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Imu-Mechanized Discrete Error-State Kalman Filtering With Lie-Group Pose Representations, Daniel P. Koch
Imu-Mechanized Discrete Error-State Kalman Filtering With Lie-Group Pose Representations, Daniel P. Koch
Theses and Dissertations
This dissertation investigates methodologies for consistent Kalman filtering with Lie-group based representations of the vehicle pose. Early results are centered around the relative navigation framework, which maintains filter observability and consistency by only tracking the state relative to the latest keyframe of an odometry system such as visual odometry or laser scan matching. A detailed derivation of a relative multiplicative extended Kalman filter, using a quaternion parameterization of the attitude state, is presented for application to multirotor vehicles. The remainder of the dissertation focuses on Kalman filtering using a Lie-group SE(3) pose representation, which improves filter consistency by correctly modeling …
The Effectiveness Of Dialogic Reading Workshops For Parents Of Children With Developmental Disabilities, Jessica Driskill
The Effectiveness Of Dialogic Reading Workshops For Parents Of Children With Developmental Disabilities, Jessica Driskill
Theses and Dissertations
The purpose of this study is to determine the effectiveness of dialogic reading workshops in improving at-home reading behaviors of both parents and their preschool-aged children. A focus of the study is to understand the dialogic reading experiences of parents with children who have developmental disabilities. Thirteen parents of children at a local preschool participated in one or more phases of the study. Phases included completing a pre-survey, attending the workshop, completing a post-survey, and participating in an interview. Five parents of typically developing children and four parents of children with developmental disabilities participated in the interviews. Participants noted an …
Data-Driven Fusion Of Earth Observation And Hydrologic Data To Forecast Flood Extents At Regional To Continental Scales, Kel N. Markert
Data-Driven Fusion Of Earth Observation And Hydrologic Data To Forecast Flood Extents At Regional To Continental Scales, Kel N. Markert
Theses and Dissertations
Accurate and timely flood inundation forecasts are crucial for mitigating the devastating impacts of floods, which affect 1.47 billion people globally and cause significant economic losses. While traditional flood forecasting methods, such as hydrologic and hydrodynamic models, have limitations in providing comprehensive and spatially explicit inundation information, recent research has focused on leveraging Earth observation data and machine learning for enhanced flood prediction. This dissertation advances the state-of-the-art in data-driven flood inundation forecasting by exploring the capabilities and scalability of the Forecasting Inundation Extents using Rotated Empirical Orthogonal Function (FIER) framework. This dissertation focuses on investigating different aspects of FIER …
Lgbtq+ Identity Development And Individual Vs Group Psychotherapy Experience: A Consensual Qualitative Analysis, Aileen Marie Rands
Lgbtq+ Identity Development And Individual Vs Group Psychotherapy Experience: A Consensual Qualitative Analysis, Aileen Marie Rands
Theses and Dissertations
Multicultural topics, such as LGBTQ+ experience, have accrued predominance within the field of psychology. It has become clear that better understanding minority experience is of utmost importance. Pervasive stigma, discrimination, and mistreatment culminate into minority stress; thus LGBTQ+ individuals face greater risk for poor mental health and seek out psychotherapy at higher rates. Despite this reality, limited psychotherapy research exists in this area generally and essentially no research has looking into the experience of LGBTQ+ individuals in group therapy. The current study investigated experiences of LGBTQ+ clients who have participated in both individual and group psychotherapy. Eleven participants were interviewed …
Comparison Of A Terrestrial And Handheld 3d Laser Scanner In As-Built Building Information Model (Bim) Creation, Cedric Scott Jankowski
Comparison Of A Terrestrial And Handheld 3d Laser Scanner In As-Built Building Information Model (Bim) Creation, Cedric Scott Jankowski
Theses and Dissertations
Advances in computer processing have allowed mobile 3D laser scanners to begin to rival terrestrial scanners in terms of accuracy and scanning speed. While terrestrial scanners are the established instrument used in BIM creation for existing buildings, their cost, immobility, and size warrants a comparison to mobile scanners. This evaluation used scans created with both scanner types, the resulting point clouds, and 3D models created by tracing these point clouds to compare the BIM models and resulting floorplans, which were checked against direct on-site measurements. Because terrestrial scanners are considered state-of-the-art, the evaluation focused primarily on comparing mobile scanner and …
