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Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson
Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson
Theses and Dissertations
Unmanned Aerial Vehicles (UAVs) have seen increased usage over the past two decades during the Global War on Terrorism (GWOT), operating in low-risk environments against dispersed enemies with minimal counter-drone capabilities. However, as the U.S. military shifts focus to Multi-Domain Operations (MDO) and Large Scale Combat Operations (LSCO), UAVs face significantly higher risks, including frequent and successful attacks, as well as the exploitation of their technology. Battle damage assessment (BDA) is not new; however, autonomous self-assessment by UAVs represents a novel advancement. Currently, UAV BDA relies on manual inspection, requiring approximately eight hours per drone. By adopting self-sensing technology, UAVs …
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 …
Model-Based Approach To Support Safety Driven Design And Satisfy Mil-Std-882e Requirements With Stpa Coordination: A Case History In Suas Defense Acquisition, Daniel A. Shea
Theses and Dissertations
Increasingly complex defense systems that are routinely overbudget and behind schedule are driving digital engineering initiatives in the defense acquisition industry. MBSE offers a solution to counter this issue but the lack of guidance on how to implement it has led to significant experimentation. One MBSE area of interest is system safety. This research demonstrates how to conduct model-based Systems Theoretic Process Analysis (STPA) to meet the unique system safety process requirements from MIL-STD882E. Based in systems theory, STPA extended for coordination enables a safety-driven design process of complex systems. This research investigated conducting STPA in the SysML-RAAML modeling language …
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Theses and Dissertations
Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …
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.
Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler
Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler
Theses and Dissertations
Per- and polyfluoroalkyl substances (PFAS), widely referred to as “forever chemicals,” exhibit high environmental persistence and potential health risks due to their robust carbon-fluorine bonds. These substances are prevalent in aqueous film-forming foams (AFFF), used in industrial and military applications, and are known to contaminate environmental surfaces, including concrete. This study aims to characterize the molecular-level interaction energies of six PFAS species—PFOA, PFOS, PFHxS, PFHxA, 6:2 FTS, and PFBS—with calcium silicate, a key component of concrete, using density functional theory (DFT) calculations. Change in Gibbs free energy (ΔG) was determined for each of the interactions, revealing negative ΔG values for …
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case
Theses and Dissertations
United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …
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 …
Cognitive Warfare In The South China Sea: Analyzing Media Influence And Public Opinion In Taiwan, Wyatt F. Blatti
Cognitive Warfare In The South China Sea: Analyzing Media Influence And Public Opinion In Taiwan, Wyatt F. Blatti
Theses and Dissertations
In a time where conflict extends beyond traditional battlefields, cognitive warfare emerges as a powerful tool to influence perceptions and gain strategic advantages. This study investigates China’s cognitive warfare strategies against Taiwan through trend analysis, topic modeling, and sentiment analysis of news media articles from March 2013 to August 2024 to uncover evolving techniques and mitigation efforts. The findings highlight the potential for tracking cognitive campaigns overtime but will require more than news media alone and suggests future research to better understand indicators of cognitive warfare.
Understanding The Acceptance Of Digital Tools Within An Air Force Environment Using The Utaut2 Model, Britton J. Edwards
Understanding The Acceptance Of Digital Tools Within An Air Force Environment Using The Utaut2 Model, Britton J. Edwards
Theses and Dissertations
This research paper explores factors influencing digital tool adoption in a military context, using a modified UTAUT2 model with the inclusion of Military Status as a moderating factor. The study examines the moderating effects of Military Status on Social Influence towards Behavioral Intention and Behavioral Intention on Use Behavior. Data was collected through a Likert-scale survey from respondents across multiple Department of the Air Force (DAF) organizations. Findings revealed Social Influence had the potential to positively influence Behavioral Intention to use digital tools, but military experience did not significantly moderate this relationship. However, past experience with the legacy tool and …
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 …
Fatigue Behavior Of An Advanced Sic/Sic Composite With An Array Of Small Cooling Holes At 1200°C, Tess K. Panchyshyn
Fatigue Behavior Of An Advanced Sic/Sic Composite With An Array Of Small Cooling Holes At 1200°C, Tess K. Panchyshyn
Theses and Dissertations
Tension-tension fatigue behavior of an advanced melt-infiltrated (MI) silicon carbide/silicon carbide (SiC/SiC) composite was evaluated, and basic tensile properties measured, at 1200°C in laboratory air. The composite consists of a melt-infiltrated SiC matrix reinforced with laminated Hi-Nicalon Type-S fibers woven in a 5-harness satin weave. The Hi-Nicalon-S fiber preforms were coated with a boron nitride (BN) fiber coating by chemical vapor infiltration (CVI). The melt-infiltrated matrix was consolidated by combining CVI-SiC with SiC particulate slurry and molten silicon infiltration. The finished ceramic matrix composite (CMC) had a fiber volume fraction of 33%. Additionally, the effect of multiple small holes on …
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.
