Doctoral Dissertations

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https://hdl.handle.net/10919/11041

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The effect of ACTH and progesterone on semen characteristics, blood hormones and testicular histology in the bull
O'Connor, Michael L. (Virginia Polytechnic Institute, 1979)
Paradigms of social stratification: the contemporary power elite debate
Kerbo, Harold R. (Virginia Polytechnic Institute, 1975)
Some dynamic mechanical properties of apple fruits and their use in the solution of an impacting contact problem of spherical fruit
Hamann, Donald D. (Donald Dale) (Virginia Polytechnic Institute, 1967)
Intracellular distribution of nitrogen during synchronous growth of Chlorella pyrenoidosa
Hare, Theodore Arthur (Virginia Polytechnic Institute, 1967)
Development of a short test for the identification of aggregates causing poor concrete performance when frozen
Hsieh, Tai-Chou (Virginia Polytechnic Institute, 1967)
Millenarian movements and the politics of liberation: the Rastafarians of Jamaica
De Albuquerque, Klaus (Virginia Polytechnic Institute, 1976)
Cultivating Sustainability: Analyzing Soil Health Dynamics and Economics of Cover Crops in the Mid-Atlantic
Haymaker, Joseph R. (Virginia Tech, 2024-11-11)
This research investigated the long-term effects of transitioning from intensive tillage to no-till (NT) practices with cover crop (CC) incorporation on soil quality, agronomic performance, and economic returns in Virginia's Coastal Plain. Nine years after integrating NT practices and CCs, improvements in soil physical and chemical properties were observed, including a 22% to 65% increase in soil organic matter (SOM) in the top 5 cm, a 4% reduction in bulk density, and enhanced soil moisture retention in corn production. Timing of CC termination played a crucial role in optimizing biomass production and nutrient accumulation. Overall accumulation rates were 44.4 kg dry biomass ha-1 d-1, 1.22 kg N ha-1 d-1, 0.16 kg P ha-1 d-1, 1.36 kg K ha-1 d-1, and 0.08 kg S ha-1 d-1 of delayed termination between March 15 and April 30. Each additional day of cover crop growth contributed to a fertilizer value of $3.91 ha-1, highlighting the economic advantage of extending CC growth during this critical period. In 2023, CC effects on corn N fertilizer demand and yields were assessed by applying variable N rates of 0, 56, 112, and 168 kg N ha-1 at sidedressing. Greatest corn yields at each N rate were observed following hairy vetch and a vetch-dominant CC mix, which had low C:N ratios (≤12:1) and accumulated 134 to 186 kg N ha-1 in their aboveground biomass. Corn yields after these CCs were 8.5 to 9.3 Mg ha-1 at the zero N sidedressing rate, increasing to 10.8 to 11.3 Mg ha-1 at the 168 kg N ha-1 rate. However, increasing the N rate yielded minimal economic benefits for these treatments. Vetch treatments produced the highest net returns, with greater returns at lower N rates, as vetch generated an additional US$1,012 ha-1 at the zero N sidedressing rate compared to the no CC control. Conversely, cereal rye produced a negative net return across all N rates, with positive returns achievable only with state cost-share payments. The findings underscore the importance of adaptive N management strategies and policy adjustments to support environmentally and economically sustainable cover crop practices in corn production.
