PHD, Kent State University, 2022, College of Arts and Sciences / Department of Physics

Compact stars (CSs) are the remnants of “dead” stars that were too small to form black holes; the category includes both white dwarfs (WDs) and neutron stars (NSs). To produce a full description of any magnetized compact star requires solving Einstein's equations in unison with Maxwell's equations. However, when putting these two sets of equations together, there is an additional degree of freedom that requires the inclusion of the equation of state (EOS) of the stellar matter in question. The most notable difference between CSs and other stars is that CSs consist of degenerate fermion matter. Fermionic matter exists in a degenerate state when the temperature is low compared to the Fermi energy. Such states arise due to the Pauli exclusion principle, which states that no two identical fermions (particles with half integer spin) in the same quantum system may inhabit the same quantum state. In the case of WDs, this degeneracy is caused solely by electrons; whereas, in NSs, the degeneracy is in several species of particles including neutrons and protons, but also more “exotic” baryons, such as Lambdas, Sigmas, and Cascades. In the grand canonical ensemble, the stellar EOS is typically expressed as the relation between the total energy density of a gas of particles and their pressure. It is calculated using thermodynamics with, in the NS case, an additional contribution from the strong nuclear force, which must be modeled. Due to computational difficulty, the EOS is often calculated in a simplified way, assuming that one aspect or another is not significant. As such, EOSs exist with temperature effects or with magnetic field effects, but not with both. For example, higher temperatures (without additional degrees of freedom) lead to higher pressures at the same energy density; the EOS is “stiffer.” Magnetic fields lead to a pressure anisotropy and Landau quantization, which gives rise to De Haas-Van Alphen oscillations in the EOS. This thesis breaks new ground by sim (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2022, Electrical Engineering

This research proposes a direct voltage control approach for electric motors, including the single-stage converter topology and the control algorithms. The proposed motor drive system achieves smooth output voltage waveforms for phase excitations and utilizes them to extend the drive capability besides improving the torque ripple, noise, and vibration performance. Applicable to various motor types, the direct voltage control (DVC) is mainly investigated for driving switched reluctance motor (SRM) in the scope of this thesis. Different voltage regulation-based control algorithms are studied. Since the capability of shaping the phase voltage precisely allows control of any motor variables, this ability enables regulating the phase currents, flux linkages, and phase voltages to obtain superior performance. A finite element analysis (FEA) is performed to characterize the motor for building a dynamic simulation model for an SRM. The developed DVC and the conventional control are simulated using this machine model in comparison to each other. A new dual polarity power converter (DPC) is modeled, which can buck and boost the DC bus voltage and provides a variable voltage generation (VVG). The DPC can process power in both directions and provide a variable voltage in both positive and negative polarities at the motor windings. Following the DPC design process, power boards and gate driver boards are manufactured and populated as modular systems for individual motor phases. The developed converter model is customized and sized to construct a motor drive for the targeted operating conditions of the investigated SRM. It includes a control board to enable the 3-phase operation and a single DC bus as the power source for all three modular power converters. A resistive load setup is built to test the converter's performance. After verifying the DPC's performance for its designed load conditions and position-dependent dynamics, the motor tests are performed. The motor tests (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Physics

The success of modern digital electronics relies on compartmentalizing logical functions into individual gates, and controlling their order of operations via a global clock. In the absence of such a timekeeping mechanism, systems of connected logic gates can quickly become chaotic and unpredictable -- exhibiting analog, asynchronous, autonomous dynamics. Such recurrent circuitry behaves in a manner more consistent with neural networks than digital computers, exchanging and conducting electricity as quickly as its hardware allows. These physics enable new forms of information processing that are faster and more complex than clocked digital circuitry. However, modern electronic design tools often fail to measure or predict the properties of large recurrent networks, and their presence can disrupt other clocked architectures. In this thesis, I study and apply the physics of complex networks of self-interacting logic gates at sub-ns timescales. At a high level, my unique contributions are: 1. I derive a general theory of network dynamics and develop open-source simulation libraries and experimental circuit designs to re-create this work; 2. I invent a best-in-class digital measurement system to experimentally analyze signals at the trillionth-of-a-second (ps) timescale; 3. I introduce a network computing architecture based on chaotic fractal dynamics, creating the first `physically unclonable function' with near-infinite entropy. In practice, I use a digital computer to reconfigure a tabletop electronic device containing millions of logic gates (a field-programmable gate array; FPGA) into a network of Boolean functions (a hybrid Boolean network; HBN). From within the FPGA, I release the HBN from initial conditions and measure the resulting state of the network over time. These data are transferred to an external computer and used to study the system experimentally and via a mathematical model. Existing mathematical theories and FPGA simulation tools produce in (open full item for complete abstract)

