Wide-bandgap (WBG) semiconductor technology will largely replace silicon switching devices in the active power factor correction (PFC) circuit of a telecom power supply in the near future. Superior electrical characteristics of commercially available Gallium Nitride (GaN) devices make totem-pole PFC a clear winner over competing topologies in terms of efficiency. This thesis focuses on the development of a totem-pole PFC using state-of-the-art GaN devices for next-generation telecom power supplies. A detailed investigation of ac zero-crossings of this topology has successfully identified the rapid fluctuation in voltage across low-frequency MOSFET as the source of common-mode noise. An equivalent circuit accompanied by a set of equations correlate different circuit parameters with the noise generation. Challenges associated with current reversal near zero-crossings of a synchronous totem-pole PFC are studied and a formerly unreported source of common-mode noise generation around ac zero-crossings has been investigated in detail.
White matter structures make up functional connectivity of the brain. The ability to observe white matter in action will provide insight into both normal brain function, as well as diseases characterized by loss of white matter integrity. Detection of functional magnetic resonance imaging (fMRI) activation in white matter is has been increasingly reported despite historically being controversial. The majority of development work to-date has used high-field MRI and specialized pulse sequences. In the current study, we utilized 3T MRI and a commonly applied gradient echo (GRE) echo-planar imaging (EPI) sequence to probe the robustness of fMRI activation using conventional clinical conditions. Functional activity was stimulated in target regions of interest within the corpus callosum, using an established visual-motor interhemispheric transfer task. The results confirmed that it was possible to detect white matter fMRI activation at the group level (N = 13, healthy individuals). Individual analyses revealed that 8 of the 13 individuals showed white matter activation in the body of the corpus callosum. Overall, the group results replicated prior 4 T MRI studies, but showed a lower percentage of individuals with activation. The findings support the concept that while white matter activation is detectable, the activation levels are close to thresholds used for routine 3 T MRI studies. Furthermore, by applying alternate hemodynamic response functions during analysis, larger clusters of activation were seen at the group-level
X-ray computed tomography (XCT), a non-destructive technique, is proposed for three-dimensional, multi-length scale characterization of complex failure modes in fuel cell electrodes. Similar to medical CT scanners, laboratory XCT enables low-intensity X-ray imaging of a specimen at different incident angles followed by reconstruction into three-dimensional views. Fuel cell materials are compatible with this technique as they are sufficiently transparent to X-rays. In this thesis, electrode failures are analyzed by comparative tomography data sets for conditioned beginning of test (BOT) and degraded end of test (EOT) membrane electrode assemblies subjected to cathode degradation. Cracks and thickness of the cathode catalyst layer (CCL) are analyzed at the micro length scale, followed by a complementary nano length scale analysis of the fine porous structure. Additionally, a novel image processing based technique is developed for nano scale segregation of pore, ionomer, and Pt/C dominated voxels in the degraded CCL. The results of this work reveal several failure modes of catalyst layers including but not limited to carbon corrosion, Pt agglomeration, and Pt migration. In summary, XCT based multi-length scale analysis enables detailed information needed for comprehensive understanding of the complex failure modes observed in fuel cell electrodes.
Waste heat-driven adsorption cooling systems (ACS) are potential replacements for vapor compression refrigeration cycles in vehicle air conditioning (A/C) applications. Working pairs in an ACS are a combination of an adsorbent material (e.g., zeolite and silica gel), and an adsorbate (e.g., water and methanol). Most of these materials are non-toxic, non-corrosive, non-ozone depleting, and inexpensive. Besides, an ACS operates quietly and valves are its only moving parts. However, the bulkiness and heavy weight of ACS are major challenges facing commercialization of these environmentally friendly systems.The focus of this research is to develop a proof-of-concept ACS with high specific cooling power for vehicle A/C applications. As such, this Ph.D. dissertation is divided into three main parts: (i) adsorbent material characterization, (ii) adsorber bed design, and (iii) ACS design. In-depth analytical and thermodynamic cycle models are developed to understand the phenomena in adsorption process, adsorber bed and ACS. Also, a modular two-adsorber bed ACS equipped with thermocouples, pressure transducers and flow meters is designed and built for the first time at the Laboratory for Alternative Energy Conversion (LAEC) to test different adsorbent materials, adsorber beds, condensers, and evaporators under different operating conditions. A low-operating pressure evaporator with capillary-assisted tubes is designed and installed on the testbed to improve the performance of ACS. In addition, a novel expansion valve and control valves are proposed to simplify the control system and reduce the complexity of ACS for vehicle A/C applications. Using this ACS testbed with enhanced performance, a specific cooling power of 150 W/kg of dry adsorbent is achieved.
