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An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves
An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves
Theses and Dissertations
This research establishes a novel agent-based modeling framework to establish the linkage between disaster-induced facility damage and mental health outcomes and the evaluation of treatment methods within the civilian and USAF mental health spheres. The study models the degradation and recovery of agent mental health using simulated data and evaluates the efficacy of three distinct treatment approaches through statistical methods. The methodology integrate agent-based modeling with resilient engineering concepts to simulate mental health resilience curves based on vulnerability, exposure, and facility damage. Agents’ mental health indices were tracked through phases of degradation, stagnation, and recovery based on the three treatments …
Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Theses and Dissertations
This study investigated the quality of untreated water collected from a vapor compression-based atmospheric water generator (AWG) operated outdoors in Dayton, Ohio. The concentrations of bacterial and chemical constituents were determined. The concentration of culturable bacteria was between 200 and 2300 CFU/mL, significantly higher than the reference levels described in recreational and drinking water quality guidance. Three discrete bacteria phenotypes were visually identified; two were yellow in color, rod-shaped and gram-negative while the third was milky white, circular, and gram-positive. Chemical analysis on 15 randomly selected samples revealed the presence of Barium (average = 0.16 mg/L), Magnesium (0.08 = mg/L), …
Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei
Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei
Theses and Dissertations
Recent advancements in 3D cargo scanning and machine learning offer solutions to improve cargo processing reliability. This study enhances a 3D cargo scanning system by addressing software crashes, connectivity failures, and image accuracy issues limiting its operational effectiveness. A systematic approach identified the primary causes of system failures. System updates were implemented, followed by 30 pre- and post-update trials to evaluate reliability improvements. Statistical t-tests showed a significant reduction in failures, although processing time slightly increased. Results indicated that targeted hardware and software updates enhanced cargo scanning efficiency and dependability. Future work will focus on refining sensor calibration, optimizing network …
Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy
Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy
Theses and Dissertations
This research evaluates the impact of electronic warfare, particularly jamming, on an audio-based drone detection wireless sensor network (WSN) using Monte Carlo simulations. A six-node IEEE 802.15.4 network, with five edge nodes and a central sink, is tested against jamming probabilities ranging from 0-100% in 5% increments across 30 iterations per configuration. Results show that packet delivery ratio (PDR) degrades linearly at approximately 20% per jammed node, while detection performance often exceeds PDR. Even at 80% jamming, detection success rates remain above 57%, highlighting resilience despite network degradation. The study reveals that jamming effectiveness depends on node placement relative to …
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 …
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 …
Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst
Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst
Theses and Dissertations
Every acquisition program begins with a requirement, and for those programs to succeed, robust requirements engineering (RE) must be implemented. RE encompasses eliciting, analyzing, specifying, and validating requirements—a critical process throughout a program's lifecycle. Despite its importance, RE faces challenges such as scope creep, ambiguity, redundancy, and inadequate automation support, often exacerbated by reliance on historical data. To address these issues, this thesis leverages advancements in Generative Technology, particularly large language models (LLMs) such as Generative Pre-Trained Transformers (GPTs). This research developed two GPT-based tools: the Single Requirement Analysis Tool and the Set of Requirements Analysis Tool. These tools were …
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 …
Air-Based Chemical Patient Decontamination Methodologies For Arctic Regions Using Methly Salicylate As A Chemical Agent Surrogate On A Litter-Bound Manikin, Marcus D. Shadd
Theses and Dissertations
This study evaluated a mobile air shower for patient decontamination without disrobing or rinsing, an alternative for Arctic conditions where water is scarce. A manikin in extreme cold weather gear was exposed to 10 µL of methyl salicylate (MeS), a sulfur mustard surrogate, and placed in a horizontal chamber on a military litter. Airborne MeS was measured using a ppbRAE 3000 detector to assess inhalation risk for the patient and decontamination team. Three methods were tested: an air-knife system, paper towels, and no decontamination, with 10 trials each (30 total). ANOVA analysis showed significant reductions in airborne MeS with air-knife …