Master of Sciences (Engineering), Case Western Reserve University, 2022, EECS - Electrical Engineering

Atrial fibrillation is a common cardiac condition which can place the patient at risk for many serious medical issues. Current interventional procedures employ cardiac ablation catheters guided using x-ray fluoroscopy imaging, which generates restricted two-dimensional images of the heart, and exposes the patient to a high dose of radiation. Three-dimensional catheter position data can be obtained and radiation exposure can be mitigated by using Magnetic Resonance Imaging (MRI) for this procedure. The magnetic field of the MRI machine can be strategically leveraged to steer and actuate a robotic ablation catheter, by energizing small embedded electromagnetic coils within the catheter tip. These coils however, may undesirably interact with the MRI machine's rotating radio-frequency (RF) magnetic field, potentially leading to excessive heating of the catheter or power supply damage. This thesis aims to characterize the RF response of actuation coils used in a novel MRI guided catheter system, and design an actuation coil set prototype which can safely operate in the MRI environment. The proposed final actuation coil set consists of 3 coils wound over the catheter body, and aims to improve the RF behavior of the coil set by implementing improved design elements such as a new winding pattern, wire gauge variation, and utilization of capacitors within the system. The final prototype presented successfully meets the required standards and is able to perform desired actuations.

Doctor of Philosophy, Case Western Reserve University, 2022, EECS - Electrical Engineering

This thesis shows that permanent magnets and electromechanical control systems can enable power-efficient, high-sensitivity, low-noise modalities for spectroscopy and wireless communication. Specifically I present two examples. The first is a radio frequency (RF) spectrometer which uses a detector cooled to 77 K to maximize measurement sensitivity, coupled with a minimally-intrusive network of active duplexers and mechanical contact switches to realize a reconfigurable series/parallel resonant network. I present a receiver which combines the highly sensitive analog frontend instrumentation with a mixed signal embedded system to monitor and control secondary processes. The cryogenic system increases the measurement signal to noise ratio (SNR) by a factor of 10×. The second example is an extremely low frequency (ELF) communication system which uses a mechanically-rotated dipole instead of an electrical antenna to generate the oscillating field of the transmitter. I show how a synchronous digital controller can maintain stable control over the dynamic process while a complementary embedded system modulates the set-point and monitors the channel. My transmitter achieves a power efficiency 7.6× greater than an equivalent electrical antenna in a device small enough to be moved by one person. I carry the transmitter into a cave and demonstrate cave-to-surface message transmission through 15 m of rock and frozen soil in a real-world field test. I present each solution in the context of scientific and human motivation, and explore tradeoffs required to achieve design goals. Emphasis is also placed on whether there exists a position of harmony and balance, where one may reasonably proclaim the optimum implementation has been achieved. The receiver is relatively more complex than the transmitter in the case of RF spectroscopy. In the case of ELF communication it is the reverse.

Master of Science (M.S.), University of Dayton, 2021, Materials Engineering

Additive Manufacturing (AM) is a rapidly developing field that offers new possibilities for manufacturing with materials that are difficult to process with traditional manufacturing methods. This report will examine the application of selective laser melting in making magnetic cores out of Hiperco 50. The iron-cobalt family of alloys is known to offer the best magnetic properties of all soft magnetic materials but is extremely brittle. Additive manufacturing offers the opportunity to make high quality magnetic cores in unique geometries that traditional manufacturing is unable to replicate. To test the viability of this process three types of test specimens were built out of Hiperco 50 powder to examine key material properties. First 1 cm3 cube specimens were built to measure the density of the final parts, and they were also used to examine the porosity and microstructure. The second type of specimens were tensile bars, built in both vertical and horizontal orientations with respect to the build plate, to examine the mechanical properties of the final parts as well as the impact of build orientation. The final test specimens were magnetic toroids, comprised of cores to be wound with copper magnet wire and tested for magnetic permeability and remanence. Half of these specimens were also subjected to a final magnetic heat treatment cycle, which was the same as the cycle used for traditionally manufactured Hiperco 50 components, in order to determine the change in performance. These AM fabricated specimens showed a 1-5% decrease in density from traditionally manufactured Hiperco 50 parts, with the build parameters being the largest deciding factor of final density and porosity. These parts also had a poorly defined grain structure until subjected to a magnetic heat treatment. After undergoing the recommended heat-treatment, niobium precipitates were observed along the newly defined grain boundaries. However, there was a severe drop in mechanical performance, (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Electrical and Computer Engineering