Evaluation of Seed Impact Mills for Harvest Weed Seed Control in Soybean and Wheat in the Eastern United States
Russell, Eli Carnley (Virginia Tech, 2024-11-11)
Harvest Weed Seed Control (HWSC) concentrates, removes, or destroys weed seeds as they pass through the combine. Seed impact mills are modifications that are mounted directly to the back of a combine and are one way to implement HWSC. Seed impact mills kill weed seeds during harvest, preventing seeds from being added to the soil seedbank. Mills like the Redekop Seed Control Unit (SCU) and the integrated Harrington Seed Destructor (iHSD) could be used in soybean and wheat production in the eastern United States. Understanding the effectiveness and limitations of these mills is important for grower adoption. So, the aim of this research was to evaluate the efficacy of two seed impact mills, the Redekop SCU and the iHSD, in soybean and wheat. The first objective tested general seed kill of problematic species in soybean and wheat and seed kill in adverse conditions, such as high chaff flow rate into the mill and high chaff moisture. Results from objective one indicate that both the Redekop SCU and iHSD killed >98% and >91% of problematic weed seeds in soybean and wheat, respectively. Increases in chaff flow rate and chaff moisture resulted in a decrease in seed kill for specific species depending on the mill. But even at high chaff flow rates, seed kill remained >98% and >77% in soybean and wheat, respectively. At high chaff moisture, seed kill remained >98% and >74% in soybean and wheat, respectively. The second objective evaluated the percentage of weed seeds that bypassed the seed impact mill by exiting the combine in the straw fraction and the percentage of weed seeds that were killed when they entered the seed impact mill during harvest with a commercial combine. Results at field scale indicated that <5% of weed seeds bypassed the seed impact mill by exiting the combine in the straw fraction during harvest in soybean and wheat. Additionally, during a commercial harvest, the seed impact mills killed >99% and >89% of seeds in soybean and wheat, respectively. The third objective monitored population density changes for common ragweed (Ambrosia artemisiifolia) in soybean and Italian ryegrass (Lolium perenne ssp. multiflorum) in wheat following a harvest with a seed impact mill. Results from objective three indicated that in the growing season following a harvest with a seed impact mill, common ragweed density was reduced by 26% and 77% in the spring and fall, respectively, in soybean, and Italian ryegrass density was reduced by 48% in wheat. The fourth objective evaluated Palmer amaranth (Amaranthus palmeri) and its ability to shift its flowering timing in response to HWSC. If weeds flower earlier, they could shatter seeds earlier, and those seeds would bypass HWSC. Through selective breeding, two populations of Palmer amaranth experienced a shift in flowering timing such that the third generations flowered 54.7 and 41.0 days sooner in the greenhouse than the initial generations. In a common garden experiment, the second generations flowered 5.5 and 8.9 days sooner than the initial generations. These results indicate that seed impact mills, like the Redekop SCU and iHSD, can deliver high seed kill rates to a range of weed species at commercial scale in both soybean and wheat. Even in adverse conditions, the mills still killed >74% of seed from tested species. However, weed species can adapt to HWSC selection pressures, resulting in a loss of HWSC efficacy. Overall, this research indicates that seed impact mills are a good tool that growers can implement to reduce the number of weed seeds being returned to the soil seedbank.
Using Screenshots as a Medium to Support Knowledge Workers' Productivity
Hu, Donghan (Virginia Tech, 2024-11-08)
As computer users increasingly rely on digital tools for daily tasks, the complexity of their working environments continues to grow. Modern knowledge workers must navigate a diverse array of digital resources, including documents, websites, applications, and other information. This complexity presents challenges in managing multiple activities to maintain productivity, such as handling interruptions, resuming tasks, curating resources, recalling context, retrieving previously closed digital resources, and fostering self-reflection. Despite these challenges, there has been limited research on leveraging visual cues to help users reconstruct their previous mental contexts, retrieve digital resources, and enhance self-reflection for behavioral change. Therefore, this Ph.D. dissertation addresses these gaps by focusing on: (1) investigating the existing challenges users face in curating digital resources, (2) designing and implementing supportive applications for task resumption, (3) developing methods that utilize screenshots and metadata for reconstructing mental context and retrieving resources, and (4) enhancing the processes of self-reflection and behavioral change to improve overall productivity.
Embeddings for Disjunctive Programs with Applications to Political Districting and Rectangle Packing
Fravel III, William James (Virginia Tech, 2024-11-08)
This dissertations represents a composite of three papers which have been submitted for publication: The first chapter deals with a non-convex knapsack which is inspired by a simplified political districting problem. We present and derive a constant time solution to the problem via a reduced-dimensional reformulation, the Karash-Kuhn-Tucker optimality conditions, and gradient descent. The second chapter covers a more complete form of the political districting problem. We attempt to overcome the non-convex objective function and combinatorially massive solution space through a variety of linearization techniques and cutting planes. Our focus on dual bounds is novel in the space. The final chapter develops a framework for identifying ideal mixed binary linear programs and applies it to several rectangle packing formulations. These include both existing and novel formulations for the underlying disjunctive program. Additionally, we investigate the poor performance of branch-and-cut on the example problems.
