement method, which enables prognosis of potential faults. A novel quadratic phase coupling detector for a single data record with coherent interharmonics is developed. The traditional bicoherence definition fails when its ’phase randomization’ assumption is not satisfied. This assumption is not appropriate for certain applications such as continuous monitoring of rotating machines. Therefore, we propose a novel quadratic phase coupling detector and compare it with previous techniques. It is shown that our detector is superior to previous detectors at high SNRs, and can also address partially coherent cases which previous approaches could not properly address. Flicker issues related to interharmonics are also discussed. We present a newly found limitation of the current IEC flickermeter regarding detecting flicker caused by low frequency interharmonics. We also present observation results of flicker responses of various lamps including light-emitting-diode (LED) lamps. Our observation results confirm that compact fluorescent and LED lamps are sensitive to high frequency interharmonics, although the IEC flickmeter can not detect flicker caused by such interharmonics. Hence, we develop an alternative flicker detection method based on down-up sampling. Our experiment results show that our method can detect flicker regardless of the value of the interharmonic frequencies. Independent of interharmonic topics, we also present our additional achievement involving application of wavelet denoising techniques to network congestion monitoring problems. This was a collaboration with researchers at the Department of Computer Sciences in the University of Texas at Austin, and mainly completed before becoming engaged in the electric ship project. By applying wavelet techniques, we could drastically enhance shared congestion detection performance over previously proposed methods. / text

Wind is one of the most promising resources in the renewable energy portfolio. Still, the cost of electrical power produced by small wind turbines impedes the use of this technology, which can otherwise provide power to millions of homes in rural regions worldwide. To encourage their use, small wind turbines must convert wind energy more effectively while avoiding increased equipment costs. A variable ratio gearbox (VRG) can provide this capability to the simple low-cost fixed-speed wind turbine through discrete operating speeds. The VRG concept is based upon mature technology taken from the automotive industry and is characterized by low cost and high reliability. A 100 kW model characterizes the benefits of integrating a VRG into a fixed-speed stall-regulated wind turbine system. Simulation results suggest it improves the efficiency of the fixed-speed turbine in the partial-load region and has the ability to limit power in the full-load region where pitch control is often used. To maximize electrical production, mechanical braking is applied during the normal operation of the wind turbine. A strategy is used to select gear ratios that produce torque slightly above the maximum amount the generator can accept while simultaneously applying the mechanical brake, so that full-load production may be realized over greater ranges of the wind speed. Dynamic programming is used to establish the VRG ratios and an optimal control design. This optimization strategy maximizes the energy production while insuring that the brake pads maintain a predetermined service life. In the final step of the research, a decision-making algorithm is developed to find the gears that emulate the ratios found in the optimal control design. The objective is to match the energy level as closely as possible, minimize the mass of the gears, and insure that tooth failure does not occur over the design life of the VRG. Recorded wind data of various wind classes is used to quantify the benefit of using the VRG. The results suggest that an optimized VRG design can increase wind energy production by roughly 10% at all of the sites in the study. / text

In the design of high-hydrogen content gas turbines for power generation, flashback of the turbulent flame by propagation through the low velocity boundary layers in the premixing region is an operationally dangerous event. The high reactivity of hydrogen combined with enhanced flammability lim- its (compared to natural gas) promotes flame propagation along low-speed boundary layers adjoining the combustion walls. This work focuses on the simulation of boundary layer flashback using large-eddy simulations (LES). A canonical channel configuration is studied to assess the capabilities of LES and determine the modeling requirements for boundary layer flashback simulations. To extend this work to complex geometries, a new reactive low-Mach number solver has been written in an unstructured code. / text

There has been a significant increase in private vehicle ownership in the last decade leading to substantial increase in air pollution, depleting fuel reserves, etc. One of the alternatives known as battery operated electric vehicles (BEVs) has the potential to reduce carbon footprints due to lesser or no emissions and thus the focus on shifting people from gasoline operated vehicles (GVs) to BEVs has increased considerably recently. However, BEVs have a limited ‘range’ and takes considerable time to completely recharge its battery. In addition, charging stations are not as pervasive as gasoline stations. As a result a new fear of getting stranded is observed in BEV drivers, known as range anxiety. Range anxiety has the potential to substantially affect the route choice of a BEV user. It has also been a major cause of lower market shares of BEVs. Range anxiety is a latent feeling which cannot be measured directly. It is not homogenous either and varies among different socio-economic groups. Thus, a better understanding of BEV users’ behavior may shed light on some potential solutions that can then be used to improve their market shares and help in developing new network models which can realistically capture effects of varying EV adoptions. Thus, in this study, we analyze the factors that may impact BEV users’ range anxiety in addition to their route choice behavior using the integrated choice latent variable model (ICLV) proposed by Bhat and Dubey (2014). Our results indicate that an individual’s range anxiety is significantly affected by their age, gender, income, awareness of charging stations, BEV ownership and other category vehicle ownership. Further, it also highlights the importance of including disutility caused by distance while considering network flow models with combined GV and BEV assignment. Finally, a more concentrated effort can be directed towards increasing the awareness of charging station locations in the neighborhood to help reduce the psychological barrier associated with range anxiety. Overcoming this barrier may help increase consumer confidence, resulting in increased BEV adoption and ultimately will lead towards a potentially pollution-free environment. / text

We considered a non-centered parameterization of the standard random-effects model, which is based on the Cholesky decomposition of the variance-covariance matrix. The regression type structure of the non-centered parameterization allows to choose a simple, conditionally conjugate normal prior on the Cholesky factor. Based on the non-centered parameterization, we search for a parsimonious variance-covariance matrix by identifying the non-zero elements of the Cholesky factors using Bayesian variable selection methods. With this method we are able to learn from the data for each effect, whether it is random or not, and whether covariances among random effects are zero or not. An application in marketing shows a substantial reduction of the number of free elements of the variance-covariance matrix. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