The antenna pattern is an essential part of the design of RF systems and affects the performance and capabilities for many applications in communications, radar, and sensing. There are many applications which require specified antenna patterns with specific directivity, beamwidth, and sidelobe level (SLL). Single-element antennas usually have simple and specific patterns which are difficult to be shaped to meet more complicated pattern requirements. For instance, the popular parabolic reflector antenna uses a reflector which can be shaped to produce a desired radiation pattern with high directivity. However, it has a large structure and can only produce single fixed-beam patterns. On the other hand, array antennas consist of multiple antenna elements which together can be used to synthesize antenna patterns with narrower beams and lower sidelobes as compared to single-element antennas. More specifically, many applications which require high directivity, narrow beam patterns with low sidelobes include: (1) radars, which often use a narrow beam to detect targets for achieving a better angular resolution, higher signal-to-noise ratio (SNR), and low sidelobes to avoid ambiguity coming from signal returns from other directions; (2) modern cellular phone base stations which employ specially shaped beam patterns to provide uniform signal strength with the coverage area while minimizing radiation into the sky; (3) newest satellite communications/broadcasting systems which adopt spotlight beams to cover specific zones while reducing interference into neighboring areas for enhanced security and SNR. The first array antennas for producing shaped directive beam patterns were introduced during World War II for early radar systems using an array of dipole elements. The disadvantages of such a dipole array were that the dipole elements were large 3D objects requiring manual labor to produce and the design was difficult to use for higher frequency such as for X band or higher. (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2021, Electrical and Computer Engineering

Photonic integrated circuits (PICs) are poised to bring about a technological paradigm shift akin to the micro-electronics revolution of the late 20th century. Emerging applications include next generation telecommunication networks and data centers, quantum computers, autonomous vehicles, and lab-on-a-chip systems. Co-integration of photonics and electronics on the same chip enables advanced technologies by using high-speed electrical signals to control the properties of light such as intensity, wavelength, phase, polarization, and spatial distribution. To date, most photonic ICs operate with the fundamental quasi-traverse-electric or quasi-transverse-magnetic polarization, but lack dynamic polarization control capable of synthesizing arbitrary polarizations. Current integrated polarization controllers suffer from at least one of the following: insertion losses of up to 3 dB, inability to generate all polarizations, or narrow optical bandwidth. To overcome these limitations, we leverage silicon optical waveguides that exhibit Berry's phase, a topological effect that is inherently broadband and low loss. We develop a design framework for an integrated polarization state generator and numerically demonstrate generation of all possible polarizations with an output polarization extinction ratio that can be tuned over ±30 dB at telecommunication wavelengths. Our approach utilizes a single continuous waveguide such that insertion loss is primarily due to propagation loss. To extend our approach to control of light's spatial degree of freedom, we examine guided light from the perspective of angular momentum, where the polarization and spatial degrees of freedom correspond to light's spin and orbital angular momentum, respectively. We uncover novel features of light's angular momentum in integrated waveguides which are of fundamental and technological interest. We leverage our results to demonstrate conversion between the higher order E_21^x and E_12^x modes via Berry's (open full item for complete abstract)