Heating, Ventilation, and Air Conditioning (HVAC) systems are the main target for energy and load management in residential buildings due to their high energy consumption. The role of Thermostats is to automatically control the HVAC systems while users accommodate their everyday schedules and preferences. The initiatives such as demand response (DR) programs, Time of Use (TOU) rates, and real-time pricing (RTP) are often applied by smart grids to encourage customers in order to reduce consumption during peak demand periods. However, it is often a hassle for residential users to manually reprogram their thermostats in response to smart grid initiatives and/or environmental conditions that vary over time. In this thesis, the research endeavors are dedicated to bring forward a novel autonomous and adaptable system for control of residential HVAC systems which results in an “Adaptive Smart Thermostat”. To do so, a “House Simulator” is developed in MATLAB-GUI with thoughtful consideration as a tool to facilitate the study of energy management for residential HVAC systems in smart grids. The simulator also assists in the implementation and verification of our proposed techniques under different scenarios such as RTP, various user schedules, and different environmental conditions. Furthermore, a new algorithm using rule-based fuzzy logic and wireless sensors capabilities for residential demand-side management is developed. The algorithm is augmented into existing programmable communicating thermostats (PCT) in order to enhance the learning capability of PCTs during participation in DR programs. The conducted results show that the PCT equipped with our approach, versus existing PCTs, performs better with respect to energy and cost saving, while maintaining user thermal comfort. The achieved results led us to develop a novel “Autonomous Smart Thermostat” that is the result of a synergy of supervised fuzzy logic learning, wireless sensor capabilities, and smart grid incentives. The results demonstrate that the developed thermostat autonomously adjusts the set point temperatures in ASHRAE thermal comfort-zone, while not ignoring the energy conservation aspects. However, in cases that the user overrides the decision(s) made by autonomous system, a novel “Adaptive Fuzzy Learning Model” utilizing wireless sensor capabilities is developed in order to learn and adapt to user new preference and schedule changes based on rulebased fuzzy logic learning. The results show that the developed system is adaptable, smart, and capable of intelligent zoning control while it improves energy management in residential buildings without jeopardizing thermal comfort.
In this thesis, the development of a novel optical tweezer is described. Additionally, alterations in the mechanical properties of cancer cells associated with metastatic transformation was characterized using this technology. Cell mechanical properties can be utilized as a quantitative measure for understanding the pathophysiological behavior of cells and evaluating pharmacological treatments that modify the cell structure. Thus, an oscillating optical tweezer capable of applying time varying force and manipulating the cell cytoskeleton was developed in order to measure the mechanical properties and structural changes of single epithelial cancer cells and blood cancer cells. Employing this device would be beneficial in differentiating between normal, cancer and metastatic cancer cells and evaluating the effectiveness of different chemotherapeutic approaches. To this end, the developed tool was utilized to conduct a systematic study of the mechanical properties of human epithelial cancer cells by mimicking the condition that causes cancer cell invasiveness and tumour cell transformation. Different signaling pathways that modulate actin organization under hypoxia were studied via analyzing the biophysical properties of cancer cells and quantifying cytoskeleton rearrangement employing the oscillating optical tweezer. It was demonstrated the optical tweezer is a novel, rapid and reliable tool for the identification and characterization of cancer cells and for evaluating therapeutic performance. Finally, a sensitivity study was applied using COMSOL to evaluate the effect of cell-bead geometries on cell mechanical responses for different cell types and optical tweezer experiments.
