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Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus Mar 2025

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 …

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Evaluating Educational Benefits Of A Custom Cyber Game: ‘Hvac Attack!’, Jillian S. Valente Mar 2025

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.

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Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler Mar 2025

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 …

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Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case Mar 2025

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 …

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A Machine Learning/Deep Learning Investigation On Remote Manufacturing Machine State Classification, Ajeet S. Parmar Mar 2025

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, …

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Uranium Particle Classification Using Statistical Machine Learning And Deep Neural Networks For Nuclear Forensics, Lee C. Lambert Mar 2025

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 …

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Cognitive Warfare In The South China Sea: Analyzing Media Influence And Public Opinion In Taiwan, Wyatt F. Blatti Mar 2025

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.

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Assessing The Feasibility Of Managed Aquifer Recharge For The United States Air Force, Daniel Hendrix Mar 2025

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 …

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Cloud One Migration Duration And Its Drivers, Grayson T. Hall Mar 2025

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. …

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Isotopic Analysis Of Lithium Hydroxide Monohydrate Using Laser-Induced Breakdown Self-Reversal Isotopic Spectrometry (Libris) And Machine Learning, Madison R. Moran Mar 2025

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 …

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Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking, Liam A. Weinfurtner Mar 2025

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.

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Design And Evaluation Of A Deployment Mechanism For A Space-Based Origami Mirror In Cubesat Missions, Arturo Luna Mar 2025

Design And Evaluation Of A Deployment Mechanism For A Space-Based Origami Mirror In Cubesat Missions, Arturo Luna

Theses and Dissertations

The space environment’s suboptimal lighting conditions and eclipse periods impede inspection and on-orbit servicing missions. To abate this problem, the Air Force Institute of Technology (AFIT) launched the Mirror Illumination for Reconnaissance and Rendezvous of Orbital Resident Systems (MIRRORS) initiative. This initiative provides augmented illumination to resident space objects (RSOs) by reflecting the sun’s rays from a mirror satellite. Leveraging origami-inspired designs for compact packaging, AFIT developed a cube origami flasher mirror constructed from aluminum panels that unfolds passively via Nitinol hinges. This research investigates the necessary deployment and panning mechanisms for a dynamic, space-based origami mirror to advance the …

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(Si14-02) Analysis Of Cross Diffusion Effects On Mhd Nanofluid Past An Oscillating Plate With Ramped Wall Temperature, Gopal Nanda, Harshad Patel Mar 2025

(Si14-02) Analysis Of Cross Diffusion Effects On Mhd Nanofluid Past An Oscillating Plate With Ramped Wall Temperature, Gopal Nanda, Harshad Patel

Applications and Applied Mathematics: An International Journal (AAM)

The primary objective of this research is to analyze the influence of cross-diffusion on the behavior of nanofluid flow, which is governed by unsteady hydrodynamics in the existence of a magnetic field. Additionally, this study considers the effects of thermal radiation and heat production. The flow occurs within a porous medium, passing through a vertically oscillating plate. The investigation focuses on two distinct nanofluid formulations, namely silver and titanium dioxide. The concept of similarity transformation is applied to simplify the governing system from partial differential equations (PDEs) to ordinary differential equations (ODEs). To obtain precise expressions for the concentration, temperature, …

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Engaging Early Childhood Students Using Clothesline Math, Stacy K. Boote, Terrie Galanti, Danielle Felicien, Tara Kelly Mar 2025

Engaging Early Childhood Students Using Clothesline Math, Stacy K. Boote, Terrie Galanti, Danielle Felicien, Tara Kelly

UNF Faculty Research and Scholarship

Strengthen young learners’ agency and accountability by problematizing number sense, place value, and multiplication concepts using a Clothesline Math routine.

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Clay Minerals Origin And Paleoclimate Implications In Quaternary Deposits Of The Saïs Plain, Fez-Morocco, Ayman Agharabi, L. Karrat, Frank R. Ettensohn, N. Har, L. Gourari, H. Bedelean, C. Balica, C. V. Mircescu Mar 2025

Clay Minerals Origin And Paleoclimate Implications In Quaternary Deposits Of The Saïs Plain, Fez-Morocco, Ayman Agharabi, L. Karrat, Frank R. Ettensohn, N. Har, L. Gourari, H. Bedelean, C. Balica, C. V. Mircescu

Earth and Environmental Sciences Faculty Publications

The city of Fez in northern Morocco is situated on northeastern parts of the Saïs Plain, an alluvial basin. It is spreading southwesterly onto Pleistocene sediments consisting primarily of alluvial, channel-fill conglomerates and overbank deposits, as well as Holocene tufas. As urban develop- ment expands, human activities are increasingly eradicating these deposits, about which little is known. This study focuses on the clay-mineral composition of these Pleistocene overbank de- posits, informally known as the “Red” and “Yellow” units, as well as of the Holocene tufas. In contrast to previous research that has emphasized the industrial uses of nearby Miocene marls. …

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A Comparison Of The Factors That Affect Graduation Rates Of Students Enrolled In Dropout Prevention Programs, Catina R. Thomason Mar 2025

A Comparison Of The Factors That Affect Graduation Rates Of Students Enrolled In Dropout Prevention Programs, Catina R. Thomason

Dissertations

The purpose of this study was to compare the factors that affected the graduation rates of students enrolled in five charter high school dropout prevention programs that utilized the same online accelerated curriculum model. The overarching research question was: what factors affected the graduation rates of students enrolled in dropout prevention programs? A mixed methods design was employed to evaluate extant data on graduation rates and attendance rates surveys and semistructured interviews were completed by administrators and teachers to compare data across the five schools. This approach allowed for a comprehensive analysis of both quantitative and qualitative data, providing a …