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 …
Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy
Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy
Theses and Dissertations
Military airfields and civilian airports serve as foundational nodes in the global transportation network, enabling travel, economic growth, and the projection of national security. This study investigates the relationship between climate variables projected through climate change and pavement degradation, with a focus on Fairchild Air Force Base (AFB). Using principal component regression (PCR), the research integrates historical pavement condition index (PCI) data with climate variables, including snowfall, precipitation, freeze-thaw cycles, solar irradiance, and wind speed to develop a predictive model of pavement performance under future climate scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. These models, for both Portland …
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 …
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Theses and Dissertations
A method for characterizing unknown targets using a hyperspectral polarimetric light detection and ranging (LiDAR) system is presented. Light reflected from manmade objects tends to be more polarized than light reflected from objects in the natural world. As such, polarization measurements can be used in remote sensing applications to differentiate artificial and natural objects. Previous works have attempted to characterize objects through passive polarimetric imagery. Methods developed by Cain and Lemaster and Cunningham facilitate reconstruction of the Stokes Vector from returning light. Martin used multispectral polarimetry to classify targets when the angle of incidence (AOI) is close to 0º. Here, …
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
Theses and Dissertations
The integration of automated processes in defense continues to expand, enhancing the lethality of military forces. Artificial intelligence accelerates decision-making cycles, removes the constraints of human-operated hardware, and improves coordination by enabling seamless integration across multiple systems. Suppression of Enemy Air Defenses (SEAD) missions are critical to the United States (U.S.) military, as they neutralize hostile air defense systems, ensuring air superiority and enabling safe and effective operations for aircraft in contested environments. Therefore, it is necessary to pair emerging autonomous capabilities with an important mission set in defense. This research investigates the Autonomous Unmanned Air-to-Ground Strike (AUAGS) problem, modeling …
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Theses and Dissertations
The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Theses and Dissertations
Uncertainty is a major challenge in optimization, especially in problems where unpredictable costs impact decision-making. Robust optimization addresses this by modeling uncertainty via uncertainty sets. These sets are then used such that solutions hold under worst-case scenarios, with success depending on the accuracy of the uncertainty sets. This research examines the use of conformal prediction to construct uncertainty sets for RO, an approach that has not been widely explored. We test split and full conformal prediction in a robust optimization minimum cost flow problem, and comparing them to interval-based and normal-based ellipsoidal uncertainty sets. Experiments run across different network structures …
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, …
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Theses and Dissertations
Solar Particle Events (SPEs) are high-energy phenomena from the Sun that pose risks to technology, human health, and Air Force operations. Accurate prediction of SPEs exceeding 100 MeV is crucial for mitigating these risks. This thesis explores using Bayesian statistical models to predict such events, integrating prior knowledge from solar physics with the ability to update predictions based on new data. The research uses a dataset spanning three solar cycles (21–23) and incorporates attributes like flare fluence, peak flux, latitude, longitude, and class. Four Bayesian models (PyMC, Bnlearn, and two Dredge models) were compared to machine learning models. The Bayesian …
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Theses and Dissertations
This research utilizes reinforcement learning (RL) to train two blue agents each imbued with a directed energy weapon (DEW) in a 2v2 within visual range air combat maneuvering problem. A phased solution approach is employed to repeatedly tune and train several RL algorithm implementations: Proximal Policy Optimization (PPO) and Double Deep Q Network (DDQN). Phase I of training includes reward shaping for basic flight elements such as altitude, airspeed, and target proximity. Phase II of training builds off policies developed in Phase I, but rewards emphasize winning the aerial engagement by any means necessary. DDQN significantly outperforms PPO in Phase …