Master of Science, The Ohio State University, 0, Mechanical Engineering

Topology optimization tools can yield multi-functional high-performance structures. The rise of additive manufacturing opened the door to realize many designs that were not possible otherwise. Cables and wires used for power and signal transmission account for a considerable weight (3-5% of total weight) in automotive and aerospace applications. In this research, we present an approach in multi-physics waveguide topology optimization in electromagnetics and mechanics. Integrating electromagnetic waveguides into frames and chassis can provide a greater reduction in weight and an increase in valuable space. We propose a gradient-based multi-objective approach that combines the electromagnetics' objective and the mechanical objective. To investigate the tradeoffs between the performances of the two physics, we vary the weights of each objective systematically. We will explore novel application examples which can be in the form of joints that can be embedded in frames and chassis to integrate electromagnetic devices in structurally sound designs. Performance metrics such as mechanical compliance, electromagnetic transmission, and transmission efficiency will be investigated. Local volume constraint and pattern repetition in topology optimization have demonstrated their capabilities and strengths in achieving high strength-to-weight ratio, high buckling resistance, excellent thermal dissipation, and many other sought-after properties in the thermal, mechanical, and acoustic domains. Additionally, this research aims at exploiting the advantages of the local volume constraint in electromagnetic waveguide structures. The control of propagation mechanism of the electromagnetic wave when tuning the pore size relative to the wavelength, resilience of electromagnetic waveguides against external electromagnetic 2 interferences achieved by using functionally tailored porosity regions, and finally, improved thermal dissipation performance enabled by porous designs. The local vo (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2021, Electrical and Computer Engineering

Electrical Capacitance Tomography (ECT) and its derived technologies represent one of the preferred mechanisms to study multi-phase flows in industrial applications due to their low cost, relatively fast imaging speed, non-invasiveness, non-intrusiveness and robustness. One important weakness of these technologies, however, is that they are part of what is known as soft-field imaging techniques, where the operating frequencies of the interrogating fields are very low, ultimately resulting in low spatial resolution. In addition, the problem of image reconstruction in ECT defines an inverse problem, which corresponds to a series of particular challenges in the solution process: mainly, lack of uniqueness in the solution, and high degree of numerical instability. This reality in practical applications results in severely underdetermined systems of equations, with particular sensitivity towards random perturbations in the input data. In the last few years there have been numerous efforts to address those difficulties in ECT-based systems, but they essentially can be categorized in two main sets. The first one corresponds to the exploration of different strategies in the algorithms to perform the image reconstruction, and the second one corresponds to different hardware mechanisms to try to obtain more information from the sensing domain. The work that we present in this dissertation deals with both. In the first case, we employ the Bayesian regression framework configured by the Relevance Vector Machine (RVM) to define an algorithm for ECT applications that can concurrently provide image reconstruction results and uncertainty estimates about the reconstruction. To illustrate the RVM operation in ECT, we simulate typical ECT scenarios, making explicit the connection between the reconstructed pixel values and the corresponding uncertainty estimates in each case. We compare the RVM reconstruction performance with that of the Iterative Landweber Method (ILM) and the leas (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2021, Electrical and Computer Engineering

This dissertation develops the foundation of two novel smart, functionalized and truly wearable clothing based technologies that break the state-of-the-art boundaries in terms of seamlessness and performance, (a) for motion capture, and (b) for realizing Wireless Body Area Networks (WBANs). Electrically Small Resonant Loop (ESRL) is devised as basic building block for both the technologies. For motion capture, transmit and receive ESRLs are used that are capable of monitoring joint flexion/extension and/or rotation seamlessly, without obstructing natural motion, in real-time and in natural settings of the individual. Three different sensor variants are developed, forming foundational blocks of the technology, (a) Transverse Configuration (TC), (b) Longitudinal Configuration (LC) and, (c) Longitudinal-Transverse-Longitudinal Configuration (LTLC). TC is capable of monitoring joint flexion while being robust to rotation. LC is capable of monitoring joint flexion and rotation simultaneously while also offering better flexion resolution compared to TC. However, its resolution and performance is hindered by inherent ambiguities. LTLC eliminates the ambiguity present in LC, while concurrently improving flexion and rotation resolution. Further, in vivo tests on a dog model under static scenarios confirm the sensor's operation on living beings. Safety aspects are taken into account and detailed design guidelines are discussed to enable translation as per requirement. For WBANs, a wearable magnetoinductive waveguide (MIW) is developed which is formed using series of body-worn ESRLs. This WBAN is capable of offering extremely low loss, low power requirements, negligible interference, secure and safe connectivity across the body, thereby overcoming shortcomings of state-of-the-art. Two different designs are developed here, (a) axial, and (b) planar. The axial design can be wrapped around any part of the human body to form a low-loss, high bandwidth WBAN. The planar design (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2021, Electrical Engineering

