Physical Sciences and Mathematics Commons^™

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …

Cellphone-Acoustics Based Suas Detection And Tracking, Ryan D. Clendening

Theses and Dissertations

Small Unmanned Aerial Systems (sUAS) are an easily accessible technology that has become an increasingly large threat to US critical systems. This threatening technology demands using fault-tolerant, low-cost, replaceable, and accurate sensing resources, which counter the ubiquitous nature of sUAS [1]. Therefore, the methods developed in this thesis detect and track sUAS using easily accessible sensing resources, such as cellphones. First, we develop an acoustics sensor network-based sUAS detection methodology. In the latter effort, a deep learning model is trained using the acoustics data from the data collection to predict sUAS range from a cellphone. Combined, these two efforts demonstrate …

Adaptation Of Network Flow Problems For Course Of Action Generation, Alexander N. Stephens

Theses and Dissertations

This thesis introduces two methods to generate Courses of Action (COA) in distributed warfare scenarios: the Wargaming Commodity Course of Action Automated Method Under Uncertainty (WCCAAM-U2) and Dynamic Transshipment Problem (DTP)-generated COAs. Previous work by Deberry et al. used a Multi-Commodity Flow Problem (MCFP) to generate COAs for single-period wargame scenarios with known enemy force amounts. In WCCAAM-U2, we adapt an MCFP to work in situations where only intelligence estimates of enemy forces are known. Compared to two other COA-generation methods, the WCCAAAM-U2 COA outperforms the next highest-performing COA by 307% when compared by a ratio of objective success rate …

Monocular Vision And Machine Learning For Pose Estimation, Quang Ngoc Tran

Theses and Dissertations

This thesis introduces a monocular vision-based approach for 6 DoF pose estimation on a known object. The proposed solution is to use a CNN to find known features of an object in an image. These known features, together with their known locations, are used by a PnP algorithm to estimate the pose of the target object with respect to the camera. The primary difficulty with CNN-based methods is needing to generate a large amount of training data to effectively create the CNN. To overcome this difficulty, a 3D model of the real-world object is created and used in a visualization …

Effectiveness Of A Timing Side Channel For Deriving Neural Network Depth, Matthew P. Weeks

Theses and Dissertations

From facial recognition on cell phones to vehicle traffic modeling for city planning, integrating ML models can be an expensive investment in resources. Protecting that investment is difficult, as information about the model and how it was built can be leaked through multiple channels, such as timing and memory access. In this thesis, one method of extracting data through a timing side-channel is examined across multiple hardware and software configurations to determine its reliability for general use. While attempting to determine the layer count of a target model solely from its inference time, the research determined that it is not …

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino

Theses and Dissertations

Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …

Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore

Theses and Dissertations

As the threat of near-peer adversaries has increased, the DoD has increased its emphasis on Joint All-Domain Operations (JADO). This emphasis on JADO highlights the need for hands-on training that can engage military members at all levels. The serious game Battlespace Next (BSN) was designed to teach high-level JADO concepts by modeling real-world military assets in the context of a strategic card game. To keep pace with the evolving landscape of warfare as well as fit the needs of a variety of Department of Defense (DoD) communities, this research introduces the Battlespace Next Education Framework (BSNEF). The BSNEF allows JADO …

A Method For Monte Carlo Neutral Particle Radiation Transport In A Variable Density Atmosphere, Aidan B. Edens

Theses and Dissertations

This study focuses on accurately simulating the transport of radiation in the atmosphere to better understand the effects of nuclear weapons. The variable nature of the atmosphere poses a challenge in accurately simulating the prompt radiation following a nuclear explosion. To address this challenge, the Mass Integral Scaling technique is integrated with the Monte Carlo method to perform calculations in a variable density atmosphere. In addition to previous free-field estimates, this work also enables the simulation of transport calculations with other media, such as clouds. Results of neutron and photon fluence have been verified against the standard version of MCNP …

Coupling To Quantum Topological Order In Superconducting Qubit Systems, Seth T. Hyra

Theses and Dissertations

The coupling of superconducting qubits to non-trivial topological phases offers a means of improving existing quantum computational capabilities in lieu of a fully realized topological quantum computer. I will show that although such systems do not completely avoid the necessary errors associated with an energetic qubit basis, they do provide a potential avenue for decoherence free quantum memory. Further, the physics behind such systems enables exploration of the nature of non-Abelian anyons, as well as the remaining challenges in realization of true topological quantum computation.

