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Articles 5851 - 5880 of 8614
Full-Text Articles in Engineering
Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones
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.
A Multi-Objective Reinforcement Learning Framework For Title Autonomous On-Orbit Inspections, Austin C. Reynolds
A Multi-Objective Reinforcement Learning Framework For Title Autonomous On-Orbit Inspections, Austin C. Reynolds
Theses and Dissertations
The rapidly evolving landscape of space operations necessitates dynamic and autonomous systems to address complex challenges such as Resident Space Object (RSO) inspections. This research explores the application of a Multi-Objective Reinforcement Learning (MORL) framework to rendezvous and proximity operations (RPO), enabling agents to balance conflicting objectives like time efficiency, fuel conservation, and information gain. Unlike traditional reinforcement learning, MORL allows dynamic reweighting of objectives without retraining, offering adaptability and efficiency in multi-objective environments. The study demonstrates MORL's capabilities through custom 2D and 3D simulations of Hill-Clohessy-Wiltshire (HCW) environments and comparing its performance to traditional RL in RPO scenarios. Tasks …
Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson
Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson
Theses and Dissertations
Unmanned Aerial Vehicles (UAVs) have seen increased usage over the past two decades during the Global War on Terrorism (GWOT), operating in low-risk environments against dispersed enemies with minimal counter-drone capabilities. However, as the U.S. military shifts focus to Multi-Domain Operations (MDO) and Large Scale Combat Operations (LSCO), UAVs face significantly higher risks, including frequent and successful attacks, as well as the exploitation of their technology. Battle damage assessment (BDA) is not new; however, autonomous self-assessment by UAVs represents a novel advancement. Currently, UAV BDA relies on manual inspection, requiring approximately eight hours per drone. By adopting self-sensing technology, UAVs …
How Does An Air Force Instructor Analyze Officer Occupational Competencies And Translate Them Into Professional Development Courses?, Julia A. Howard
How Does An Air Force Instructor Analyze Officer Occupational Competencies And Translate Them Into Professional Development Courses?, Julia A. Howard
Theses and Dissertations
This thesis examines how Air Force instructors translate officer occupational competencies into professional development courses. The study aims to address a pressing need to align Civil Engineer education with the Department of the Air Force objective of competency based education in the midst of changing operational demands. The methodology uses expert elicitation, thematic analysis, qualitative and quantitative statistics to formulate a curriculum development methodology. Data collection involved an expert elicitation from subject matter experts in the Civil Engineer career field. This data helped to pair 32E competencies with course learning objectives. The expert opinions provided insight into where civil engineering …
Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler
Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler
Theses and Dissertations
Per- and polyfluoroalkyl substances (PFAS), widely referred to as “forever chemicals,” exhibit high environmental persistence and potential health risks due to their robust carbon-fluorine bonds. These substances are prevalent in aqueous film-forming foams (AFFF), used in industrial and military applications, and are known to contaminate environmental surfaces, including concrete. This study aims to characterize the molecular-level interaction energies of six PFAS species—PFOA, PFOS, PFHxS, PFHxA, 6:2 FTS, and PFBS—with calcium silicate, a key component of concrete, using density functional theory (DFT) calculations. Change in Gibbs free energy (ΔG) was determined for each of the interactions, revealing negative ΔG values for …
On The Exploration Of Crystallographic Anisotropy And Defects In Shock Loading Using Molecular Dynamics, Benjamin P. Helman
On The Exploration Of Crystallographic Anisotropy And Defects In Shock Loading Using Molecular Dynamics, Benjamin P. Helman
Theses and Dissertations
The impact of crystallographic orientation, grain boundaries, and vacancies on the shock behavior of aluminum was investigated using molecular dynamics simulations. Shock loading in the [001], [011], and [111] directions was explored, revealing anisotropic behavior in shock speed, melting, dislocation density, and unique phase changes. The Hugoniot elastic limit in the [100], [110], and [111] directions was calculated as 23.2 GPa, 24 GPa, and 18.4 GPa respectively. These results were found to be an order of magnitude larger than the compressive yield strength computed at equilibrium. Additionally, metastable melting in the [011] and [111] directions occurred roughly 1000 K below …
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
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. …
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Theses and Dissertations
This research develops a digital twin of the global maritime shipping system to model disruptions in major shipping lanes like the Suez and Panama Canals. By incorporating live ship-tracking data, the model simulates closures, forecasts queue lengths, and determines the best rerouting options. Findings show that canal closures cause large traffic backlogs and increased congestion at alternative chokepoints, while rerouted ships may face higher piracy risks in regions like the Gulf of Guinea and the Strait of Malacca. This tool helps decision-makers respond effectively to maritime disruptions.
Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam
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
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, …
Analysis Of An Army Recruiter Allocation Model (Ram), Erik J. Wittendorf
Analysis Of An Army Recruiter Allocation Model (Ram), Erik J. Wittendorf
Theses and Dissertations
The United States Army Recruiting Command’s mission to recruit America’s best and brightest volunteers that can deploy, fight, and win requires an effective distribution of its recruiting force to serve as local community ambassadors. This research analyzes an Army recruiter allocation model (RAM) and assesses its underlying assumptions, objective function, and constraints. A detailed study of relative market potential and production rates for up to 1,319 Army recruiting stations and 18,789 ZIP codes enables RAM modification recommendations leveraging evolving recruiting concepts and identifies areas of future work to continue improving the Army’s understanding of the recruiting environment.
An Analysis Of Development Phase Nre/Rec Costs In Dod Acquisition Efforts, Jason Aristizabal
An Analysis Of Development Phase Nre/Rec Costs In Dod Acquisition Efforts, Jason Aristizabal
Theses and Dissertations
Estimating Nonrecurring Engineering (NRE) and Recurring Engineering (REC) costs in defense acquisition programs remains challenging, especially in development. While production costs are studied, NRE/REC ratios in development receive little attention. This study analyzes NRE/REC ratios across WBS elements, commodity types, and time periods using defense program data. Results show significant variability, challenging the assumed 1:1 ratio. System Level, PME, and ST&E elements follow distinct trends, highlighting shifting cost structures. These findings stress the need for adaptive methodologies, enabling cost analysts to refine estimates based on historical trends and program-specific factors for improved resource planning.
Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Theses and Dissertations
The Department of Defense (DoD) faces significant challenges in maintaining mission-critical infrastructure within highly corrosive environments, with annual costs exceeding $22.5 billion to combat corrosion. This thesis investigated the interplay between environmental severity, sustainment funding, and infrastructure performance. This research utilized Facility Sustainment, Restoration, and Modernization (FSRM) funding data, statistical analyses, and regression modeling, to evaluate how Environmental Severity Index (ESI) categories influence Base Condition Index (BCI) trends and the efficacy of the Facility Sustainment Model (FSM). The analysis revealed that installations in higher ESI categories required significantly greater investment per square foot to achieve comparable improvements in BCI. The …
Development Of An Advanced 16-Channel High-Fidelity Multi-Frequency Software-Defined Rf Front-End For Advanced Satnav Signal Monitoring Applications, Melbourne T. Ketteridge
Development Of An Advanced 16-Channel High-Fidelity Multi-Frequency Software-Defined Rf Front-End For Advanced Satnav Signal Monitoring Applications, Melbourne T. Ketteridge
Theses and Dissertations
Multi-element antenna array technology provides significant performance advantages in satellite timing and navigation (satnav) receiver applications. It is the most effective anti-jamming method with the ability to place steep nulls in the direction of jammers. Until recently, satnav systems with 4 or more antenna elements were designated as weapons technology and restricted under ITAR regulations. This opens the door to commercial multi-element satnav receivers. Due to advancements in wireless broadband technology a receiver built entirely using commercial off-the-shelf (COTS) components is possible. This thesis presents an architecture for a high fidelity 16-channel RF front-end (RFFE) for research and development of …
Discovering Design Requirements For Next Generation Arctic Tension Fabric Shelters, Mark W. Mcveigh
Discovering Design Requirements For Next Generation Arctic Tension Fabric Shelters, Mark W. Mcveigh
Theses and Dissertations
Military operations to remote Arctic regions require large-span temporary shelters to house tactical aircraft and provide heated maintained spaces. However, the current System-50 Large Area Maintenance Shelters used by the United States Air Force and Department of Defense are inadequate for Arctic deployments. These shelters lack durability against extreme subzero temperatures, heavy snow accumulation, and high wind speeds. They also fail to address critical Arctic-specific design challenges including permafrost protection, foundation disruption caused by frost heaves, and efficient heating as a result of their inadequate thermal resistance properties. This research analyzed 20 years of climatological data from 8,399 weather observation …