Triple Helix Relations in Local and International Scientific Collaborations: A Case Study of Thailand, the United States, and China
Petri, Bunyakiat (Virginia Tech, 2024-11-04)
Local and international scientific collaborations are crucial for innovation and sustainable development. However, there is a gap in understanding how these collaborations affect national innovation ecosystems. This study examines the dynamics of Triple Helix Relations, focusing on collaborations within Thailand and its international partnerships with the United States and China from 2006 to 2022. I use Shannon's mutual information, enhanced by Loet Leydesdorff, to analyze the synergy among various local sectors and conduct interviews with eighteen researchers and policymakers, utilizing Latour and Woolgar's cycle of credibility. The study delves deeply into the complexities of collaboration dynamics and motivations. The analysis reveals nuanced patterns of collaboration, spanning both within Thailand and across international boundaries. I distinguish collaborations based on the nationality of partners (Thai-China vs. Thai-U.S.) and subject areas (engineering, medicine, agricultural and biological sciences). The findings show significant variation in collaboration patterns depending on these factors. Universities are the main contributors to scientific publications, while the Thai government is more active in medicine and collaborations with the United States. Industry is more engaged in agricultural, biological sciences, and engineering, especially with China. One recurring theme that emerges from our interviews is the importance of relationship networks as significant assets in collaborative endeavors. Different credibility resources and networks yield varying levels of negotiation power and influence dynamics in different collaborative settings. Understanding these dynamics could assist smaller countries like Thailand in devising strategies to maximize the benefits of international collaborations. Despite the opportunities globalization presents, I observe a decline in local collaborative synergy among Thailand's three sectors, university, government, and industry. Local collaborations are mostly bilateral, indicating a need for greater involvement from the third sector to foster sustainable growth and development. This study demonstrates the use of STS concepts and various analytical tools, such as co-authored publications and Shannon's mutual information, to showcase collaboration trends and synergy among local sectors in Thailand. The study also includes case studies from diverse countries to consider different conditions affecting collaboration dynamics. Emphasizing recent data, the study aims to capture the evolving landscape of international and local scientific collaborations comprehensively.
A Fast-Response Odor Chromatographic Sniffer (FOX)
Chowdhury, Mustahsin (Virginia Tech, 2024-11-04)
This thesis in microscale gas chromatography (μGC) creates a paradigm shift in rapidly analyzing chemicals in the environment or analytes. We are looking for unexpected chemical changes that have been added purposefully or unintentionally. The work examines various aspects of μGC technology, including the optimization of ionic liquid stationary phase coatings for microfabricated columns, achieving up to 8300 theoretical plates per meter for naphthalene using 1-butylpyridinum bis(trifluoromethylsulfonyl)imide [BPY][NTf2] at 240°C. The development of portable systems for fuel adulteration detection is demonstrated, capable of discriminating 5% kerosene adulterated diesel fuel with four seconds of chromatogram analysis. The research also presents a novel parallel column configuration using three ionic liquid-coated semi-packed columns, each 1 m long and 240 μm deep, for complex gas analysis of up to 46 compounds. Key innovations discussed include optimized coating procedure of GC separation columns and implementation of GC based miniaturized electronic nose with the integration of machine learning algorithms. An evaluation of a prototype modular electric and fluidic μGC was evaluated and validated for benzene toluene, ethylbenzene, and xylene (BTEX). This research highlights the versatility of μGCs in applications ranging from environmental monitoring to quality control in the fuel industry, showcasing their potential as powerful tools for on-site chemical analysis with improved selectivity, resolution, and portability.