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Plural Water Narratives: An Environmental Justice Lens On A Systematic Review Of Q-Methodology Water Research, Melissa Haeffner, Alida Cantor, Janet Cowal, Andrea Bryant, Darius Mani Yaw, Kinna Je Palacios, Daniela Serna, Bryce Sprauer, Abigail Tran-Gruver Mar 2025

Plural Water Narratives: An Environmental Justice Lens On A Systematic Review Of Q-Methodology Water Research, Melissa Haeffner, Alida Cantor, Janet Cowal, Andrea Bryant, Darius Mani Yaw, Kinna Je Palacios, Daniela Serna, Bryce Sprauer, Abigail Tran-Gruver

Environmental Science and Management Faculty Publications and Presentations

Environmental justice research has shown that people's experiences and perceptions of water differ because systematic inequalities shape the extent to which people access clean water and are exposed to water hazards. Q‐methodology is one technique that has been used to aggregate multifaceted subjective narratives and understand different perspectives on a topic. In this paper, we systematically review 77 case study articles applying Q‐methodology to water‐related topics, to inventory how people perceive their relationships with water. We create a classification system based on environmental justice theory to examine (1) distributive justice issues around alternative water sources and agricultural and urban water …

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Quantum Finite Automaton Using Ternary Rotation Quantum Gates And Chrestenson Family Quantum Gates, Yuchen Huang, Marek Perkowski, Xiaoyu Song, John M. Acken Mar 2025

Quantum Finite Automaton Using Ternary Rotation Quantum Gates And Chrestenson Family Quantum Gates, Yuchen Huang, Marek Perkowski, Xiaoyu Song, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Quantum automata can solve certain problems with a smaller state space than classical automata. We developed a quantum finite automaton using ternary rotation quantum gates and the Chrestenson family of ternary quantum gates. The main idea of this paper is to show how to combine rotation ternary quantum circuit-based QuantumFinite Automaton and quantum reversible circuit-based Deterministic Finite Automaton to build a more powerful machine. The combined machine can enable more complex language and pattern recognition. The developed quantum finite automaton and resulting combined machine can be used for robotics applications such as language, gesture, and motion recognition.

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Investigation Of Neutron Inelastic Scatter Cross Sections On 16O, Molly A. Wakeling Mar 2025

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, …

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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 Mar 2025

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 …

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Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst Mar 2025

Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst

Theses and Dissertations

This research optimizes the number, placement, and capacity of Military Entrance Processing Stations (MEPS) to minimize applicant and recruiter travel and improve recruitment efficiency. Using mixed-integer programming, it develops capacitated facility location (CFLP) and maximal covering location (MCLP) models, considering facility capacity, budget, and geographic coverage. Computational testing and scenario evaluations highlight opportunities to reduce travel and balance capacity. For example, the CFLP model adds three new MEPS, reducing annual applicant travel by 1.2 million miles in Florida and Texas and 1.0 million in California, while increasing accessibility within 60 miles of a MEPS. This data-driven approach provides USMEPCOM with …

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Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp Mar 2025

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 …

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Forecasting Army Recruiting Mission Distribution, Maxwell A. Deihl Mar 2025

Forecasting Army Recruiting Mission Distribution, Maxwell A. Deihl

Theses and Dissertations

The Army’s recruiting landscape has changed markedly in recent years, raising questions about whether forecasting methods of Army contracts remain robust. This thesis recreates the presented models in Joshua McDonald’s 2015 thesis. It replicates and evaluates the models with updated data (2018–2023) to assess their current validity and compare them to novel alternative approaches, such as simpler regression models or neural networks. While the 2015 model remains a valuable baseline, results suggest that either refining its variables or adopting alternative methods can improve predictive accuracy and interpretability. Ultimately, the United States Army Recruiting Command has many options regarding how it …

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Advancing Defense Software Cost Estimation Through Regression, Probabilistic, And Machine Learning Models, Stephen D. Chatterton Mar 2025

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 …

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The Location Set Covering Disruption Problem, Richard A. Sheldon Mar 2025

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 …

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Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii Mar 2025

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.

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Evaluating A Military Digital Badging System Prototype, Benjamin T. Pederson Mar 2025

Evaluating A Military Digital Badging System Prototype, Benjamin T. Pederson

Theses and Dissertations

The Department of Defense is committed to developing and maintaining a highly skilled workforce capable of defending the United States and associated interests abroad. Digital badging systems, a form of micro-credentialing, offer a way to record service member competencies. By providing decision-makers with granular data, this technology could augment the military’s development of a highly skilled workforce, especially in technical career fields including cyber operations. Mixed-method data from thirty-six participants suggest that establishing a digital badging program could increase deterrence and operational effectiveness.

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Calibration And Demonstration Of A Dropped Channel Polarimetric Compressive Sensing Radar System, Cameron G. Goodbar Mar 2025

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 …

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Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones Mar 2025

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.

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Tracking News Narratives: Topic Modeling, Sentiment, And Media Coverage Patterns, Alexandria G. Lai Mar 2025

Tracking News Narratives: Topic Modeling, Sentiment, And Media Coverage Patterns, Alexandria G. Lai

Theses and Dissertations

This study introduces a novel content-driven influence measurement framework, built around a custom influence formula that integrates Non-negative Matrix Factorization (NMF) topic modeling, sentiment analysis, and influence metrics to analyze media narratives over time. Applied to news coverage of the 2020 U.S. presidential election and the COVID-19 pandemic, the framework identifies key topics, sentiment patterns, and influential sources. Results demonstrate its ability to distinguish between transient political controversies and sustained public health discourse while capturing shifts in media influence. While effective, refinements in topic separation, sentiment analysis, and temporal weighting could enhance adaptability. This study highlights the novel influence formula …

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