In Micro-Electro-Mechanical Systems packages, sealing pressure is one of the most important indicators of packaging quality. Traditional hermeticity testing methods are expensive and inconvenient. Solution for in-package pressure monitoring has long been appealing. Pirani sensor is a commonly used pressure sensor that can be integrated into Micro-Electro-Mechanical Systems packages. Our team is developing a hermetic packaging process for extremely sensitive and low noise accelerometers. A eutectic package sealing process is developed and evaluated. To verify the stability of environment inside the package, a lowcost, process flow compatible, space saving bondwire Pirani sensor has been explored. The sensing principle is based on resistance change of the filament is a function of pressure under constant electrical power. The feasibility of using the bondwire Pirani sensor has been thoroughly discussed. A novel four point measurement set up is implemented to achieve the accurate low resistance measurement. The bondwire Pirani sensor has a dynamic range from 0.1 Torr to about 50 Torr and is compatible with any micro-system such as resonators, gyroscopes, micro-mirrors, and micro-display systems among others. The sensor is applied to our own packaging process as pressure sensing element to detect pressure change. Long-term pressure stability for sealed packages is also measured by the bondwire Pirani sensor.
The objective of this thesis is to describe the implementation of an innovative agent-based architecture of controllers for stand-alone DC microgrids. The controllers have to regulate voltage to the required level and manage energy flow in the system. In addition, they should maintain a deterministic time frame on the order of a few tens of milliseconds for a system with tens of power electronic converters with no limitation in the number of events which might happen concurrently. Optimal power sharing ensures minimum transmission and distribution loss while enforcing constraints such as generators’ capacity limits. Multiple agents take part in the process to determine optimum power sharing for the converters. The thesis compares system complexity using numerical analysis of different distributed lookup algorithms based on defined metric values for a standalone DC microgrid including 32 converters. The numerical analysis results aid in choosing a publish-subscribe model as the most efficient and scalable solution for developing agent technology for standalone DC microgrids. Application of publish-subscribe agent-based control is presented for real-time coordination of power converters in a defined microgrid. To test the design, a sample DC shipboard microgrid with eight converters is used as a case study. Results of implementing the agent-based publish-subscribe control system using Java Agent DEvelopment Framework (JADE) are illustrated in the thesis. Simulation results affirm the accuracy of numerical analysis results.
Heavy duty fuel cells used in transportation system applications such as transit buses expose the fuel cell membranes to conditions that can lead to lifetime-limiting membrane failure via combined chemical and mechanical degradation. Highly durable membranes and reliable predictive models are therefore needed in order to achieve the heavy duty fuel cell lifetime target of 18,000 h. In the present work, an empirical membrane lifetime model was developed based on laboratory data from a suite of accelerated membrane durability tests. The model considers the effects of cell voltage, temperature, oxygen concentration, humidity cycling, humidity level, and platinum in the membrane using inverse power law and exponential relationships within the framework of a general log-linear Weibull life-stress statistical distribution. The obtained model is capable of extrapolating the membrane lifetime from accelerated test conditions to use level conditions during field operation. Based on typical conditions for the Whistler, British Columbia fuel cell transit bus fleet, the model predicts a stack lifetime of 17,500 h and a membrane leak initiation time of 9,200 h. Validation performed with the aid of a field operated stack confirmed the initial goal of the model to predict membrane lifetime within 20% of the actual operating time.
MagnetoRheological (MR) dampers are controllable shock absorption devices that are vastly used in vibration and motion control applications. MR dampers can provide an adjustable damping constant that can be used to generate controlled damping force for vibration and shocks control. In this research different methods of reducing the weight and power consumption of MR dampers are investigated. First, optimal design of MR dampers using a Genetic Algorithm is presented. Next design of novel magnetic circuits and damper mechanisms for reducing the weight and power consumption is investigated and a new low-power, low-weight mechanism is proposed. Experimental results for the proposed MR damper are further presented and compared with the results obtained from a conventional MR damper.