Black Feminist Liberatory Pedagogy and Ubuntu Solidarity: Toward an Otherwise World of Education
Kaerwer, Karin Louise (Virginia Tech, 2024-11-01)
Since the beginning, U.S. public schools have perpetuated harm towards students that do not fall under the descriptors of male, middle/upper class, cis-gender, heterosexual, able-bodied, neurotypical, and white. Education scholars with varying ideological backgrounds have approached questions of education equity for decades; yet, in asking these questions through the "white gaze" (Wright, 2023), some scholars have perpetuated the harm they seek to demystify. The following series of manuscripts express the dire need for (re)calibrating U.S. public schools so that all children receive just, equitable, and humanizing education. The first manuscript analyzes harmful white supremacist ideological hegemony embedded in education policy, the second manuscript is an ethnographic portrait (Lawrence-Lightfoot and Davis, 1997) that resists the "white gaze" and illuminates the good in a thriving classroom comprised of Black and Brown teachers and students through a lens of Black feminist theory, and the third manuscript interrogates what it takes emotionally and intellectually to do this work as a white woman scholar who seeks ubuntu feminist solidarity. The dissertation concludes with a posture of hope. Hope of an otherwise world (Greene, 1995) of education in which ubuntu feminist scholarship will inform praxis so that students may experience pedagogies that liberate instead of harm.
Climate Crisis in Our Closets: Sustainability Transition of Fast Fashion Using MLP Analysis
Kiran, Pratyusha Pranob (Virginia Tech, 2024-10-31)
Innovations in production and retail methods have propelled the fashion industry's explosive growth, with complex global supply chains that pose serious environmental and social issues. Despite increased awareness and multiple attempts toward sustainability, the industry is still trapped in an unsustainable paradigm. Therefore, this dissertation aims to examine the barriers of transition toward a sustainable fashion model. Given the highly globalized nature of the fashion supply chain, and manufacturing spread across different nations, it is essential to examine the barriers to sustainability from the perspective of actors within the supply chain. Examining these issues through the perspectives of manufacturers and other key stakeholders offers valuable insight into the intricate dynamics at work and helps in locating regional barriers that could prevent a smooth transition. Hence, this study focuses on conducting interviews with manufacturers and industry experts in Indian fashion supply chain to get the perspective of a manufacturing country. The findings reveal a disconnect between sustainability standards and their local implementation, often exacerbated by the lack of brand accountability and disregard for local realities. The research highlights how certifications, largely shaped by Western ideals, fail to account for the socio-economic and infrastructural constraints of manufacturing regions like India. This study argues for a pivot away from a one-size-fits-all approach to sustainability, advocating for strategies tailored to local contexts that better align with the needs and challenges faced by actors in developing economies.
Pre-ionization studies on the modular theta-pinch experiment for field-reversed configuration applications
Bean, Ian Alexander (Virginia Tech, 2024-10-31)
A new semi-empirical model is introduced for the quantification of inductively-coupled breakdown systems. The model is informed by breakdown studies conducted on the Modular Theta-pinch eXperiment (MTX). Observations made of inductively-coupled breakdown behaviour are consistent with the model's expectations, indicating that the model can be used to aid in design of inductively-coupled pre-ionization systems. The model is further found to be capable of quantifying the efficacy of seed ionization in inductively-coupled systems. Comparisons are made between the standard ringing-theta and a new field-aligned dipole pre-ionization systems. In the presence of sufficient seed ionization, no physical reason was observed for selection of one method over the other, leaving only engineering considerations as the determining factor for selection of an appropriate pre-ionization system. This work is supported by the Institute for Critical Technology and Applied Science (ICTAS) at Virginia Tech and the National Nuclear Security Administration of the U.S. Department of Energy. LA-UR-24-31269
Innovative Design and Development of PANDORA: Advancing Humanoid Robotics Through Additive Manufacturing
Fuge, Alexander Jonathan (Virginia Tech, 2024-10-31)
This dissertation presents the innovative design and development of PANDORA, a full-sized humanoid robot that stands 1.9 meters tall and weighs 45 kilograms. Its highly configurable structure was created primarily using Additive Manufacturing(AM) techniques. PANDORA is designed to address the limitations of existing humanoid robots, particularly regarding accessibility, cost, and customization for research purposes. The robot features 32 degrees of freedom, enabling it to perform a wide range of human-like motions, such as walking, reaching, and manipulating objects. The development of PANDORA focuses on leveraging the flexibility of AM to create a lightweight, cost-effective, and easily modifiable robotic platform. The dissertation details the iterative design process, which includes the structural components for weight reduction while maintaining the necessary strength and durability for dynamic movements. The lower body of PANDORA incorporates advanced joint configurations and custom-designed linear actuators, initially developed for previous Terrestrial Robotics and Engineering Controls (TREC) Lab robots, such as THOR and ESCHER. The upper body features a cable-driven arm system, which is both lightweight and highly functional, offering eight degrees of freedom per arm. A significant contribution of this work is the development of design heuristics for AM, tailored specifically for the construction of large-scale robotic components. These heuristics were validated through extensive finite element analysis (FEA) and physical testing, ensuring the AM parts could withstand the loads and stresses encountered during operation. The open-source nature of the PANDORA platform, including all design files and documentation, further enhances its value to the research community, providing a robust foundation for future developments in humanoid robotics.
