Thesis (Ph. D.)--University of Wisconsin--Madison, 1976. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 122-123).

Thesis (M.S.)--University of Wisconsin--Madison, 1963. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1957. / Typescript. Abstracted in Dissertation abstracts, v. 17 (1957) no. 11, p. 2552-2553. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 115-116).

Thesis (M.S.)--University of Wisconsin--Madison, 1964. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 83.

Thesis (M.S.)--University of Wisconsin--Madison, 1964. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 41.

Over the last decade, advancement of microelectronics has triggered a growing interest in ambient energy harvesting. Ambient energy can be found in various forms such as: thermoelectric, acoustic, solar, and mechanical vibrations. Most of the stated ambient energy sources have been thoroughly investigated. One of the relatively unexplored ambient energy sources is raindrop impact energy. Raindrop impact energy harvesting is achieved by converting the strain induced by an impinging raindrop on a piezoelectric beam into usable electrical energy. Most of the conducted research from the literature only considered single droplet impact on a piezoelectric beam. More interestingly, actual field test has yet to be conducted. These are the areas that the research will cover. A commercial piezoelectric beam (Mide-v25w) is utilised for this research. In this work, the piezoelectric beam is modelled as a distributed parameter system. To describe the post impact behaviours and water layer formed on the piezoelectric beam, impact coefficient and added mass coefficient are introduced for respective cases. Excitation models for single droplet, multiple droplet, artificial rain, and actual rain are developed. The models presented here were validated via experimental results. A hybrid bridge rectifier is designed and tested under actual rain. Experiment results showed that the half bridge rectifier is able to produce 95.12 % more energy than the full bridge rectifier during low voltage operation. From the actual rain experiment, the raindrop impact energy harvester was able to produce 1564 µJ energy over a rain period of 3539 s. The maximum instantaneous power generated by the piezoelectric was found to be 3.75 mW. This is higher compared the highest instantaneous power recorded in the literatures, which was 23 µW.

Current Non Destructing Testing (NDT) techniques for oil and gas pipeline inspection are accurate and reliable but there are limited numbers of continuous monitoring technique available that can automatically make real-time decisions on the status of the pipeline. Furthermore, most of the NDT methods are deployed at predetermined interval which can last for several months. Sudden onsets of defects are undetected and lead to pipeline failure and unscheduled shutdown. A reliable inspection method is required whereby the pipelines are monitored continuously and are able to provide the operators sufficient time to plan and organize shutdowns. In order to implement this, a continuous monitoring technique is needed which can detect defects automatically with minimal human intervention. Support Vector Machine (SVM) is a powerful machine learning technique for classification, however, the training phase requires batch data to find a model and this is not feasible for a continuous NDT system. This thesis proposes a novel method where the SVM training phase is able to find a model from the incremental dataset acquired from Long Range Ultrasonic Testing (LRUT) system. Results show that this method has comparable accuracy compared to the batch data method. Traditionally, SVM training data is labeled by an expert, however in a continuous monitoring NDT, it is not practical to assign an expert to label the continuously acquired data. Therefore, a novel unsupervised training technique is proposed. The technique is able to cluster the acquired data into a few clusters accurately. The performance of the proposed technique is compared to Self Organizing Map (SOM) method and shows better results. This thesis also proposes a novel method to implement a Genetic Algorithm (GA) as the Quadratic Programming (QP) solver in the SVM efficiently. Conventional SVM implement Sequential Minimal Optimization (SMO) which requires that the data be sparse for optimal operation. The performance of the method is evaluated and shows comparable result to traditional methods. As such, this thesis provides the framework to perform unsupervised continuous monitoring for oil and gas pipelines using LRUT in real time.

Thesis (M.B.A.)--Boston University

Over the last few years, significant advancements in the SiC power MOSFET fabrication technology has led to their wide commercial availability from various manufacturers. As a result, they have now transitioned from being a research activity to becoming an industrial reality. SiC power MOSFET technology offers great benefits in the electrical energy conversion domain which have been widely discussed and partially demonstrated. Superior material properties of SiC and the consequent advantages are both later discussed here. For any new device technology to be widely implemented in power electronics applications, it’s crucial to thoroughly investigate and then validate for robustness, reliability and electrical parameter stability requirements set by the industry. This thesis focuses on device characterisation of state-of-the-art SiC power MOSFETs from different manufacturers during short circuit and avalanche breakdown operation modes under a wide range of operating conditions. The functional characterisation of packaged DUTs was thoroughly performed outside of the safe operating area up until failure test conditions to obtain absolute device limitations. For structural characterisation, Infrared thermography on bare die DUTs was also performed with an aim to observe hotspots and/or degradation of the structural features of the device. The experimental results are also complemented by 2D TCAD simulation results in order to get a further insight into the underlying physical mechanisms behind failure during such operation regimes. Moreover, the DUTs were also tested for body diode characterisation with an aim to observe degradation and instability of electrical device parameters which may adversely affect the performance of the overall system. Such investigations are really important and act as a feedback to device manufacturers for further technological improvements in order to overcome the highlighted issues with an aim to bring about advancements in device design to meet the ever-increasing demands of power electronics.

Power electronics is an enabler for the low-carbon economy, delivering flexible and efficient control and conversion of electrical energy in support of renewable energy technologies, transport electrification and smart grids. Reduced costs, increased efficiency and high power densities are the main drivers for future power electronic systems, demanding innovation in materials, component technologies, converter architectures and control. Power electronic systems utilise semiconductor switches and energy storage devices, such as capacitors and inductors to realise their primary function of energy conversion. Presently, roughly 50% of the volume of a typical power electronic converter is taken up by the energy storage components, so reducing their weight and volume can help to reduce overall costs and increase power densities. In addition, the energy storage densities of inductors are typically much lower than those of capacitors, providing a compelling incentive to investigate techniques for improvement. The main goal of this research was to improve the design of an inductor in order to achieve higher energy densities by combining significantly increased current densities in the inductor windings with the ability to limit the temperature increase of the inductor through a highly effective cooling system. Through careful optimisation of the magnetic, electrical and thermal design a current density of 46 A/mm2 was shown to be sustainable, yielding an energy storage density of 0.537 J/ kg. A principal target for this enhanced inductor technology was to achieve a high enough energy density to enable it to be readily integrated within a power module and so take a step towards a fully-integrated “converter in package” concept. The research included the influence of the operating dc current, current ripple, airgap location and operating frequency on the inductor design and its resulting characteristics. High frequency analysis was performed using an improved equivalent circuit, allowing the physical structure of the inductor to be directly related to the circuit parameters. These studies were validated by detailed small-signal ac measurements. The large signal characteristics of the inductor were determined under conditions of triangular, high-frequency current as a function of frequency, current (flux) ripple amplitude and dc bias current (flux) and a model developed allowing the inductor losses to be predicted under typical power electronic operating conditions.