An Analysis Of Hardware Modification Cost: A Test Of A 1:1 Ratio Heuristic, Oluwasegun Faleye
An Analysis Of Hardware Modification Cost: A Test Of A 1:1 Ratio Heuristic, Oluwasegun Faleye
Theses and Dissertations
Accurate cost estimation for Department of Defense (DoD) hardware modification programs remains a critical challenge due to the complexity of Group A and Group B modifications and their associated installation costs. This study evaluates the validity of a 1:1 ratio heuristic, which suggests that Group A modification kits combined with installation costs should equate to the costs of Group B modification kits. This study analyzes cost relationships across system types and modification categories using a dataset of 255 modification programs from the Air Force Life Cycle Management Center (AFLCMC). Statistical methods, including means tables and regression modeling, evaluate the validity …
Mediating And Moderating Effects Of Job Satisfaction, Organizational Commitment, Perceptions Of External Markets, And Work-Life Balance On Employee Retention, Naya J. Gillespie
Mediating And Moderating Effects Of Job Satisfaction, Organizational Commitment, Perceptions Of External Markets, And Work-Life Balance On Employee Retention, Naya J. Gillespie
Theses and Dissertations
Employee retention remains a critical challenge for organizations across industries, particularly in environments with high turnover rates and competitive external job markets. This thesis examines the correlations between organizational commitment, job satisfaction, work-life balance, and perceptions of external job markets to uncover their collective and individual impacts on employee retention. Using quantitative research design, data was collected through an online survey of 240 participants across various hierarchical levels. Key findings indicate that organizational commitment and job satisfaction significantly influence retention, with job satisfaction also serving as a mediator between organizational commitment and turnover intentions. Work-life balance plays a direct role …
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. …
Using Mbse To Facilitate Integration And Stakeholder Support For Autonomous Aerial Refueling Flight Test, Kevin G. Keth
Using Mbse To Facilitate Integration And Stakeholder Support For Autonomous Aerial Refueling Flight Test, Kevin G. Keth
Theses and Dissertations
he Department of Defense has pushed to implement Digital Material Management, to include Engineering (DE) and Model-Based Systems Engineering (MBSE) into acquisition processes, publishing various supporting documents such as the Systems Engineering Guidebook, DoDI 5000.97 Digital Engineering, and DoD Reference Architecture Description. DE and MBSE aims to establish a digital authoritative source of truth accessible to all stakeholders responsible for system architecture. However, within multidisciplinary teams, individuals often come from diverse professional backgrounds unrelated to DE and systems engineering, making it challenging to fully leverage the benefits of the digital model. This paper describes an MBSE model that adopts a …
Safety-Driven Concept Development Using System Theoretic Process Analysis Extended For Coordination In A Model Based Environment: A Case Study On Autonomous Satellite Teaming, Taylor L. Matarazzo
Safety-Driven Concept Development Using System Theoretic Process Analysis Extended For Coordination In A Model Based Environment: A Case Study On Autonomous Satellite Teaming, Taylor L. Matarazzo
Theses and Dissertations
Rigorous system safety analysis methods, allow programs to identify potential problems helping to minimize their impact to program schedules and budgets. In the contested, congested, and competitive space environment, coordination within and between systems is critical to mission success. System Theoretic Process Analysis extended for Coordination (STPA-coord) can prescriptively analyze these coordination interactions. STPA-coord shifts the conversation of system safety from elements ofreliability to elements of control, providing insights that holistically analyze the system. As studies suggest, decisions made early in a systems design determine 80-86% of a programs final cost, therefore integrating system safety as early into design can …
Weighed And Measured: Toward An Evaluation Method For Digital Models In Source Selection, Liam N. O'Neill
Weighed And Measured: Toward An Evaluation Method For Digital Models In Source Selection, Liam N. O'Neill
Theses and Dissertations