Sustainable Well-Being For Young Adults: An Online Course To Build Ecological And Psychological Flourishing In A Changing Climate, Jeremy Stanley Bekker
Sustainable Well-Being For Young Adults: An Online Course To Build Ecological And Psychological Flourishing In A Changing Climate, Jeremy Stanley Bekker
Theses and Dissertations
Sustainable well-being is "happiness that contributes to individual, community and/or global well-being without exploiting other people, the environment or future generations" (O'Brien, 2010, p. 2). Sustainable well-being education may encourage environmentally sustainable behavior while also teaching people how to live meaningful lives. However, there is currently a lack of research-based disseminable courses for teaching sustainable well-being. We hypothesized that taking the course would result in lower eco-anxiety and higher well-being, as well as increased pro-environmental self-efficacy and pro-environmental values. We used a randomized crossover repeated measures research design to assess pre and post effects. Quantitative results indicated that participating in …
Immersive Virtual Reality Heavy Equipment Simulator Training Effectiveness And Participant Performance Comparison, Zachary E. Calderon
Immersive Virtual Reality Heavy Equipment Simulator Training Effectiveness And Participant Performance Comparison, Zachary E. Calderon
Theses and Dissertations
Immersive Virtual Reality (IVR) simulator training is an interactive form of computer-based training that can positively promote the transfer of skills from training to trainees. Even at a lower physical fidelity IVR simulators may more effectively train individuals on the operation of virtual heavy equipment compared to written, demonstrative, and oral computer-based training. IVR simulator training may also be beneficial for implementation of heavy equipment operation training as a means to promote familiarization of controls and foster self-efficacy and confidence in trainees. A multi-stage IVR simulator was created for this study that both trained participants on wheel loader operations and …
Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Theses and Dissertations
The Department of Defense (DoD) faces significant challenges in maintaining mission-critical infrastructure within highly corrosive environments, with annual costs exceeding $22.5 billion to combat corrosion. This thesis investigated the interplay between environmental severity, sustainment funding, and infrastructure performance. This research utilized Facility Sustainment, Restoration, and Modernization (FSRM) funding data, statistical analyses, and regression modeling, to evaluate how Environmental Severity Index (ESI) categories influence Base Condition Index (BCI) trends and the efficacy of the Facility Sustainment Model (FSM). The analysis revealed that installations in higher ESI categories required significantly greater investment per square foot to achieve comparable improvements in BCI. The …
Emergency Response Digital Twin: Integrating Augmented Reality And Live Position Data With Simulation-Aided Decision-Making In Real-Time, Joseph Fuentes
Emergency Response Digital Twin: Integrating Augmented Reality And Live Position Data With Simulation-Aided Decision-Making In Real-Time, Joseph Fuentes
Theses and Dissertations
With the growing use of simulation across industries, the digital twin remains an underexplored research area, particularly in emergency management and response. Its real-time updating capability is often overlooked due to the misconception that "digital twin" is merely a complex term for simulation. This paper highlights its distinctiveness through an evasion exercise involving two independent entities in a collocated environment. Using a highly integrated virtual environment (HIVE) and internet of things (IoT) devices, we link the physical system with an analytical simulation, demonstrating the impact of lag times in high-pressure scenarios. The computational model leverages agent-based modeling (ABM) and discrete-event …
Proof Of Concept: Using Uas Technology To Accomplish Aerial Roof Inspections, Madison R. Fanning
Proof Of Concept: Using Uas Technology To Accomplish Aerial Roof Inspections, Madison R. Fanning
Theses and Dissertations
With the growing use of simulation across industries, the digital twin remains an underexplored research area, particularly in emergency management and response. Its real-time updating capability is often overlooked due to the misconception that "digital twin" is merely a complex term for simulation. This paper highlights its distinctiveness through an evasion exercise involving two independent entities in a collocated environment. Using a highly integrated virtual environment (HIVE) and internet of things (IoT) devices, we link the physical system with an analytical simulation, demonstrating the impact of lag times in high-pressure scenarios. The computational model leverages agent-based modeling (ABM) and discrete-event …
