UTILIZING A FACTION DISPOSITION PARTICLE FILTER (FDPF) FOR TRACKING OPPOSING FORCES (OPFOR) ENTITY POSITIONS IN LAND-BASED MILITARY SIMULATIONS WITH PARTIAL OBSERVABILITY

This thesis investigates how a Faction Disposition Particle Filter can be effectively designed to estimate the positions of opposing force (OPFOR) entities under conditions of fog of war on land-based military simulations with partial observability. Inspired by military planning procedures, the proposed method models entire faction-level enemy courses of action (COAs) as individual particles. Unlike conventional approaches that estimate unit positions independently, each particle represents the coordinated behavior of all OPFOR units, capturing their collective intent and operational coherence. This enables the decision-making AI to reason over complete enemy dispositions rather than fragmented unit data. The implemented prototype consists of three core components: a set of Particle AIs encoding plausible OPFOR COAs, a Likelihood Estimator assessing their consistency with current observations, and a decision-making AI that selects actions based on the weighted particle states. Evaluated across a range of scenarios, the approach demonstrated improved estimation and adaptive planning under uncertainty. The modular design, observed limitations, and identified trade-offs offer a foundation for future enhancements, including dynamic particle management, improved likelihood modeling, and predictive planning.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, German Arm

NEARSHORE BATHYMETRIC MAPPING USING DRONE-ACQUIRED VISUAL WAVETOP IMAGERY

Nearshore bathymetric mapping is critical for naval operations, coastal management, and oceanographic modeling. However, traditional acoustic survey methods are costly, time-consuming, and dangerous in surf zones. This study investigates the use of unmanned aerial systems (UASs) to derive bathymetry from visual wavetop imagery at the morphologically dynamic Pajaro River mouth in Monterey Bay, California. Data was collected during closed (2021) and open (2025) river mouth conditions. This study uses the open source cBathy and cBathyCT toolboxes to output bathymetry. Imagery was processed to identify wave characteristics so that the wave dispersion relationship could be used to calculate depth. cBathyCT provided improved fidelity on wave crest identification using a machine learning algorithm and a nonlinear wave theory correction for surfzone depth estimation. Results were consistent with expected depth overestimation within the surfzone for cBathy when compared to cBathyCT results. The technique successfully identified complex bathymetric features including a trough seaward of the river mouth, validated through consistent wave breaking patterns. This methodology provides a foundation for future research in bathymetry derived from drone-acquired wavetop visual imagery.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav

PERSONALITY AND CHARACTER TRAITS IN NAVAL ACADEMY LEADERSHIP

This capstone investigates the personality traits and character values associated with leadership selection at the United States Naval Academy (USNA). Framed within the Academy’s role as a “leadership laboratory,” the study explores whether the traits most commonly observed among Brigade leaders reflect an intentional leadership model—or if they may signal an implicit preference for certain profiles. Using data from standardized assessments administered during plebe year, including the IPIP-NEO and VIA Character Strengths Survey, the analysis highlights notable patterns among those chosen for leadership roles. The findings raise important questions about the qualities USNA implicitly rewards and how those signals might shape leadership development, selection, and diversity of thought within the Brigade.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisLieutenant, United States NavySenior Chief Petty Officer, United States NavyLieutenant, United States Nav

POWER GENERATION SOLUTIONS FOR THE GREEN ENERGY SHIP

The green energy ship project has been proposed as a potential solution to the current energy problems. This thesis focuses on the design of a power generation plant that turns wind energy into electricity and sits in the heart of the vessel. This paper discusses the concepts that have been proposed in the green energy ship and identifies how they can be practically implemented in a real world design that may be used to close the gap in energy demand and clean energy production. In addition, this thesis provides an overview of the hydrodynamics, performance characteristics, and control and automation requirements of an unmanned sailing vessel, as well as the electrical and mechanical components that would work in the 12 Metre Class sailboat identified as potential testbed. Finally, this paper proposes an algorithm for rectifier control that will act to regulate power flow in the system.Distribution Statement A. Approved for public release: Distribution is unlimited.Commander, United States Nav