Gnotobiotic Pig Models for the Study of Enteric Pathogen Replication and Pathogenesis
Nyblade, Charlotte June (Virginia Tech, 2024-10-09)
Clostridioides difficile (C. difficile) and human rotavirus (HRV) are leading causes of bacterial and viral gastroenteritis worldwide. Treatment and vaccination options for both pathogens have significant limitations. C. difficile infections are treated with antibiotics, which is paradoxical as C. difficile itself is associated with antibiotic usage. In the United States, two live oral attenuated vaccines (Rotarix and RotaTeq) are licensed for protection against HRV. Since receiving approval from the World Health Organization (WHO), Rotarix and RotaTeq have been widely implemented into global national childhood immunization schedules, with one report finding 59 countries using Rotarix and 25 using RotaTeq. However, these vaccines have much lower efficacy rates in low- and middle-income countries. Because of these caveats, there is an urgent need to generate novel prophylaxes and treatments for C. difficile and HRV. In order to address this need, animal models that replicate the nuances of each infection are imperative. We have developed gnotobiotic (Gn) pig models for each pathogen. Gn pigs infected with spores of the hypervirulent UK1 strain of C. difficile develop classical signs of infection, including watery diarrhea and weight loss. Gross necropsy reveals colonic distention and discoloration, and histopathological evaluation shows volcano lesions, pseudo membrane formation, and epithelial cell erosion. Gn pigs infected with a G4P[6] strain of HRV also display pathogen specific signs of infection, including diarrhea, fecal rotavirus shedding, and damaged intestinal villi. A dose response study of the G4P[6] strain revealed diarrhea and virus shedding occurred at all tested doses, however the most severe diarrhea and virus shedding, measured by cumulative diarrhea score, area under the curve (AUC) of diarrhea, peak virus titer, and AUC of virus shedding, were all detected in the highest dose group. Based on the presentation of clinical signs of infection, 105 fluorescent focus units was selected as the optimal challenge dose for future studies. These models enable us to test candidate therapeutics, but also elucidate unique replicative features of the pathogens. For example, we found that HRV can replicate in the salivary glands and nasal cavity of Gn pigs in addition to the small intestine. HRV infection primed immune responses in the ileum, tonsils, and facial lymph nodes; infection also induced high levels of systemic and mucosal rotavirus specific antibody responses. Moving forward, we hope to expand upon this replication study to identify what cell types within the glands are infected as well as look at local cellular immune responses to HRV infection. Additional future directions include determining the protective efficacy of next generation HRV vaccines and evaluating effectiveness of an engineered probiotic yeast in reducing severity of C. difficile infection and disease. The Gn pig models of C. difficile and G4P[6] HRV are clinically relevant, and they will continue to serve as useful tools to better our understanding of pathogenesis, infection, and prevention of these pathogens.
