Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Open top chambers and infrared lamps : a comparison of heating efficacy and CO₂/CH₄ dynamics in a Lake Superior coastal peatland

Experimental warming provides a method to determine how an ecosystem will respond to increased temperatures. Northern peatland ecosystems, sensitive to changing climates, provide an excellent setting for experimental warming. Storing great quantities of carbon, northern peatlands play a critical role in regulating global temperatures. Two of the most common methods of experimental warming include open top chambers (OTCs) and infrared (IR) lamps. These warming systems have been used in many ecosystems throughout the world, yet their efficacy to create a warmer environment is variable and has not been widely studied. To date, there has not been a direct, experimentally controlled comparison of OTCs and IR lamps. As a result, a factorial study was implemented to compare the warming efficacy of OTCs and IR lamps and to examine the resulting carbon dioxide (CO2) and methane (CH4) flux rates in a Lake Superior peatland. IR lamps warmed the ecosystem on average by 1-2 #°C, with the majority of warming occurring during nighttime hours. OTC's did not provide any long-term warming above control plots, which is contrary to similar OTC studies at high latitudes. By investigating diurnal heating patterns and micrometeorological variables, we were able to conclude that OTCs were not achieving strong daytime heating peaks and were often cooler than control plots during nighttime hours. Temperate day-length, cloudy and humid conditions, and latent heat loss were factors that inhibited OTC warming. There were no changes in CO2 flux between warming treatments in lawn plots. Gross ecosystem production was significantly greater in IR lamp-hummock plots, while ecosystem respiration was not affected. CH4 flux was not significantly affected by warming treatment. Minimal daytime heating differences, high ambient temperatures, decay resistant substrate, as well as other factors suppressed significant gas flux responses from warming treatments.

Integrated solar energy and absorption cooling model for HVAC (heating, ventilating, and air conditioning) applications in buildings

The demands in production and associate costs at power generation through non renewable resources are increasing at an alarming rate. Solar energy is one of the renewable resource that has the potential to minimize this increase. Utilization of solar energy have been concentrated mainly on heating application. The use of solar energy in cooling systems in building would benefit greatly achieving the goal of non-renewable energy minimization. The approaches of solar energy heating system research done by initiation such as University of Wisconsin at Madison and building heat flow model research conducted by Oklahoma State University can be used to develop and optimize solar cooling building system. The research uses two approaches to develop a Graphical User Interface (GUI) software for an integrated solar absorption cooling building model, which is capable of simulating and optimizing the absorption cooling system using solar energy as the main energy source to drive the cycle. The software was then put through a number of litmus test to verify its integrity. The litmus test was conducted on various building cooling system data sets of similar applications around the world. The output obtained from the software developed were identical with established experimental results from the data sets used. Software developed by other research are catered for advanced users. The software developed by this research is not only reliable in its code integrity but also through its integrated approach which is catered for new entry users. Hence, this dissertation aims to correctly model a complete building with the absorption cooling system in appropriate climate as a cost effective alternative to conventional vapor compression system.