Acoustic noise and vibration prediction, mitigation, and performance optimization, in electric machines, are studied in this dissertation. First, vibration prediction enhancement in electric machines through frequency-dependent damping characterization is proposed in this dissertation. Different methods of mass and stiffness-dependent Rayleigh damping coefficient calculation are studied to identify the best damping estimation strategy. The proposed damping estimation strategy is used to predict the vibration spectrums of two 12-slot 10-pole (12s10p) permanent magnet synchronous machine (PMSM) designs and predicted vibration spectrums are experimentally validated through run-up tests of two prototypes. Moreover, to eliminate the dependency of the damping estimation strategy on the availability of a prototype, a damping coefficient prediction methodology is proposed. The proposed prediction methodology is experimentally validated using a third 12s10p PMSM prototype. Secondly, a lumped unit response-based sensitivity analysis procedure is introduced, which isolates electromagnetic and structural impacts brought by variation of different design parameters in an electric machine. The lumped unit response strategy utilizes the frequency-dependent damping estimation method developed early in the dissertation. The impact of different generic design parameters and a structural feature on a range of output quantities are studied in detail for a 12s10p PMSM. Analysis reveals that on a 12s10p PMSM, slot opening has a very high impact on the dominant airgap force component. A multi-level non-linear regression model-based optimization strategy is introduced considering electromagnetic and structural design objectives and constraints following the sensitivity analysis. A 12s10p PMSM prototype is tested to validate the FEA simulations used during the optimization process. Finally, the lumped unit response-based vibration prediction methodology devel (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2021, Electrical Engineering

At the frequencies used in switching dc-dc converters, the skin and proximity effects have a significant effect on both the losses and leakage inductance of the transformers used in these circuits. Analytical expressions that have been derived to calculate ac resistance and leakage inductance have primarily used a 1-D approximation. They also have used Cartesian coordinates or approximations that are equivalent to Cartesian coordinates, as well as usually assuming an ideal core of infinite permeability. The classical result in the case of the resistance/losses is Dowell's equation, and there are analogous results for leakage inductance. This dissertation derives new equations that take the effect of winding curvature into account by using cylindrical coordinates. These equations are also more general in that they permit any interleaving pattern as well as variable layer thicknesses and gaps between layers. Additionally, new equations for the magnetic field coefficients are derived that take the core permeability into account, which requires a full 2-D model and the method of images applied in two dimensions. These coefficients then allow calculations of resistance/losses and leakage inductance that also take the core permeability and winding width into account. The accuracy of all of these equations is assessed by comparing their results with those of finite-element analysis (FEA) simulations. Due to the large number of parameters involved with the fully general equations, a statistical approach is used in which a large number of randomly generated devices are simulated. Finally, for a special class of more specific transformers, the effects of a reduced number of independent parameters on the resistance/losses and leakage inductance is determined empirically. The relative sensitivity of these quantities on these parameters is also determined.

Master of Science, The Ohio State University, 2021, Electrical and Computer Engineering

Neuro-sensing of the human brain has unparallel benefits when it comes to early detection of neural disorders like Alzheimer's, Parkinson's, multiple sclerosis, epilepsy, etc. However present neuro-sensing techniques suffers with various crisis. Some of them being immobility of patients due to use of intracranial wires, frequent surgeries for replacement of batteries and heating issues due to dense electronics. Passive neuro-sensing techniques have been reported to deal with these issues. However, shift from traditional to passive neuro-sensing system introduced complications like misalignment loss. State of the art neuro-sensing technologies suffered with losses of about 10 dB in case of misalignment in human brain in-vitro settings. This thesis presents a neuro-sensing antenna system that is able to read a complete range of neural signals keeping the misalignment losses less than 2 dB. A canonical four-layer human head and a three-layer rat head model is presented. The previous state of the art neuro-sensing antenna systems are simulated in these head models for misalignment losses. High simulation time was observed when these systems were tested in human and rat head model. To reduce the simulation time a canonical single layer human and rat head model was proposed. Up to 3 times reduction in simulation time was observed in single layer as opposed to multi-layer head models. A bump is also proposed in rat head model to accommodate the implant and help in realistic and error-free modelling. The proposed technique will also help in accurate mapping of the rat head models for in-vivo measurements. A new antenna system with an interrogator (antenna used to receive neural signals) and an implant antenna is proposed. The enhanced transmission coefficient and reduced misalignment losses help in efficiently increasing the sensitivity up to 20 µVpp. The amount of power transferred by the interrogator antenna towards the implant is reduced for th (open full item for complete abstract)

Master of Science, The Ohio State University, 2021, Electrical and Computer Engineering