Investigation Of The Convective Heat Transfer Driving Potential For Hypersonic Flows, Roderick A. Mills
Investigation Of The Convective Heat Transfer Driving Potential For Hypersonic Flows, Roderick A. Mills
Theses and Dissertations
Accurately determining adiabatic wall temperature is critical for characterizing surface heating in hypersonic flows. The differences between adiabatic wall temperature and stagnation temperature for Mach 6 flow are examined. A two-dimensional explicit finite difference scheme was developed to analyze heat transfer within an angled wedge and to assess the applicability of the classical semi-infinite solid solution to the Fourier Heat Equation for estimating adiabatic wall temperature and convective heat transfer coefficients. Experimental surface temperature data were extracted from infrared thermography obtained during Mach 6 wind tunnel tests, and the semi-infinite solid solution was applied to estimate the adiabatic wall temperature. …
Thin-Filament Pyrometry In A Rotating Detonation Engine, Theodore B. Guetig
Thin-Filament Pyrometry In A Rotating Detonation Engine, Theodore B. Guetig
Theses and Dissertations
Rotating Detonation Engine (RDE) proves beneficial by creating a pressure rise across the combustor rather than a pressure drop seen in traditional aircraft combustors. Coupled with this high pressure is a high temperature in the detonation engine that is difficult to measure as it varies spatially and temporally. Thin-Filament Pyrometry (TFP) was performed on a 6-in RDE to measure these high temperatures. Temperature profiles were obtained over a variety of mass flows, equivalence ratios, and different axial locations within the RDE providing insight into the mixing process and where the heat release occurs. Successful determination of these temperature profiles within …
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus
Theses and Dissertations
This research models and analyzes the impact of stochastic travel times on port selection during a large-scale mobilization of equipment from continental United States installations to deployment locations using sealift ships. A stochastic mixed-integer programming model is developed to minimize the average arrival time of equipment into theater. The model is solved using Sample Average Approximation. In the first stage, the model selects ports to open and assigns installations, equipment, and ships to open ports. In the second stage, travel times are realized, and equipment is assigned to specific ships that are scheduled to depart. Results show that the marginal …
Evaluating Educational Benefits Of A Custom Cyber Game: ‘Hvac Attack!’, Jillian S. Valente
Evaluating Educational Benefits Of A Custom Cyber Game: ‘Hvac Attack!’, Jillian S. Valente
Theses and Dissertations
Cyber competition and conflict remain an enduring concern for the Department of Defense (DoD). Positive control of cyberspace is crucial across the vast diversity of military operations and supporting activities. Military members play an important role in cyber prevention, detection, and remediation, but most receive relatively little training outside of the annual Cyber Awareness Challenge. Particular career fields within the DoD may benefit from specialized training in cybersecurity, in particular the civil engineering (CE) community supporting critical infrastructure protection. Prior research has suggested that game-based learning (GBL) can be beneficial for teaching cyber concepts.
A Machine Learning/Deep Learning Investigation On Remote Manufacturing Machine State Classification, Ajeet S. Parmar
A Machine Learning/Deep Learning Investigation On Remote Manufacturing Machine State Classification, Ajeet S. Parmar
Theses and Dissertations
Determining the extent of manufacturing capabilities with respect to adversarial or hostile nations is a topic of significant importance to the Department of Defense. Manufacturing capabilities can serve as indications of a nation's industrial power and its economy of force in warfare. Remotely detecting machine operations via electromagnetic sensors may be possible via Deep Learning (DL) and Machine Learning (ML) algorithms. To predict machine states, sensor data is collected externally from a machine shop on a college campus to monitor the operating states of lathes and mills in individual and concurrent operation. Furthermore, several sensors are placed in various positions, …
Uranium Particle Classification Using Statistical Machine Learning And Deep Neural Networks For Nuclear Forensics, Lee C. Lambert
Uranium Particle Classification Using Statistical Machine Learning And Deep Neural Networks For Nuclear Forensics, Lee C. Lambert
Theses and Dissertations