Heat transfer in microwave heating

Heat transfer is considered as one of the most critical issues for design and implement of large-scale microwave heating systems, in which improvement of the microwave absorption of materials and suppression of uneven temperature distribution are the two main objectives. The present work focuses on the analysis of heat transfer in microwave heating for achieving highly efficient microwave assisted steelmaking through the investigations on the following aspects: (1) characterization of microwave dissipation using the derived equations, (2) quantification of magnetic loss, (3) determination of microwave absorption properties of materials, (4) modeling of microwave propagation, (5) simulation of heat transfer, and (6) improvement of microwave absorption and heating uniformity. Microwave heating is attributed to the heat generation in materials, which depends on the microwave dissipation. To theoretically characterize microwave heating, simplified equations for determining the transverse electromagnetic mode (TEM) power penetration depth, microwave field attenuation length, and half-power depth of microwaves in materials having both magnetic and dielectric responses were derived. It was followed by developing a simplified equation for quantifying magnetic loss in materials under microwave irradiation to demonstrate the importance of magnetic loss in microwave heating. The permittivity and permeability measurements of various materials, namely, hematite, magnetite concentrate, wüstite, and coal were performed. Microwave loss calculations for these materials were carried out. It is suggested that magnetic loss can play a major role in the heating of magnetic dielectrics. Microwave propagation in various media was predicted using the finite-difference time-domain method. For lossy magnetic dielectrics, the dissipation of microwaves in the medium is ascribed to the decay of both electric and magnetic fields. The heat transfer process in microwave heating of magnetite, which is a typical magnetic dielectric, was simulated by using an explicit finite-difference approach. It is demonstrated that the heat generation due to microwave irradiation dominates the initial temperature rise in the heating and the heat radiation heavily affects the temperature distribution, giving rise to a hot spot in the predicted temperature profile. Microwave heating at 915 MHz exhibits better heating homogeneity than that at 2450 MHz due to larger microwave penetration depth. To minimize/avoid temperature nonuniformity during microwave heating the optimization of object dimension should be considered. The calculated reflection loss over the temperature range of heating is found to be useful for obtaining a rapid optimization of absorber dimension, which increases microwave absorption and achieves relatively uniform heating. To further improve the heating effectiveness, a function for evaluating absorber impedance matching in microwave heating was proposed. It is found that the maximum absorption is associated with perfect impedance matching, which can be achieved by either selecting a reasonable sample dimension or modifying the microwave parameters of the sample.

Fabrication of nanoparticles by short-distance sputter deposition

During the past decades, tremendous research interests have been attracted to investigate nanoparticles due to their promising catalytic, magnetic, and optical properties. In this thesis, two novel methods of nanoparticle fabrication were introduced and the basic formation mechanisms were studied. Metal nanoparticles and polyurethane nanoparticles were separately fabricated by a short-distance sputter deposition technique and a reactive ion etching process. First, a sputter deposition method with a very short target-substrate distance is found to be able to generate metal nanoparticles on the glass substrate inside a RIE chamber. The distribution and morphology of nanoparticles are affected by the distance, the ion concentration and the process time. Densely-distributed nanoparticles of various compositions are deposited on the substrate surface when the target-substrate distance is smaller than 130mm. It is much less than the atoms’ mean free path, which is the threshold in previous research for nanoparticles’ formation. Island structures are formed when the distance is increased to 510mm, indicating the tendency to form continuous thin film. The trend is different from previously-reported sputtering method for nanoparticle fabrication, where longer distance between the target and the substrate facilitates the formation of nanoparticle. A mechanism based on the seeding effect of the substrate is proposed to interpret the experimental results. Secondly, in polyurethane nanoparticles’ fabrication, a mechanism is put forward based on the microphase separation phenomenon in block copolymer thin film. The synthesized polymers have formed dispersed and continuous phases because of the different properties between segments. With harder mechanical property, the dispersed phase is remained after RIE process while the continuous phase is etched away, leading to the formation of nanoparticles on the substrate. The nanoparticles distribution is found to be affected by the heating effect, the process time and the plasma power. Superhydrophilic property is found on samples with these two types of nanoparticles. The relationship between the nanostructure and the hydrophilicity is studied for further potential applications.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

COMPARISON OF NON-HEATING PALEOINTENSITY TECHNIQUES USING BASALTS FROM LEMPTÉGY VOLCANO, FRANCE AND SYNTHETIC MAGNETITE-BEARING SAMPLES

Data of the strength of Earth’s magnetic field (paleointensity) in the geological past are crucial for understanding the geodynamo. Conventional paleointensity determination methods require heating a sample to a high temperature in one or more steps. Consequently, many rocks are unsuitable for these methods due to a heating-induced experimental alteration. Alternative non-heating paleointensity methods are investigated to assess their effectiveness and reliability using both natural samples from Lemptégy Volcano, France, and synthetic samples. Paleointensity was measured from the natural and synthetic samples using the Pseudo-Thellier, ARM, REM, REMc, REM’, and Preisach methods. For the natural samples, only the Pseudo-Thellier method was able to produce a reasonable paleointensity estimate consistent with previous paleointensity data. The synthetic samples yielded more successful estimates using all the methods, with the Pseudo-Thellier and ARM methods producing the most accurate results. The Pseudo-Thellier method appears to be the best alternative to the heating-based paleointensity methods.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.