Advancements in semiconductor technology present new challenges in electric machine construction, operation, and control. Silicon carbide (SiC)-based power electronics are becoming the new standard for high-power consumer and commercial devices, and are implemented in technologies such as power inverters, converters and rectifiers. This paper focuses on the effects of inverter drives for traction motors in electric vehicles with high dV/dt rates on bar-wound machine windings, including the expected impacts on insulation materials under prolonged periods of high voltage stress. Partial discharge inception voltage testing was performed to evaluate the voltage bus level at which breakdown will start to occur. A simulation model was constructed using finite element analysis, the results of which were validated with experimental results using a commercially available SiC inverter and traction motor. Correlation has been established between the preliminary simulation results and experimental data. It is proven that as DC bus voltages increase with the capabilities of SiC devices, the voltage stresses inside the stator windings approach levels which could cause partial discharge and premature insulation degradation in existing stator designs.

Doctor of Philosophy, The Ohio State University, 2020, Physics

Like many problems in physics, the interaction between high intensity laser pulses and solid materials depends critically on the relative timescales of the drive (the laser pulse with finite duration) and the material response. This is especially true for Laser-Induced Damage and Ablation (LIDA) of solids, where femtosecond (1 fs = 10e−15 s) laser pulses can achieve extremely high energy densities since there isn't enough time for energy to diffuse away during the laser pulse like there is for picosecond (10e−12 s) and nanoseond (10e−9 s) pulses,for example. The pulse duration dependence of fs-LIDA for Near-Infrared (NIR) pulses less than 100 fs is less well-understood, especially in the Few-Cycle Pulse (FCP) regime (<10fs) where energy is deposited faster than almost all of the processes associated with the material response. In this thesis, the pulse duration dependence of LIDA of transparent dielectric material systems down to the FCP regime is studied using a well-established time-and space-resolved imaging technique as well as high-resolution depth-profiling. LIDA of dielectric solids has large application spaces in precision micro-machining andsurface patterning, as well as improving the LIDA performance of dielectric thin-film opticsto increase the output of high power laser systems. Practical multilayer thin-film opticsintroduce more complexity to the LIDA process due to thin-film interference, so I startedwith a study of FCP-LIDA of the simplest thin-film system: a single layer. I found that dif-ferences in LIDA between two film thicknesses are exacerbated by Few-Cycle Pulses (FCPs)relative to 100 fs pulses. I wrote a Finite-Difference Time-Domain (FDTD) simulation thatmotivates a possible mechanism for this, suggesting FCPs result in a more spatially non-uniform excitation of the films. My results show that the models I used must be extendedto more completely describe my experimental observati (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Electrical and Computer Engineering

Radiowave propagation through various complex environments is a field of active research due to the impact it has on various communication systems. One aspect of radiowave propagation in the marine atmospheric boundary layer (MABL) is the ducting propagation mechanism. Duct formation is highly dependent on atmospheric conditions and hence, research on ducting propagation involves propagation measurements with atmospheric characterization. These measurements eventually lead to improved modeling of such a propagation mechanism. Another aspect of electromagnetic (EM) signal propagation in the atmosphere is the presence of small scale fluctuations of the refractive index leading to the variation of the amplitude and the phase of the received signal. This signal fluctuation is known as scintillation. Scintillation is one of the reasons for signal enhancement or fading in any air-ground or ground-ground communication link. Apart from the atmospheric conditions, factors like rough seas, mountainous terrain or vegetation affect signal propagation. The goal of this dissertation is to develop a comprehensive simulation model using the parabolic wave equation (PWE) to predict the signal propagation effects in all the aforementioned atmospheric and surface conditions. Various experimental campaigns were conducted to measure the propagation loss which can be used to validate the different simulation cases. In all the experiments, a transceiver system, operating from 2 GHz - 40 GHz, was used to measure the propagation loss in different ground/air-ground communication links. In the 2017 CASPER West campaign in southern California, a link was established between the research platform, R/P Flip, stationed around 46.7 km from the shore to measure the propagation loss with time. These fixed ground-ground measurements were made such that the scintillation prediction made in the turbulent MABL by the PWE can be validated. In another campaign, PIMTER 2019, the transceiver system, (open full item for complete abstract)

Master of Science in Electrical Engineering, University of Dayton, 2020, Electrical and Computer Engineering