STRENGTHENING MEDICAL AND PUBLIC HEALTH INTELLIGENCE AT THE LOCAL AND REGIONAL LEVELS

The integration and collective interpretation of medical intelligence (MEDINT) are critical for an effective emergency response to public health crises. Examining established collaborative systems, the collective analysis of MEDINT, and forecasting, this thesis presents case studies of Israel’s intelligence community and the Association of Bay Area Health Officers (ABAHO) in responding to the COVID-19 pandemic to investigate how public health and intelligence communities at local and regional levels can strengthen the collective interpretation of MEDINT. As demonstrated by Israel and ABAHO, by integrating medical and public health intelligence into collaborative systems through multi-agency coordination or fusion centers, thereby integrating expertise across agencies, emergency responders can enhance situational awareness, improve resource allocation, and respond proactively to emerging threats. Thus, policymakers and emergency response agencies should prioritize the development of collaborative systems, cross-sector training, and the integration of MEDINT into fusion centers to enhance public health and safety management at all levels. This thesis recommends formalizing processes to collectively interpret MEDINT at local and regional levels to enhance operational readiness, contributing to more effective emergency management strategies.Distribution Statement A. Approved for public release: Distribution is unlimited.Civilian, San Mateo Count

PREPARED OR PRECARIOUS? U.S. GOVERNMENT READINESS IN THE FACE OF BIOLOGICAL TERRORISM

The threat of biological terrorism is constantly evolving, and concerns about biological threats were heightened by the 2020 COVID-19 pandemic. This thesis argues that while U.S. biodefense strategies and policies have significantly improved since the Bush administration, vital gaps remain and the U.S. government is unprepared to defend against future attacks. Through an analysis of three case studies, the 1984 Rajneeshee Salmonella attacks, the 1995 Aum Shinrikyo attacks, and the 2001 Anthrax attacks, this thesis identifies shortcomings in past biodefense strategies and highlights ongoing weaknesses in interagency coordination and partnerships, education and training, and investment in biodefense. The research further examines the biodefense strategies of post-9/11 presidential administrations, analyzes current biodefense readiness and response capabilities, and reviews the challenges and limitations that U.S. biodefense strategies face. This thesis also discusses the potential effect the COVID-19 pandemic may have on the biothreat landscape. The findings indicate that the lessons from past incidents remain relevant today and can inform efforts to close existing gaps in the nation’s biodefense. This thesis concludes with proposals for future research aimed at enhancing national preparedness and improving strategies to prevent, detect, and respond to future biothreats.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav

EXPERIMENTAL ACCURACY OF NILM LOAD DISAGGREGATION ON THREE-PHASE MICROGRID TEST BED

Non-intrusive load monitoring (NILM) is a powerful tool that uses machine learning and special sensors to disaggregate large amounts of electrical data from a single central point of a power system. This service provides valuable insight into the system, allowing for anomaly detection and improvements to preventative maintenance. An important aspect of NILM is the accuracy of the sensors collecting the power data. The United States Navy is currently experimenting with the Mobile Power Meter (MPM), a load monitoring sensor that is proprietary to the Army Research Lab (ARL). These sensors are still being tested, optimized, and improved with every iteration. MPMs have not yet been validated for widespread use. In this thesis, we test the accuracy of MPM data collection and load disaggregation when applied to a three-phase microgrid testbed. The MPMs are run through tests with various loads and then meticulously compared to the ground truth data, which is obtained from oscilloscope probes attached at every phase of every load. Various power features, such as the frequency, voltage, and phase currents, are then selected for analysis. Based on percent error calculations and visual analysis, the MPM data is compared against the oscilloscopes for accuracy. Validating the accuracy of the MPMs is a significant step in ensuring NILM is precisely executed, thereby bolstering the energy security of the United States Navy.Distribution Statement A. Approved for public release: Distribution is unlimited.Ensign, United States Nav

DEVELOPMENT AND DIGITALIZATION OF EDUCATIONAL WARGAME “RACE FOR THE ARCTIC”

This capstone aims to develop and optimize the award-winning educational wargame “The Race for the Arctic” by Howell and Leisinger, published in 2023. The conceptual approach has been to add further realism and learning objectives to the game without sacrificing its entertainment value. The capstone work consisted of extensive playtesting (board game and digital), field studies, consultations with subject matter experts in various Arctic disciplines, and literature research. Major findings include a redesign around the Svalbard Archipelago and Chinese activities in the Arctic, modeling fisheries as a separate resource, and a redesign of the game’s victory conditions. Minor suggested implementations include various enhancements to improve game mechanics and the overall game experience. Many of the recommended implementations offer scalable options, and future game development must adopt a holistic approach when determining which elements to include in future versions.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, Norwegian Arm

Faces of NPS: Ens. Olivia "Ollie" Shapiro, USN

Faces of NPS features interviews spotlighting the students, faculty, staff and alumni of our Nation's premier defense education and research institution