Towards An Understanding Of The Thermodynamic Properties Of Crtao4: A Computational Perspective, Tanner B. Gordon

Theses and Dissertations

Materials that can withstand higher temperatures are paramount for next-generation aircraft design. Hypersonic capabilities and jet-turbine engines operate in extreme environments. Choosing materials that have high thermal stability and oxidation resistance for these applications can increase engine efficiency, reduce size, weight and power (SWaP), and increase the maneuverability of the aircraft. The mixed oxide CrTaO₄ has been experimentally observed to significantly contribute to oxidation resistance at high temperatures. However, and despite its significance, its properties remain largely unknown. This work explores the thermal properties of this material from a multi-scale approach, by obtaining an accurate description of the thermodynamics …

Characterizing Gesn Alloys By Sem/Eds And Photoluminescence Spectroscopy, Christopher M. Sutphin

Theses and Dissertations

Germanium tin (GeSn) alloys are being studied as potential transition metal (Group IV) photoelectric semiconductors or optical detectors. GeSn alloys could be employed as an optically active material within a computer. Compared to current technologies, a direct band gap GeSn alloy can be engineered to operate with higher thermal stability and efficiency. The GeSn alloy studied was composed of Ge and Si substrates with various Sn percentages grown using remote plasma-enhanced chemical vapor deposition (RPECVD). Photoluminescence spectroscopy (PL) techniques were initially used to determine the GeSn properties, including the band gap. The Ge_91.2Sn_8.8 PL spectra suggested the …

Simulation Of Neutron Generation From Laser-Driven Fusion In A Liquid D2o Sheet Using Novel Warpx Module, Colton R. Stoner

Theses and Dissertations

Using WarpX’s new nuclear fusion module, this work attempts to model an experimental system at the ELL at the AFIT with WarpX and draw conclusions about fusion products from resulting simulations. Recently, a table-top, high repetition rate, mixed radiation source was demonstrated at the ELL employing a HIL to fuse the deuterium nuclei present in a unique liquid target of heavy water. Analysis of the simulations predicted an isotropic output of neutrons from deuterium-deuterium fusion. These simulated neutrons were created in tens of femtoseconds from dense bodies of deuterons that were perturbed by the laser. However, it was found that …

A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor

Theses and Dissertations

A one-versus-one air combat maneuvering problem is considered wherein a friendly autonomous aircraft must engage and defeat an adversary autonomous aircraft in a beyond visual range environment. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) is leveraged to model the complex and interdependent operations of aircraft, sensors, and weapons utilized in beyond visual range air combat. We formulate a Markov decision process to obtain high-quality decision policies wherein our autonomous aircraft makes maneuvering and missile firing decisions. We utilize a reinforcement learning solution procedure that implements a linear value function approximation to represent state-decision pairs due to the high …

User Acceptance And Adoption Of Smart Homes: A Decade Long Systematic Literature Review, Ibrahim Mashal, Ahmed Shuhaiber, Ayman Wael Al-Khatib

All Works

This survey aims to provide a coherent and bibliometric overview of the theories and constructs employed in smart homes acceptance and adoption literature. To achieve the study aims, we con-ducted a systematic search for every article related to the SH concept, services and applications, user acceptance and adoption, and integrated IoT home appliances and devices, in 10 major library databases, namely, IEEE Digital Library, ACM Digital Library, Association for Information Systems (AIS), Elsevier, Emerald, Taylor and Francis, Wiley InterScience, Springer, Inderscience, and Hindawi. These databases contain literature focusing on smart home adoption using IoT tech-nology. 40 research articles of journal …

A Satellite-Based Monitoring System For Quantifying Surface Water And Mesic Vegetation Dynamics In A Semi-Arid Region, N. E. Kolarik, A. Roopsind, A. Pickens, J. S. Brandt

Human-Environment Systems Research Center Faculty Publications and Presentations

Semi-arid and arid systems cover one third of the earth’s land surface, and are becoming increasingly drier, but existing datasets do not capture all of the types of water resources that sustain these systems. In semi-arid environments, small surface water bodies and areas of mesic vegetation (wetlands, wet meadows, riparian zones) function as critical water resources. However, the most commonly-used maps of water resources are derived from the Landsat time series or single date aerial photographs, and are too coarse either spatially or temporally to effectively monitor water resource dynamics. In this study, we produced a Sentinel Fusion (SF) water …

Merging Black Holes: Assessing The Performance Of Two Analytic Gravitational Waves Models, Dillon Buskirk, Maria Babiuc-Hamilton

Physics Faculty Research

Merging black holes produce the loudest signal in the detectors. However, this is the most difficult signal to accurately predict with analytical techniques. Only computer simulations can account for the nonlinear physics during the collision, but they are inherently complex, costly, and affected by numerical errors. In order to bypass this problem, two analytical models for the merger have been developed: the Implicit Rotating Source (IRS) and the newer Backwards one Body (BoB). In this work, we assess the performance of the BoB model by comparing it with the older IRS model and with the numerical data, identifying its strengths …

Assessing Functional Biodiversity For The Future Of Plants, Planet, And People, Ali Loker

Doctor of Plant Health Program: Dissertations and Student Research

Biodiversity plays a critical role in supporting life in global ecosystems and its links to ecosystem services and sustainability are recognized by scientific and non-scientific communities. Growing awareness of the importance of biodiversity is accelerated by discussions of its loss, and how to design interventions to conserve and mitigate a biodiversity crisis. Stakeholders are funding and implementing assessment strategies at various scales to help direct conservation efforts. There is also growing interest in measuring and communicating biodiversity outcomes.