Demands for self-sustainable energy sources are rising as we become more and more reliable on electronic devices in our daily lives. Scientists and engineers have been exploring various novel methods to harvest energy from existing resources in order to eliminate or reduce the usage of battery and/or conventional power equipment. Solar, water, tide, wind, and terrestrial heat are renewable and green resources that have been widely adopted and commercialized[1]. With the rapid development of technology, more resources can be used for providing energy and compressing the size of devices. For example, piezoelectricity, vibration, and electromagnetic energy can also be used in the large-scale area[2]. Electromagnetic energy, especially in WIFI frequencies, is recently gaining more and more interest because of the wide signal coverage on campus and residential areas. An unique advantage of harvesting electromagnetic energy is its little dependence from weather related factors, unlike solar, water, tide, wind and terrestrial heat[3]. Given the circumstances, the interest in this work is to design a novel rectenna device to harvest energy from WIFI frequencies and to provide a parametric study in efficiency improvement. Our comfort and fast life in modern society roots in massive volumes of data exchange through wireless transmission. In modern communication systems, different radio spectrum's only use is for single media to prevent interference between users and different devices. International telecommunication Union (ITU) established rules to allocate spectrums for various purposes; the chart [4] shows specific distributions for mobile, broadcast, satellite, and other devices. Since antenna is the only component worked as receiver and transmitter in a device, the main problem in communication systems are the versatility of antenna. So, antenna with reconfigurability is desired in today's multi-band multi-mode communication system front end. The key solution is to wide (open full item for complete abstract)

Master of Science, The Ohio State University, 2020, Aero/Astro Engineering

This research investigates the strategic design of elastomeric metamaterials to induce controllable mechanical properties and sensing capabilities. Elastomers have been utilized in the creation of flexible electronics due to the inherent ability to nondestructively deform. When a malleable, conductive material, such as liquid metal, is incorporated into an elastomeric host structure, a flexible electronic material is created that may maintain electrical conductivity during high strain loading. While research has uncovered ways of utilizing deformation of flexible electronics to achieve functionality such as resistance change and self-healing, there are few studies that explore mechanical and electrical properties of such systems when subjected to compression. The material responses may be made more versatile by exploiting principles of elastic metamaterials. Such metamaterials contain void architectures that create elastic truss networks capable of reversible buckling, and have shown ability to provide impact and vibration attenuation capabilities. Methods of controlling the mechanical properties of these metamaterials, such as functionally grading layers of beams, or incorporating magnetic microparticles into the elastomer matrix to modify the stiffness in real-time with an externally applied magnetic field, have been explored. Yet, research is lacking on the interplay of design parameters and magnetic field that result in mechanical behaviors. Motivated by these needs, this research explores foundations of new generations of smart metamaterials by establishing methods for sensing and control of material behavior. A new approach to liquid metal-based sensing in elastomeric materials is built up, leveraging mechanical deformation to induce a digital logic sensing modality. Then, the interplay of mechanical design and magnetoelasticity is explored for metamaterials with properties governed by ferromagnetic particle filler and the presence of magnetic field. The findi (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Electrical and Computer Engineering

Antennas mounted on aircraft, UAVs, and other platforms are used in a number of critical applications, such as navigation, communication, and situational awareness. Since the platform can heavily affect the antenna pattern, one should carry out in situ characterization of the antenna to evaluate the performance of the RF systems. It is often too expensive or impractical to measure the antenna on the intended platform, so instead, the antenna under test (AUT) is measured on a simple ground plane. The measurements are then imported into computational electromagnetics (CEM) codes to simulate platform scattering from the platform of interest. However, current approaches struggle to isolate the antenna radiation from the measurement ground plane interactions, leading to inaccuracies in the AUT representation. Furthermore, many approaches rely on near-field measurements for accuracy and use many current elements to represent the AUT leading to long simulation run-times. This dissertation presents a novel approach for in situ manifold estimation which represents measured data via a weighted sum of simple basis element far-fields. The approach, the Sparse-Constrained Equivalent Element Distribution Method (SC-EEDM), provides a more accurate representation of the AUT compared to existing techniques. The SC-EEDM accurately represents the AUT using measured far-field data only, and represents the AUT using a small number of current elements. In addition, the SC-EEDM isolates antenna radiation from antenna-ground plane interactions, leading to more accurate in situ manifold estimations. Using high-fidelity simulations, the method is shown to accurately estimate antenna far-fields on complex platforms from antenna measurements on simple structures.