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 …
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 …
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 …
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 …
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, …
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 …
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 …
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, …
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 …
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 …
Design, Simulation, And Characterization Of A Deuterated Plastic Scintillator For A Portable Neutron Spectrometer, Anders M. Kinney Ii
Design, Simulation, And Characterization Of A Deuterated Plastic Scintillator For A Portable Neutron Spectrometer, Anders M. Kinney Ii
Theses and Dissertations
This thesis examines the design, simulation, and experimental characterization of a novel deuterated plastic scintillator for portable neutron spectroscopy applications related to homeland security and nuclear non-proliferation. Using Monte Carlo N-Particle (MCNP) simulations and experimental tests with gamma-ray (137Cs) and neutron sources (AmBe, 252Cf), this research shows that deuterium substitution in scintillators significantly enhances pulse shape discrimination (PSD) and neutron energy spectrum unfolding capabilities. Although deuterated scintillators demonstrate reduced overall light output, their higher stopping power and increased ionization quenching lead to superior neutron event differentiation, particularly between (α, n) and spontaneous fission neutrons critical for detecting …
Best Estimate Reconstruction Of The Control Profile For A Maneuvering Reentry Vehicle, Justin R. Evans
Best Estimate Reconstruction Of The Control Profile For A Maneuvering Reentry Vehicle, Justin R. Evans
Theses and Dissertations
Astrodynamic reentry is an increasingly important flight regime as countries around the world develop new spacecraft and weapons. A design of interest is that of hypersonic glide vehicles with the ability to maneuver in the atmosphere. As these vehicles become more common across the world, it has become advantageous to track foreign reentry tests in order to determine capabilities. While current observation techniques may allow position and velocity to be tracked across the trajectory, orientation of the vehicle is not always observable. The ability to find vehicle orientation across time gives insight into the performance characteristics of the vehicle. This …
Extension Of The Circular Restricted N-Body Problem (Crnbp) To Varying Multi-Body Gravitational Systems, Annika J. Gilliam
Extension Of The Circular Restricted N-Body Problem (Crnbp) To Varying Multi-Body Gravitational Systems, Annika J. Gilliam
Theses and Dissertations
Multi-body dynamical models are a valuable tool used to examine certain aspects of spacecraft orbital mechanics by applying assumptions to restrict the problem. The Circular Restricted Three-Body Problem (CR3BP), one of these dynamical models, has been examined extensively in the last few decades; however, this model is not sufficient in the case of more than two massive celestial bodies gravitationally affecting a spacecraft. A novel model called the Circular Restricted N-Body Problem (CRNBP) is studied in this research as an alternative to the traditional CR3BP where necessary. A variety of systems are examined in this thesis, including the Jovian, Saturnian, …
Approximating Three-Body Trajectories With A Knot Theory Inspired Model For Orbit Generation And Determination, Mason R. Mill
Approximating Three-Body Trajectories With A Knot Theory Inspired Model For Orbit Generation And Determination, Mason R. Mill
Theses and Dissertations
This thesis explores a novel approach to approximating three-body trajectories using a knot theory-inspired model for orbit generation and determination. Traditional methods for solving the Circular Restricted Three-Body Problem (CR3BP) rely on numerical integration and correction schemes to generate trajectories, often requiring iterative refinements. This research investigates the application of knot theory principles—such as torus knots, Alexander polynomials, and Reidemeister moves—to categorize and model complex orbital trajectories in the CR3BP. By leveraging these mathematical tools, the study aims to enhance trajectory prediction, orbit determination, and mission planning for spacecraft operating in the cislunar environment. The results demonstrate that knot theory …