Pyrolysis and Flamelet Model for Polymethyl Methacrylate in Solid Fuel Sc(ramjet) Combustors
Pace, Henry Rogers (Virginia Tech, 2024-10-28)
Scramjets have been identified as a potential long-term replacement for rocket and ramjet propulsion systems due to their enhanced performance at high Mach numbers. The introduction of solid fuels in these scramjet systems allows for shaping of the solid fuel cavity by additive manufacturing and introduces the possibility of enhancing combustion rates and stability. The present investigation aims to develop a coupled, high-order computational model to study the combustion of solid fuel scramjets. The primary objectives are to identify the effects of changing geometry on combustion and to better characterize the combustion process and flow patterns within a solid fuel scramjet engine. The high-Mach number of the air inflow over a scramjet cavity introduces a strong coupling between fluid dynamics, combustion, and regression time scales. Existing models often use simplified treatments of melt-layer conditions and combustion models that over-predict experimental rates, along with highly dissipative numerical schemes that inhibit the study of thermo-acoustic interactions between coherent pressure waves and the burning walls of the cavity. These limitations in current models suggest the need for a Navier-Stokes solver based on a high-order, discontinuous Galerkin method, incorporating melt layer equations and enhanced combustion manifolds. These manifolds should account for the effects of pressure and high oxidizer temperatures on flamelet dynamics. The focus is on modeling the flow field with accurate chemical heat release and residence time, to better study the effects of heat flux on the solid surface and the resulting coupling. An investigation of solid fuel scramjets was performed, and the numerical methodology with which the problem was tackled is described. A novel combustion mechanism was developed using a counterflow burner to study the combustion and regression of solid model fuel polymethyl methacrylate (PMMA). The diffusion flame between the fuel and oxidizer was studied numerically using a solid fuel decomposition and melt layer model to simulate convection and pyrolysis of the material. This model was validated using new experimental data as well as previously published works. The foam layer parameters are critical to the success of the validation. Results showed that the increased residence time of the gas in the bubbles facilitates the fuel breakdown. Fully coupled fuel injection and solid fuel surface monitoring was implemented based on this counterflow model and was a function of heat flux. Fuel regression was handled using adaptive control points for a B-Spline basis that updates based on surface movement. This methodology was used due to its resilience against the creation of surface discontinuities likely to result from large temperature gradients during combustion. Fourth-order computational simulations of ramjet combustion without regressing fuel walls using an in-house Discontinuous Galerkin approach were performed with a fully conjugate solution for the thermal wave in the solid. Results in ramjet geometries showed the turbulent combustion strongly affects the heat feedback to the walls and thus increases both the regression and fuel injection rates. Scramjet geometries were also simulated using the flamelet-progress variable approach in two different oxidizer conditions. All of these simulations showed strong agreement with experimental data and helped to uncover flame holding characteristics of the scramjet cavities and the strong coupling between the recirculation region and pyrolysis of fuel. The analysis has led to a better understanding of the effects of solid fuel scramjet geometries on mixing, enhanced modeling of acoustic instabilities in solid fuel air-breathing propulsion, and improved fuel chemistry modeling. It has been shown that cavity design significantly influences heat transfer to the solid fuel in both ramjet and scramjet conditions. The presence and thickness of the melt layer will guide designs that aim to reduce or enhance mechanical removal of fuel. Additionally, ramjet results indicate that longer cavities can couple with acoustics to induce self-excited conditions, leading to increased heat transfer to the solid. The importance of self-sustained instability and its coupling with melt layer fuel injection will contribute to improved acoustic stability. Developing pressure/temperature-dependent manifolds and melt layer models will advance our understanding of solid fuel supersonic combustion and its effects on phenomena such as blowout, fuel residence time, and solid fuel dual-mode transition.