This dissertation focuses on a variety of vadose zone processes that impact water table fluctuations. The development of vadose zone process conceptualization has been limited due to both the lack of recognition of the importance of the vadose zone and the absence of suitable field data. Recent studies have, however, shown that vadose zone soil moisture dynamics, especially in shallow water table environments, can have a significant effect on processes such as infiltration, recharge to the water table, and evapotranspiration. This dissertation, hence, attempts to elucidate approaches for modeling vadose zone soil moisture dynamics. The ultimate objective is to predict different vertical and horizontal hydrological fluxes. The first part of the dissertation demonstrates a new methodology using soil moisture and water table data collected along a flow transect. The methodology was found to be successful in the estimation of hydrological fluxes such as evapotranspiration, infiltration, runoff, etc. The observed dataset was also used to verify an exponential model developed to quantify the ground water component of total evapotranspiration. This analysis was followed by a study which analyzed the impact of soil moisture variability in the vadose zone on water table fluctuations. It was found that antecedent soil moisture conditions in the vadose zone greatly affected the specific yield values, causing a broad range of water table fluctuations for similar boundary fluxes. Hence, use of a constant specific yield value can produce inaccurate results. Having gained insight into the process of evapotranspiration and specific yield, a threshold based model to determine evapotranspiration and subsequent water table fluctuation was conceptualized and validated. A discussion of plant root water uptake and its impact on vadose zone soil moisture dynamics is presented in the latter half of this dissertation. A methodology utilizing soil moisture and water table data to determine the root water uptake from different sections of roots is also described. It was found that, unlike traditional empirical root water uptake models, the uptake was not only proportional to the root fraction, but was also dependent on the ambient soil moisture conditions. A modeling framework based on root hydraulic characteristics is provided as well. Lastly, a preliminary analysis of observed data indicated that, under certain field conditions, air entrapment and air pressurization can significantly affect the observed water table values. A modeling technique must be developed to correct such observations.

Two application applications of Fuzzy Logic to improve the performance of two controllers are presented. The first application takes a Sliding Mode Controller designed for chemical process to reject disturbances. A fuzzy element is added to the sliding surface to improve the controller performance when set point change affects the control loop; especially for process showing highly nonlinear behavior. This fuzzy element, , is calculated by means of a set of fuzzy rules designed based on expert knowledge and experience. The addition of improved the controller response because accelerate or smooth the controller as the control loop requires. The Fuzzy Sliding Mode Controller (FSMCr) is a completely general controller. The FSMCr was tested with two models of nonlinear process: mixing tank and neutralization reactor. In both cases the FSMCr improves the performance shown for other control strategies, as the industrial PID, the conventional Sliding Mode Control and the Stan dard Fuzzy Logic Controller. The second part of this research presents a new way to implement the Dynamic Matrix Control Algorithm (DMC). A Parametric structure of DMC (PDMC) control algorithm is proposed, allowing to the controller to adapt to process nonlinearities. For a standard DMC a process model is used to calculate de controller response. This model is a matrix calculated from the dynamic response of the process at open loop. In this case the process parameters are imbibed into the matrix. The parametric structure isolates the process parameters allowing adjust the model as the nonlinear process changes its behavior. A Fuzzy supervisor was developed to detect changes in the process and send taht [sic]information to the PDMCr. The modeling error and other parameters related were used to estimate those changes. Some equations were developed to calculate the PDMCr tuning parameter,lambda, as a function of the process parameters. The performance of PDMCr was tested using to model of nonlinear process and compare with the standard DMC; in most the cases PDMCr presents less oscillations and tracks with less error the set point. Both control strategies presented in this research can be implemented into industrial applications easily.

Alcohol consumption may affect labor market outcomes directly through a reduction in productivity and indirectly through human capital accumulation. However, empirical results from previous studies in the economics literature are mixed and inconclusive. While some researchers found negative effects of alcohol use on labor market outcomes, quite a few studies found either positive or insignificant effects. The purpose of this dissertation is to estimate causal effects of alcohol consumption on employment status. It uses three data sets previously unexploited for this purpose and attempts to eliminate any potential estimation problems from previous studies. The results show that previous problematic heavy drinking, i.e. clinically-defined alcohol abuse and/or dependence, has no significant direct effects, but has significant indirect effects on current employment propensity for both genders through human capital components, specifically educational attainment and health status. While general alcohol consumption has only an indirect effect on employment status for females, it has both direct and indirect effects on employment status for males, though the direct effect is very small.

M. Tech. Engineering: Mechanical. / Determines the highest energy savings which could be achieved by using variable air ventilation (VAV) strategy in cool processing, without affecting the performance of the cold room.

Successful development of the electric power grid of the future, hereinafter referred to as a smart grid, implicitly demands the capability to model the behavior, performance, and cost of distribution-level smart grid components. The modeling and simulation of such individual components, together with their overall interaction, will provide a foundation for the design and configuration of a smart grid. It is the primary intent of this thesis, to provide a basic insight into the energy transfer of various distribution-level components by modeling and simulating their dynamic behavior. The principal operations of a smart grid must be considered, including variable renewable generation, energy storage, power electronic interfaces, variable load, and plug-in electric vehicles. The methodology involves deriving the mathematical equations of components, and, using the MATLAB/Simulink environment, creating modules for each component. Ultimately, these individual modules may be connected together via a voltage interface to perform various analyses, such as the treatment of harmonics, or to acquire an understanding of design parameters such as capacity, runtime, and optimal asset utilization. / text