Functional biodiversity characterizes the multiplicity of life forms into groups based on their diverse contributions to natural and agro-ecosystems. Assessing functional biodiversity …

2023 March - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Net Zero Water Air Force Installations, Kenneth R. Mcknight

Theses and Dissertations

The United States continues to face problems of a reduction in quality and quantity of groundwater sources because water extraction exceeds natural source recharge. The Air Force has recognized the importance of these groundwater sources but has put minimal effort into determining their contribution to the depletion of these sources. The purpose of this study is to determine this contribution by determining whether Air Force installations are net zero water. This is done using a geospatial information system to determine the volume of water recharging groundwater sources associated with an Air Force installation. This volume is then compared to the …

Validation Of Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Density, Dylan J. Shaver

Theses and Dissertations

An in-depth validation of a new bottom-up approach using GNSS Radio Occultation (GNSS-RO) data to generate electron density profiles in the D- and E-region ionosphere. This comparison was completed using daytime ionosonde profiles when sporadic-E (E_s) was not present, and corresponding FIRI profiles. The average GNSS-RO profile is a few kilometers higher in altitude than the ionosonde profiles at the minimum frequency, f min. When the ionosonde profiles are shifted so that the altitudes match at f min, they are in good agreement up to the E-region peak altitude, hmE. Below f min, the …

Design And Modeling Of A Pvdf-Trfe Flexible Wind Energy Harvester, Berkay Kullukçu, Levent Beker

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the simulation, experimentation, and design considerations of a Poly(vinylidene fluoride co-trifluoroethylene)/ Polyethylene Terephthalate (PVDF-TrFe / PET), laser-cut, flexible piezoelectric energy harvester. It is possible to obtain energy from the environment around autonomous sensor systems, which can then be used to power various equipment. This article investigates the actuation means of ambient vibration, which is a good candidate for using piezoelectric energy harvester (PEH) devices. The output voltage characteristics were analyzed in a wind test apparatus. Finite element modeling (FEM) was done for von Mises stress and modal analysis. Resonance frequency sweeps, quality factors, and damping ratios of …

An Exploratory Study On The Effect Of Applying Various Artificial Neural Networks To The Classification Of Lower Limb Injury, Rachel Yun, May Salama, Lamiaa Elrefaei

Turkish Journal of Electrical Engineering and Computer Sciences

This paper explores the application of a deep neural network (DNN) framework to human gait analysis for injury classification. The paper aims to identify whether a subject is healthy or has an injury of the ankle, knee, hip, or heel solely based on ground reaction force plate measurements. We consider how three DNNs-the multi-layer perceptron (MLP), fully convolutional network (FCN), and residual network (ResNet)-can be applied to gait analysis when the number of trainable network parameters far exceeds the number of training samples, and benchmark their performance in this context against that of shallow neural networks. The DNN architectures outperformed …

3d Point Cloud Classification With Acgan-3d And Vacwgan-Gp, Onur Ergün, Yusuf Sahi̇lli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Machine learning and deep learning techniques are widely used to make sense of 3D point cloud data which became ubiquitous and important due to the recent advances in 3D scanning technologies and other sensors. In this work, we propose two networks to predict the class of the input 3D point cloud: 3D Auxiliary Classifier Generative Adversarial Network (ACGAN-3D) and Versatile Auxiliary Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (VACWGAN-GP). Unlike other classifiers, we are able to enlarge the limited data set with the data produced by generative models. We consequently aim to increase the success of the model by …

Study Of Helical Antenna Endowing Short Wire Length And Compact Structure For High-Frequency Operations And Its Exclusive Manufacturing Process, Meli̇h Aslan, Kaan Şik, İzzet Güzelkara, İbrahi̇m Tuna Özdür, Veli̇ Tayfun Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a study of a helical antenna resonating at high-frequency (HF) band with a very compact structure is reported. The designed antenna's S11 parameter magnitude change with frequency was calculated for different geometrical parameters. For each case, first, only a single parameter was changed. Then for a fair comparison, multiple parameters were changed simultaneously while the total wire length was set to be constant. Also, shifts in resonance frequencies and variations in -10 dB bandwidths were investigated. Our results show that resonance behaviour changes distinctively with the geometrical parameters and it allows shortening of the antenna wire length. …