Resilient Navigation through Jamming Detection and Measurement Error Modeling
Jada, Sandeep Kiran (Virginia Tech, 2024-10-28)
Global Navigation Satellite Systems (GNSS) provide critical positioning, navigation, and timing (PNT) services across various sectors. GNSS signals are weak when they reach Earth from Medium Earth Orbit (MEO), making them vulnerable to jamming. The jamming threat has been growing over the past decade, putting critical services at risk. In response, the National Space-Based PNT Advisory Board and the White House advocate for policies and technologies to protect, toughen, and augment GPS for a more resilient PNT. Time-sequential estimation improves navigation accuracy and allows for the augmentation of GNSS with other difficult-to-interfere sensors. Safety-critical navigation applications (e.g., GNSS/INS-based aircraft localization) that use time-sequential estimation require high-integrity measurement error time correlation models to compute estimation error bounds. In response, two new methods to identify high-integrity measurement error time correlation models from experimental data are developed and evaluated in this thesis. As opposed to bounding autocorrelation functions in the time domain and power spectra in the frequency domain, methods proposed in this thesis use bounding of lagged product distributions in the time domain and scaled periodogram distributions in the frequency domain. The proposed methods can identify tight-bounding models from empirical data, resulting in tighter estimation error bounds. The sample distributions are bound using theoretical First-order Gauss-Markov process (FOGMP) model distributions derived in this thesis. FOGMP models provide means to account for error time correlation while being easily incorporated into linear estimators. The two methods were evaluated using simulated and experimental GPS measurement error data collected in a mild multipath environment. To protect and alert GNSS end users of jamming, this thesis proposes and evaluates an autonomous algorithm to detect jamming using publicly available data from large receiver networks. The algorithm uses carrier-to-noise ratio (C/N0)-based jamming detectors that are optimal, self-calibrating, receiver-independent, and while adhering to a predefined false alert rate. This algorithm was tested using data from networks with hundreds of receivers, revealing patterns indicative of intentional interference, which provided an opportunity to validate the detector. This validation activity, described in this thesis, consists of designing a portable hardware setup, deriving an optimal power-based jamming monitor for independent detection, and time-frequency analysis of wideband RF (WBRF) data collected during jamming events. The analysis of the WBRF data from a genuine jamming event detected while driving on I-25 in Denver, Colorado, USA, revealed power variations resembling a personal privacy device (PPD), validating the C/N0 detector's result. Finally, this thesis investigates the cause of recurring false alerts in our power-based jamming detectors. These false alerts are caused by a few short pulses of power increases, which other researchers also observe. The time-frequency analysis of signals from the pulses revealed binary data encoded using frequency shift keying (FSK) in the GPS L1 band. Various experiments confirmed the signals are not aliases of out-of-band signals. A survey of similar encoded messages identified the source as car key fobs and other devices transmitting at 315 MHz, nowhere near the GPS L1 band, with an unattenuated 5$^{th}$ harmonic in the GPS L1 band. The RF emission regulations were analyzed to identify mitigation.
Neural Operators for Learning Complex Nonlocal Mappings in Fluid Dynamics
Zhou, Xuhui (Virginia Tech, 2024-10-24)
Accurate physical modeling and accelerated numerical simulation of turbulent flows remain primary challenges in CFD for aerospace engineering and related fields. This dissertation tackles these challenges with a focus on Reynolds-Averaged Navier--Stokes (RANS) models, which will continue to serve as the backbone for many practical aircraft applications. Specifically, in RANS turbulence modeling, the challenges include developing more efficient ensemble filters to learn nonlinear eddy viscosity models from observation data that move beyond the classical Boussinesq hypothesis, as well as developing non-equilibrium models that break away from the weak equilibrium assumption while maintaining computational efficiency. For accelerating RANS simulations, the challenges include leveraging existing simulation data to optimize the computational workflow while maintaining the method's adaptability to various computational settings. From a fundamental and mathematical perspective, we view these challenges as problems of modeling and learning complex nonlinear and nonlocal mappings, which we categorize into three types: field-to-point, field-to-field, and ensemble-to-ensemble. To model and resolve these mappings, we build up on recent advancements in machine learning and develop novel neural operator-based methods that not only possess strong representational capabilities but also preserve critical physical and mathematical principles. With the developed tools, we have demonstrated promising preliminary results in addressing these challenges and have the potential to significantly advance the state of the art in RANS turbulence modeling and simulation acceleration.

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