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In this dissertation a new time domain approach for the determination of material properties such as the complex permittivity and the complex permeability in a stripline geometry is presented. The new technique uses both Time Domain Reflectometry (TDR) and Time Domain Transmission (TDT) measurements for determining an optimum frequency dependent lossy transmission line model for the stripline under test. The optimization is done in the time domain by comparing the experimental TDR and TDT response waveforms with the simulated ones using a non-linear least squares fit. The conventional optimization algorithms have shown to be inefficient in this specific application. In this dissertation an efficient optimization algorithm which has been developed to suit this application is also presented. In general, the material properties in a stripline under test are related with the geometrical parameters of the line through complicated integral expressions. Using the proposed approach, the use of complicated integral expressions are avoided. The material properties such as the complex permittivity and the complex permeability are determined from the optimum lossy transmission line model. For this purpose, the frequency behavior of the line parameters have to be known beforehand in the form of causal mathematical models. The literature survey shows that, no causal model exists for the complex permittivity of thick film and polymer materials. The dissertation proposes a new causal model for this purpose. / Ph. D.

Parametric design models were created to optimize cable sensitivities in a structural health-monitoring system. Experiments were also conducted to determine the sensitivity of a working system. The system consists of time domain reflectometry (TDR) signal processing equipment and specially designed sensing cables. The TDR equipment sends a high-frequency electric pulse (in the gigahertz range) along the sensing cable. Any change in electric impedance along the cable reflects some portion of the electric pulse back to the TDR equipment. The time delay, amplitude, and shape of the reflected pulse provides the means to respectively locate, determine the magnitude, and indicate the nature of the change in impedance. The change in the sensing cable impedance may be caused by cable elongation (change in resistance), shear deformation (change in capacitance), corrosion of the cable or the materials around the cable (change in inductance), etc. The sensing cables are an essential part of the health-monitoring system because the cable design parameters determine the cable impedance sensitivity to structural changes. By using parametric design models, the optimum cable parameters can be determined for specific cases and used to select or design an appropriate cable. Proof-of-concept and resolution experiments were also conducted to provide, respectively, verification and sensitivity of the system. / Master of Science

Effective and efficient system identification techniques for discrete, time domain, linear, MIMO, heavily damped modal systems from input/output sequences have been developed and simulated. This will facilitate a better understanding of the possible errors in the estimated model and lead to a more accurate compensator and estimator design. Three different time domain system identification algorithms have been developed in this work. The first algorithm determines the state space model in a pseudo controllable/observable canonical form. The second method is a computational simplification of the Eigensystem Realization Algorithm using pseudo observability and controllability indices. The third algorithm tested is the Pseudo Linear Identification Algorithm (PLID). The PLID algorithm is extensively tested on simulated data. This algorithm is also applied to identify a rectangular plate which gives a realistic idea of the identification capabilities of the PLID algorithm to real measured data. / Master of Science

Renewable energy is a critical component in combating climate change. Ocean wave energy is a source of renewable energy that can be harvested using Wave Energy Converters (WECs). One such WEC is the floating Oscillating Water Column (OWC), which has been successfully field tested and warrants further exploration. This research implements a publicly accessible code in MatLab and SimuLink to simulate the dynamics of a floating OWC in the time domain. This code, known as the Floating OWC Iterative Time Series Solver (FlOWCITSS), uses the pressure distribution model paired with state space realization to capture the internal water column dynamics of the WEC and estimate pneumatic power generation. Published experimental results of floating moored structures are then used to validate FlOWCITSS. While FlOWCITSS seemed to capture the period and general nature of the heave, surge, and internal water column dynamics, the magnitude of the response sometimes had errors ranging from 1.5% −37%. This error could be caused by the modeling techniques used, or it could be due to uncertainties in the experiments. The presence of smaller error values shows potential for FlOWCITSS to achieve consistently higher fidelity results as the code undergoes further developments. To demonstrate the use of FlOWCITSS, geometry variations of a Backward Bent Duct Buoy (BBDB) are explored for a wave environment and mooring configuration. The reference model from Sandia National Labs, RM6, performed significantly better than a BBDB with an altered stern geometry for a 3 second wave period, indicating that stern geometry can have a significant impact on pneumatic power performance. / Master of Science / Renewable energy is a critical component in combating climate change. Ocean wave energy is a source of renewable energy that can be converted into electricity using Wave Energy Converters (WECs). One such WEC is the floating Oscillating Water Column (OWC), which has been successfully field tested and warrants further exploration. Floating OWCs are partially submerged floating structures that have an internal chamber which water oscillates in. The motions of the water displace air inside this chamber, causing the air to be forced through a high speed turbine, which generates electricity. This research develops a publicly accessible code using MatLab and SimuLink to evaluate the motions and power generation capabilities of floating OWCs. This code is then validated against physical experiments to verify its effectiveness in predicting the device's motions. This publicly accessible code, known as the Floating OWC Iterative Time Series Solver (FlOWCITSS), showed error ranging from 1.5 % - 37% for the most important motions that are relevant to energy harvesting and power generation. These errors could be caused by the numerical models used, or uncertainties in experimental data. The presence of smaller error values shows potential for FlOWCITSS to achieve consistently higher fidelity results as the code undergoes further developments. To demonstrate the use of FlOWCITSS, geometry variations of floating OWCs are explored.

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Microwave circuits play an important role in wireless communications. Microwave circuits are made up of many components, including passive devices. Passive devices include resistors, capacitors, inductors, and transformers. These passive devices are used to help lower noise and to allow signals to pass effectively though the circuit. The Finite-Difference Time-Domain (FDTD) method is a powerful tool used to analyze the electromagnetic properties of objects. FDTD can be used to model the electromagnetic behavior of microwave circuits. Important electromagnetic properties such as S-parameters, effective dielectric constant, phase constant, and the movement of the electric and magnetic fields through the circuit can be extracted from a single FDTD simulation. Also of particular interest is the frequency response of a circuit, which can be determined by taking the Fourier transform of the time-domain results. FDTD is an efficient way to determine many electromagnetic characteristics of a microwave circuit. FDTD offers a programmer much freedom in assigning the shape, properties, and size of a structure that is to be analyzed. Also, FDTD is more robust than other electromagnetic analysis methods due to the algorithm it uses in finding the electric and magnetic fields. These useful aspects of FDTD make it the top choice in analyzing passive devices in microwave circuits. The thesis involves the electromagnetic analysis of passive structures that are used in RF IC's. Circuits that will be analyzed include a low-pass filter, antenna, and coplanar waveguides. This leads to the ultimate goal of the thesis, the analysis of a spiral inductor that is to be used in an RF IC. Spiral inductors are used as passive devices in planar microwave circuits. Spiral inductors can take on several shapes, with the square being the shape of interest in this thesis. FDTD will be used to analyze the electromagnetic properties of the spiral inductor, with the inductance being extracted from the values of the electromagnetic variables calculated during the simulation. Two types of spiral inductors will be analyzed; a three-turn spiral inductor and an eight-turn spiral inductor. Both types of spiral inductor will be analyzed on silicon and gallium arsenide dielectric substrates. The inductance values extracted from the spiral inductor can be used to determine how the inductor will behave as part of a microwave circuit. Inductor behavior is critical in that the performance of an RF IC will be affected if inductors are not performing optimally.