Digital Commons Network^™

Seabed Characterization Using Ambient Sound For A Range-Dependent Track In The New England Mud Patcha, Martin Siderius, Stan E. Dosso, Brian Granger

Electrical and Computer Engineering Faculty Publications and Presentations

Wind-generated, ocean ambient sound data were used to characterize seabed properties along a track in the New England Mud Patch. A 15-m vertical array, consisting of 16 hydrophones, collected ambient sound data across the 50–5000 Hz frequency band. The array drifted for 1 h, covering a 1.7 km track. Seabed characterization was performed using beamforming techniques, which limited the analysis to the 400–700 Hz band. Passive fathometer processing was applied to estimate the water–seabed interface and sub-bottom layering. Additionally, the data were used to estimate the power reflection coefficient, which was then used as input for a trans-dimensional geoacoustic inversion. …

Distribution Comparisons Of Eac Cost Growth For Aircraft Work Breakdown Structure Elements, Kyle P. Marquis, Edward D. White, Brandon M. Lucas, Robert D. Fass, Jonathan D. Ritschel, Shawn M. Valentine

Faculty Publications

This article analyzes and investigates the distribution of cost growth of the Estimate at Completion (EAC) for the Work Breakdown Structure (WBS) elements of approximately 60 historical United States Acquisition Category I Research, Development, Test and Evaluation aircraft programs. Using the method of maximum likelihood in conjunction with the Akaike Information Criterion, the authors suggest that both the lognormal and Weibull distributions provide relatively good fit to EAC cost growth, with the lognormal slightly edging out the Weibull. As a summarized finding, the authors present their empirical results for the mean, coefficient of variation (CV), the 15th and 85th percentiles …

Understanding Firn Dynamics: Modeling And Microstructure From East Antarctica, Ilyse Horlings

Dartmouth College Ph.D Dissertations

Glacier ice is formed from the accumulation of snow and its compaction through a transitional material called firn. Firn dynamics are fundamentally influenced by climatic factors, such as temperature and snow accumulation rate, and so are crucial for understanding a number of cryospheric applications. For example, ice-sheet mass loss contributions to sea-level rise from repeat satellite-altimetry observations depend on calculating firn density and its evolution. Past atmospheric gases in ice core bubbles are often younger than the surrounding ice, and their exact age depends on how firn closes off interconnected pores to become impermeable. Models often estimate bulk properties, such …

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

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 …

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 …

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. …

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 …

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 …

Deep Reinforcement Learning For Leo Satellite Grouping, James E. Minteer

Theses and Dissertations

This research investigates jamming evasion using DRL to provide an autonomous solution that repositions a geostationary satellite experiencing directed, terrestrial based jamming. Second, this thesis applies DRL to an area of research for LEO satellite constellations, user grouping, using a portion of an Air Force Research Lab reinforcement learning framework. As LEO satellites orbit the earth, they must constantly re-evaluate not only which users they are able to connect to, but on which of its multiple beams. This model succeeds in finding a balance between maximizing signal strength and minimizing overhead from switching user assignments, all while requiring fewer costly …

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene

Theses and Dissertations

Operational Energy (OE) education is vital for national security, military readiness, and fuel energy efficiency. This thesis analyzes the current landscape of OE education and identifies key gaps in awareness, energy knowledge, and curriculum structure. Through a reflexive thematic analysis of interviews with Subject Matter Experts (SMEs), the study underscores the necessity of integrating OE concepts into both educational and professional training programs. A framework is proposed to enhance OE education across various levels in the Air Force, aiming to cultivate a more energy-conscious and strategically prepared force. The findings highlight the critical need for targeted training, curriculum enhancements, and …

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 …

Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock

Theses and Dissertations

In conjunction with the Air Force Research Laboratory Materials Lab(AFRL-RX), this study evaluates the potential military value of the prototype material sensing composites on Unmanned Aerial Vehicle (UAV) operations in intelligence, surveillance, reconnaissance (ISR), and close air support (CAS) missions within a contested Indo-Pacific theater. Using a Simio based simulation,UAV performance was assessed under varying combat conditions, focusing on Remote Sensing, deployment strategies, initial lay-downs, and varying loss rates. Re-sults show that UAVs equipped with Remote Sensing technology significantly improved sortie generation and logistical efficiency. Scenario 17 achieved the highest sortie rate(965.5 sorties), outperforming the next-best scenario by 25 sorties. …

Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam

Theses and Dissertations

Since the introduction of the first unmanned aerial vehicle (UAV), UAVs have consistently improved in capability and versatility. The ability to perform military operations without the risk of losing human life is crucial for the United States military. The trade-off for this versatility is cost, and several ongoing research efforts are being made to improve UAV mission success and the lifespan of UAVs. An area of research that falls under the categories mentioned is self-damage detection. The Air Force Research Laboratories (AFRL) are developing a capability to enable a UAV to assess airframe damage, enabling real-time determination of damage potentially …