Inspired by a recent model-based source selection conducted by the Advanced Range Threat System (ARTS) Program Office at Hill AFB, this research effort explored the development of new tools the DoD could use when evaluating models submitted with proposals. Specifically, the effort aimed to incorporate the Multi-Objective Decisions Analysis (MODA) framework into SysML diagrams as a solution for technical evaluations on models submitted with offeror proposals, eventually producing the Model-Based Decision Tool (MBDT). The MBDT is built from a Value Hierarchy based on key system requirements, each weighted by priority and measured by their own Single-Dimensional Value Functions (SDVFs). By …
Developing Core Competencies For The Air Force Civil Engineer Asset Management Career Field, David A. Rochester
Developing Core Competencies For The Air Force Civil Engineer Asset Management Career Field, David A. Rochester
Theses and Dissertations
The United States Air Force (USAF) relies on a highly trained and capable workforce to maintain and manage its infrastructure, ensuring mission readiness and operational effectiveness. However, the increasing complexity of asset management, aging infrastructure, and evolving global threats necessitate a structured approach to developing the competencies required for Air Force Civil Engineer Asset Managers. This research aims to identify, develop, and validate core competencies specific to this career field, utilizing a structured methodology that combines an Education Working Group (EWG) with a Delphi study. The study begins with an expert-led EWG to generate an initial list of competencies based …
An Analysis Of Supervisor Job Satisfaction During Telework In The Covid-19 Pandemic, Corey L. Rucker
An Analysis Of Supervisor Job Satisfaction During Telework In The Covid-19 Pandemic, Corey L. Rucker
Theses and Dissertations
The COVID-19 pandemic significantly reshaped workplace practices, accelerating the adoption of telework. This study examines the job satisfaction of supervisors in telework environments, focusing on qualitative analysis of survey responses from 41 supervisors in the Department of Defense (DoD). Through thematic analysis, the research identifies key factors influencing supervisor satisfaction. These themes include flexibility, communication challenges, resource gaps, and the unique stressors of managing remote teams. Findings reveal that while telework offers benefits such as improved work-life balance and productivity, it also presents challenges like reduced team cohesion, blurred work-home boundaries, and difficulties in performance management. Grounded in Herzberg’s Two-Factor …
Radiation Assessment And Distribution In Changing Atmospheric Structures And Turbulence (Radcast), Steven B. Hernandez
Radiation Assessment And Distribution In Changing Atmospheric Structures And Turbulence (Radcast), Steven B. Hernandez
Theses and Dissertations
The accessibility of materials and online information has made radiological dispersal devices (RDDs) a more probable threat than conventional nuclear weapons. This study analyzed five datasets from three test periods, using a correlation analysis between optical turbulence, aerosol concentration, and environmental parameters, and geometric mean diameter (GMD) calculations. The correlation analysis failed to yield meaningful insights, prompted a transition to the GMD analysis, which produced clearer results. Findings show GMD ranged from 38–41 nm, increasing at night and during neutral events as reduced vertical motion and boundary layer contraction correlated with optical turbulence. An alternative GMD dataset, calculated by the …
Characterization Of The Neutron Spectrum Produced By A Pulsed Power Generator, Daniel S. Godlasky
Characterization Of The Neutron Spectrum Produced By A Pulsed Power Generator, Daniel S. Godlasky
Theses and Dissertations
Neutron time-of-flight, activation foils, and spectral unfolding software were used to characterize the energy and fluence of the neutron spectrum created by the Gamble II pulsed power generator. Gamble II is a pulsed power generator that delivers a 1 MV to 2.2 MV and 800 kA electrical pulse peaking at 50 ns. This electrical release creates deuterium ions in the diode that are accelerated to a neutron converter covered with a novel lithium fluoride or deuterated polyethylene to create primarily 7Li(d,n) or D(d,n) and 12C(d,n) nuclear reactions. In October 2024, two D(d,n) shots occurred, and in November 2024, …
Numerical Studies Of Semiclassical Light Storage Using The Coherent Atomic Transfer Function, Zachary T. Johnson
Numerical Studies Of Semiclassical Light Storage Using The Coherent Atomic Transfer Function, Zachary T. Johnson
Theses and Dissertations
Quantum communication through photons relies on photonic storage to preserve quantum states. However, when photons interact with matter, quantum information becomes distorted. A recently developed semi-classical analytical model predicts output light pulses from an electromagnetically induced transparency (EIT) system. Using the predictions, the model known as the Coherent Atomic Transfer (CAT) Function, is capable of predicting the stored pulse or reconstructing the original pulse. Using numerical convolution and deconvolution with the CAT function as an analog of the point spread function of Fourier optics can provide insights on the effects of EIT storage on the retrieved pulse. Blind deconvolution is …