The classification of uranium particles from scanning electron microscopy (SEM) imagery is critical to nuclear forensics, but has traditionally relied solely on skilled analysts whose classification accuracy and procedures may vary widely. Existing morphology lexicology [1] provides standardization guidelines to aid analysts but cannot fully address analyst variability. Using a dataset of 1,906 SEM images across 13 unevenly distributed particle classes and 73 magnification levels, final accuracy between statistical and deep learning methods were compared to find the best classification techniques. Ultimately, the deep learning model achieved an impressive 82% accuracy (80% balanced accuracy) on a withheld test set. This …
Assessing The Feasibility Of Managed Aquifer Recharge For The United States Air Force, Daniel Hendrix
Assessing The Feasibility Of Managed Aquifer Recharge For The United States Air Force, Daniel Hendrix
Theses and Dissertations
Water stress is becoming an increasing global issue, with 4 billion people (50% of the world’s population) experiencing water stress at least one month per year. By 2050, 60% of the world’s population and $70 trillion USD in global gross domestic product will be affected. This research analyzes 78 CONUS USAF installations to determine location-specific water stress and feasible Managed Aquifer Recharge (MAR) solutions. Although thousands of MAR projects have been implemented globally, active-duty USAF installations have yet to contribute to solving this growing issue. Important factors such as required subsurface conditions, physical limitations, design, cost, and regulatory constraints are …
Cloud One Migration Duration And Its Drivers, Grayson T. Hall
Cloud One Migration Duration And Its Drivers, Grayson T. Hall
Theses and Dissertations
As modern warfare evolves with rapid technological advancements, cloud computing plays a critical role in managing the vast amounts of data required for real-time decision making, as well as enabling seamless organizational access to mission-critical programs and information from around the globe. Recognizing its importance, the Department of Defense (DoD) identified cloud computing as essential for maintaining the military’s technological edge. However, despite cloud computing’s strategic significance, the DoD faces challenges in successfully implementing department-wide cloud computing. In contrast, the Air Force’s cloud computing environment, Cloud One, is fully operational and has already integrated over 145 systems into its platform. …
Isotopic Analysis Of Lithium Hydroxide Monohydrate Using Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (Libris) And Machine Learning, Madison R. Moran
Isotopic Analysis Of Lithium Hydroxide Monohydrate Using Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (Libris) And Machine Learning, Madison R. Moran
Theses and Dissertations
High-resolution Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (LIBRIS) is implemented to record the 15.8 pm Li I 670.8 nm isotopic shift in LiOH · H2O samples of varying 6, 7Li abundance. A simple univariate linear regression demonstrates an acquired isotopic shift of 13.813 ± 1.21 pm in samples varying from 3 to 95 6Li at%. Supervised machine learning regressions are trained on self-reversal wavelength locations in order to quantify 6Li abundance. A stacked ensemble using two base learners yields the superlative characterization of 6Li abundance with RMSE of 5.66 at% and detection limit of 18.8 at%. Using …
Analyzing And Mapping Hypersonic Cruise Vehicle Maneuvers, Kyle T. Monsma
Analyzing And Mapping Hypersonic Cruise Vehicle Maneuvers, Kyle T. Monsma
Theses and Dissertations
This thesis develops a computational framework for analyzing the stability, control, and maneuverability of hypersonic cruise vehicles using surrogate modeling and trajectory propagation techniques. A polynomial ridge regression approach is implemented to create a continuous aerodynamic model from discrete force-moment data, enabling rapid stability and control assessments across Mach and altitude ranges. Vinh’s equations of motion are utilized to account for Earth’s curvature and gravitational effects, refining trajectory analysis for maneuver feasibility studies. Energy maneuverability diagrams, turn rate charts, and short-period stability metrics are generated to visualize flight performance constraints and dynamic stability characteristics. The results highlight the impact of …
Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking, Liam A. Weinfurtner
Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking, Liam A. Weinfurtner
Theses and Dissertations
This work introduces a bi-directional, multi-object detection framework that integrates pose estimates from both receiver- and tanker-mounted cameras to improve accuracy and redundancy. A modular YOLO-based detection pipeline is trained using synthetic and real imagery, leveraging a bootstrap transfer learning approach to enhance sim-to-real performance. System evaluation in both virtual and real-world environments demonstrates improved detection robustness, pose estimation accuracy, and scalability. These advancements contribute to the development of AI-driven vision systems for AAR and other autonomous docking applications.