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 …
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Theses and Dissertations
The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.
Calibration And Demonstration Of A Dropped Channel Polarimetric Compressive Sensing Radar System, Cameron G. Goodbar
Calibration And Demonstration Of A Dropped Channel Polarimetric Compressive Sensing Radar System, Cameron G. Goodbar
Theses and Dissertations
The Air Force Institute of Technology (AFIT) Dropped Channel Polarimetric Compressive Sensing (DCPCS) Radar System is a polarimetric radar utilizing four horn antennae with a unique cross-coupling architecture that enables direct control of system parameters to embed signals into adjacent channels. This thesis characterizes the nature of the system, develops system calibration, and illustrates the performance of the DCPCS technique under multiple system configurations. As shown in the results, DCPCS can successfully reconstruct full-polarization data from a subset of polarization measurements. In many cases, the target estimation and signal reconstruction is precise despite less-than-ideal conditioning of the canonical target dictionary …
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman
Theses and Dissertations
This study examines the effects of active learning compared to didactic methodologies on two soft skills, namely teamwork and self-efficacy using regression analyses and connected letter reports. Learning styles and personality traits were used as predictors. Findings indicate significant interaction effects between methodology, aural learning style, and personality traits on self-efficacy and teamwork ability. The findings highlight the nuanced role of learner traits in shaping teamwork outcomes across instructional methods. While active learning supports soft skills, individual differences must be considered in instructional design to optimize teamwork in technical education settings.
How Does An Air Force Instructor Analyze Officer Occupational Competencies And Translate Them Into Professional Development Courses?, Julia A. Howard
How Does An Air Force Instructor Analyze Officer Occupational Competencies And Translate Them Into Professional Development Courses?, Julia A. Howard
Theses and Dissertations
This thesis examines how Air Force instructors translate officer occupational competencies into professional development courses. The study aims to address a pressing need to align Civil Engineer education with the Department of the Air Force objective of competency based education in the midst of changing operational demands. The methodology uses expert elicitation, thematic analysis, qualitative and quantitative statistics to formulate a curriculum development methodology. Data collection involved an expert elicitation from subject matter experts in the Civil Engineer career field. This data helped to pair 32E competencies with course learning objectives. The expert opinions provided insight into where civil engineering …
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Theses and Dissertations
This research develops a digital twin of the global maritime shipping system to model disruptions in major shipping lanes like the Suez and Panama Canals. By incorporating live ship-tracking data, the model simulates closures, forecasts queue lengths, and determines the best rerouting options. Findings show that canal closures cause large traffic backlogs and increased congestion at alternative chokepoints, while rerouted ships may face higher piracy risks in regions like the Gulf of Guinea and the Strait of Malacca. This tool helps decision-makers respond effectively to maritime disruptions.
Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds
Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds
Theses and Dissertations
Class imbalance poses significant challenges in machine learning classification. This study evaluates the performance of seven models (ANN, k-Means, kNN, LDA, LR, SVM, XGBoost) across multiple imbalance levels (10\%, 5\%, 1 \%, 0.5\%) and investigates the effectiveness of sampling techniques (Undersampling, SMOTE, SMOTE-ENN). ANOVA results confirm that model choice is the most critical factor, with XGBoost and SVM demonstrating superior robustness. SMOTE improves recall but reduces precision, while undersampling generally degrades overall performance. While significant, imbalance levels do not play a critical role in model effectiveness.
Job Demands And Resources: A Look At The Vha Workforce To Support Dod Goals, Anthony J. Rivera
Job Demands And Resources: A Look At The Vha Workforce To Support Dod Goals, Anthony J. Rivera
Theses and Dissertations
This study investigates the relationships between job demands, job resources, burnout, turnover intention, and workplace attitudes among employees of the Veterans Health Administration (VHA) through the lens of the Job Demands-Resources (JD-R) model. The findings reveal both expected and novel insights. Consistent with prior research, the study confirms that excessive job demands, without enough resources to balance then, lead to burnout. This, in turn, increases turnover intention and negatively affects how employees view leadership and the work environment. A significant discovery, however, challenges conventional assumptions: favorable job demands were positively correlated with turnover intention, suggesting that employees in favorable roles …