Improving Zero Shot Learning By Linking Multi-Label Cnns With Llms, Michael A. Wegner

Theses and Dissertations

Classifying previously unseen objects poses a significant challenge for traditional computer vision algorithms, which rely on extensive labeled training data. Zero-shot reasoning offers a way to overcome this limitation. This research explores a novel method for image recognition using the Animals with Attributes 2 (AWA2) dataset as a proof of concept. A multi-label ResNet50 model predicts core attributes like color, ear shape, or number of limbs. Those attributes then feed into ChatGPT which leverages its extensive knowledge base to classify the animal based on the provided attributes. This novel approach skips the need to train on every possible class. Instead, …

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 …

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

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, …

An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow

Theses and Dissertations

This paper is concerned with a co-planar pursuit-evasion scenario where two Pursuers (P) are after an Evader (E). The players are holonomic/can turn on a dime and their speeds, V_P and V_E, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ =  V_E/V_P > 1. The Pursuers are endowed with a circular capture disc whose radius l > 0. A differential game (DG) with three states and one parameter is addressed through geometric and analytical methods where a partial solution is outlined and visualized. The game is split …

Blast Tube Design: How Shape And Size Influence The Resultant Shock Wave, R. L. Bauer, C. E. Johnson

Mining Engineering Faculty Research & Creative Works

Shock tubes and tunnels are often used in research settings as a way of producing high pressure shock waves in a smaller footprint or without the use of explosives. However, there is no standard geometric design across laboratories. Peak pressure is a significant parameter for characterizing a shock wave. However, different tube configurations could also affect parameters such as impulse and duration, yet no research has investigated how the scale of the tube affects the overall waveform shape. To understand the implications of shock tube design, tubes with a constant length to diameter ratio were evaluated to determine how tube …

Characterization And Modeling Of Polyphase Machines And Power Conditioning Components, Nathan Lockhart

Electrical Engineering Dissertations - Archive

Microgrid power configurations have become increasingly prevalent in recent power systems due to the rise of power electronic energy generation, energy storage, and the many diverse electrical demands. Microgrids offer numerous advantages over traditional power electronic networks, which rely on large rotating generators to supply power over extensive distances to multiple users. Remote power grids are particularly beneficial for smaller networks that may be isolated or have unique power requirements, often incorporating energy storage to enhance operational flexibility. Advances in power electronics, such as medium voltage DC distribution, are enhancing the reliability, redundancy, and integration capabilities of isolated microgrids.

To …

Multi-Agent Differential Games Under An Altruistic Equilibrium, Craig Alan Lovell

Mechanical and Aerospace Engineering Theses - Archive

This work studies a multi-agent differential game with linear dynamics under the Berge equilibrium. The governing coupled differential equations for a two-agent and a three-agent game under the Berge equilibrium are derived. These games are simulated and compared to the Nash equilibrium. A sensitivity study is performed which validates that, under some criteria, the Nash equilibrium can be recovered from the Berge equilibrium. Policy fusion between the Berge and Nash equilibrium is explored in a two-agent game. A five-agent game under the Berge equilibrium is simulated and multiple teams of agents in this game are evaluated. Finally, a mixed game, …

Power Quality Event Diagnosis Using Multi-Rate Neural Networks, Jordan D. Lloyd

Electrical Engineering Theses - Archive

Power quality disturbances (PQDs) are among the primary challenges facing modern electrical systems, as they degrade the performance and lifespan of connected equipment. This thesis investigates the relationship between the rate at which voltage waveform data are sampled, the reliability of these measurements, and the ability of deep neural networks to classify PQDs accurately. A one-dimensional convolutional neural network (CNN) was trained and evaluated across multiple sampling rates and signal-to-noise ratios to quantify how information loss in the temporal and spectral domains affects classification reliability. The results demonstrate that model accuracy degrades nonlinearly as sampling rate and signal-to-noise ratio (SNR) …

Detection Of Data Leakage And Disruption Of Covert Timing Channel In Secure Drone Communication Using Machine And Deep Learning, Jonathan Walatkiewicz

Master's Theses and Doctoral Dissertations

The utilization of recreational drones has experienced a substantial increase in both the United States and globally. However, it is noteworthy that most drones, classified as Internet of Things devices, are produced with a limited security lifecycle. This study's findings are of paramount importance, as traditional computing exploits can be applied to drones, designating them as high- value targets. This study examines the detectability and disruptability of covert timing channel traffic in secure drones. The investigation aims to ascertain the effects of multiple interarrival times, distances ranging from 1 to 330 feet, various detection algorithms, and stream sizes between 32-bit …