Investigation Of Neutron Inelastic Scatter Cross Sections On 16O, Molly A. Wakeling
Investigation Of Neutron Inelastic Scatter Cross Sections On 16O, Molly A. Wakeling
Theses and Dissertations
Nuclear data underpin a number of applications across nuclear reactor design, medicine, astrophysics, nonproliferation, national security, and other related fields. However, data are conflicting or missing across the spectrum of isotopes and reactions, and theoretical calculations can only go so far to predict nuclear properties. A key reaction with incomplete data is neutron inelastic scatter on 16O, which reduces neutron energies and produces high-energy gamma rays that are often not taken into account in simulations of nuclear reactors, nuclear weapon detonations, nuclear fusion, and other areas. To fill these gaps, the Gamma-Energy Neutron-Energy Spectrometer for Inelastic Scattering, or GENESIS, …
Early-Phase Cost Estimation For Department Of Defense Construction Projects Via Artificial Neural Networks: Implications And Policy Recommendations For Artificial Intelligence Integration, Kobe T. Thompson
Theses and Dissertations
The Department of Defense lost over 500 million dollars between 2016 and 2024, partially due to poor early cost estimates resulting in cost overruns. practice for cost estimation relied on parametric techniques that incorporate historical data, subject matter experts in cost estimating, and predictive software applications. The main motivation for this study was to assess the viability of artificial neural networks as a means of providing a more accurate cost estimate in the early design phases of a construction project. The dataset initially contained approximately 48,000 data points from a database of various Air Force projects, including maintenance, repair, minor …
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp
Theses and Dissertations
Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …
Advancing Defense Software Cost Estimation Through Regression, Probabilistic, And Machine Learning Models, Stephen D. Chatterton
Advancing Defense Software Cost Estimation Through Regression, Probabilistic, And Machine Learning Models, Stephen D. Chatterton
Theses and Dissertations
Accurately estimating software costs is critical for effective project management within the Department of Defense (DoD), where early decisions shape resource allocation and risk management. This work evaluates regression-based Cost Estimating Relationships (CERs), probabilistic models, and machine learning techniques to address limitations of traditional estimation methods. Using records from two DoD repositories, the analysis applied Ordinary Least Squares (OLS) regression, Multinomial Logistic Regression (MLR), Random Forest, and neural networks to model and classify software costs, with key predictors including Source Lines of Code (SLOC), Equivalent Source Lines of Code (ESLOC), and programming hours. The findings highlight strengths and trade-offs of …
The Location Set Covering Disruption Problem, Richard A. Sheldon
The Location Set Covering Disruption Problem, Richard A. Sheldon
Theses and Dissertations
This research models and analyzes a variant of the Location Set Covering Problem (LSCP) in a bilevel, game theoretic setting by posing the LSCP as a non-cooperative attacker-defender Stackelberg game, where facilities are to be emplaced by the defender from a boarder set of potential facility locations to cover a set of demands; however, an attacker removes the possibility of emplacing q specific facility locations with the objective to remove the maximum weighted value demands, and then lexicographically maximize the cost of coverage of remaining demands. A novel methodology leveraging lexicographic programming computed an optimal solution for 98% of all …
Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones
Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones
Theses and Dissertations
The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.
Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson
Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson
Theses and Dissertations
This research investigated the performance of a Tsunami T50 Vapor Compression Cycle styled Atmospheric Water Generation (AWG) machine operated under ambient conditions in Dayton, Ohio. Water yield from the device was measured volumetrically and these values are paired with respective weather data, collected from a local monitoring station, to build an Artificial Neural Network in MATLAB and JMP software. Water yield varied over the course of this study but averaged 1.2L and maxed at 5L for 4-hour operating periods. This work is part of a 3-year project; future data is needed to enhance both training and validation of the model …
Geo-Spatial Mapping Of Sentiment Analysis With Transformer-Based Models, Dugan J. Turnbow
Geo-Spatial Mapping Of Sentiment Analysis With Transformer-Based Models, Dugan J. Turnbow
Theses and Dissertations
The public sentiment of events of interest, and their impacts, is vital for decision makers to allocate resources. This research develops a robust algorithm for aggregating sentiment analysis from social media and published articles, while contextualizing results through spatial and temporal mapping. The methodology employs two transformer-based language models for sentiment analysis and named entity recognition (NER). Sentiment scores are generated and augmented using explicit location data, such as latitude and longitude, and implicit location data derived through NER or location features. Results are mapped using a geo-tagged location dictionary, enabling visualization of sentiment trends at state and county levels …
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
Theses and Dissertations
As fighter aircraft become more complex and technology, such as autonomy, is introduced, it is essential to anticipate the critical tasks and information pilots need to accomplish their mission with these new systems. Fighter pilots operate in highly demanding situations where the consequences of failure are severe and require their systems to provide the right information for the task. Traditionally, these designs are informed through Critical Task Analyses of existing systems. This research produced a method for modeling critical task analysis and information requirements using model-based systems engineering. The scenario was a fighter aircraft conducting basic fighter maneuvers in a …