Load Analysis And Material Optimization For An Underwater Autonomy Sensorized Task Platform, Andrew Vo

Engineering Theses

With developing technology, options for fabrication and material selection broaden. An example is 3D printable photopolymer resin used to create parts serving several applications. An application of this photopolymer resin is the ONR research project for the creation of the sensorized task platform for a robot to use underwater. The resin in this project was used to fabricate custom-made connecting brackets. These fabricated parts were hastily designed with no detailed analysis on stress distributions or material consumption. Using SolidWorks simulation analysis and Instron machines for experimentation, the goal of this project was to modify the original part with a reduced …

Lidar From The Skies: A Uav-Based Approach For Efficient Object Detection And Tracking, Baya Cherif

Masters Theses

"Recently, there has been a growing interest in deploying the Light Detection and Ranging (LiDAR) technology to gain traction in the autonomous vehicle industry, its applications are expanding into areas like smart cities, agriculture, and renewable energy. This work proposes an advanced approach to enhance aerial traffic monitoring using Li- DAR. We aim to provide accurate, real-time object detection and tracking from an aerial perspective by integrating Unmanned Aerial Vehicle (UAV) with LiDAR, culminating in a smart UAV-integrated LiDAR (A-LiD) sensor for traffic surveillance. We introduce an adapted version of one of the newest methods of the cutting-edge 3D object …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Anti-Jamming Attack Mixed Strategy For Formation Tracking Control Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Yongbao Wu, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Communication plays a role in multi-UAV to perform formation tracking missions. In complex environments, UAV communication is often subject to jamming attacks, affecting the formation process. Therefore, studying the formation tracking control problem in jamming attacks is of great significance. Typically, the actions of the UAV consist of two fundamental modules: mobility strategy and communication strategy. In this paper, we design an anti-jamming attack mixed strategy for formation tracking control of the multi-UAV system. In practical scenarios, multi-UAV systems not only require the accomplishment of formation maneuvers but also necessitate effective mitigation of jamming attacks caused by other UAVs. Therefore, …

ต้นแบบระบบตรวจจับ คัดแยก และป้องกันภัยจากอากาศยานไร้คนขับขนาดเล็ก, รักษ์ตะวัน พูลสุวรรณ

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้ได้นำเสนอการออกแบบและความเป็นไปได้ของระบบกระบวนการหลายขั้นตอนแบบครบวงจรสำหรับการตอบโต้โดรน (UAV) โดยใช้แพลตฟอร์ม Software-Defined Radio (SDR) ในกระบวนการแรก การตรวจจับใช้วิดีโอเรดาร์แบบคลื่นต่อเนื่องปรับความถี่ (FMCW) ที่มีความถี่พาหะ 2.4GHz สำหรับการตรวจจับและติดตามเป้าหมายทางอากาศ ระบบย่อยนี้ได้รับการออกแบบมาเพื่อระบุระยะทางและความเร็วของวัตถุที่เข้ามา ขั้นตอนที่สองเกี่ยวข้องกับการจำแนกสัญญาณคลื่นความถี่วิทยุ (RF) โดยใช้โครงข่ายประสาทเทียมแบบคอนโวลูชัน (CNN) เพื่อวิเคราะห์สัญญาณควบคุมและการถ่ายโอนข้อมูลที่ส่งระหว่างโดรนและผู้ควบคุมภายในย่านความถี่ ISM (2.4GHz) ขั้นตอนสุดท้ายคือการทำให้ภัยคุกคามที่ได้รับการยืนยันเป็นกลางโดยใช้เทคนิคการตอบโต้ทางอิเล็กทรอนิกส์สองวิธี วิธีแรกคือการปล่อยสัญญาณรบกวนเพื่อขัดขวางการเชื่อมโยงคำสั่งและการควบคุมในย่านความถี่ ISM (2.4GHz) เพื่อแยกโดรนออกจากผู้ควบคุมได้อย่างมีประสิทธิภาพ ในขณะเดียวกัน ระบบจะทำการหลอก GPS ภายในย่านความถี่ L1 โดยการส่งสัญญาณ GPS L1 จำลองในย่านความถี่ 1.575GHz เพื่อทำให้ตำแหน่งของโดรนสับสน ระบบนี้ได้ทดสอบกับโดรน DJI Mini 4K ที่มีพื้นที่หน้าตัดเรดาร์ 0.01 ตารางเมตร โดยมีผลลัพธ์คือระยะการตรวจจับ 20 เมตร และระยะการรบกวนและการหลอก GPS ที่ 50 เมตร ภายใต้ข้อจำกัดกำลังส่งที่ 20 dB ตามข้อจำกัดของย่านความถี่ ISM