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Articles 3721 - 3750 of 77518

Full-Text Articles in Engineering

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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Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson Mar 2025

Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson

Theses and Dissertations

This research investigated the performance of a Tsunami T50 Vapor Compression Cycle styled Atmospheric Water Generation (AWG) machine operated under ambient conditions in Dayton, Ohio. Water yield from the device was measured volumetrically and these values are paired with respective weather data, collected from a local monitoring station, to build an Artificial Neural Network in MATLAB and JMP software. Water yield varied over the course of this study but averaged 1.2L and maxed at 5L for 4-hour operating periods. This work is part of a 3-year project; future data is needed to enhance both training and validation of the model …

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Creating And Analyzing Space Vehicle Seit/Pm Factors, Jordan A. Bosco Mar 2025

Creating And Analyzing Space Vehicle Seit/Pm Factors, Jordan A. Bosco

Theses and Dissertations

The Department of Defense relies on accurate cost estimation to inform budget decisions. Beyond being a critical component of the Defense Acquisition System, cost estimation is a legal requirement in the budgeting process. Cost analysts, therefore, have both a fiduciary and statutory responsibility to produce realistic estimates. Among the many elements of a space system cost estimate is Space Vehicle Systems Engineering, Integration & Test, and Program Management (SEIT/PM). While existing factors aid in estimating SEIT/PM, Space Systems Command is interested in research in alternatives to the current methods and crosschecks for those methods. This study develops a set of …

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A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin Mar 2025

A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin

Theses and Dissertations

As fighter aircraft become more complex and technology, such as autonomy, is introduced, it is essential to anticipate the critical tasks and information pilots need to accomplish their mission with these new systems. Fighter pilots operate in highly demanding situations where the consequences of failure are severe and require their systems to provide the right information for the task. Traditionally, these designs are informed through Critical Task Analyses of existing systems. This research produced a method for modeling critical task analysis and information requirements using model-based systems engineering. The scenario was a fighter aircraft conducting basic fighter maneuvers in a …

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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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Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty Mar 2025

Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty

Theses and Dissertations

This thesis addresses the challenge of generating optimized UAV waypoints for complete coverage of complex 3D environments, utilizing graph-based computational techniques. The proposed framework replaces computationally intensive steps—triangulation and three-coloring—within the Vantage Waypoint Set Generation Algorithm (VWSGA) pipeline with Graph Neural Networks (GNNs). By learning structural patterns, the GNN achieves scalable and robust triangulation and node classification, enabling enhanced coverage planning in irregular geometries. A novel penalty mechanism ensures alignment with graph structure during adjacency prediction. Experimental results demonstrate the effectiveness of GNNs in balancing accuracy, computational efficiency, and adaptability, advancing UAV coverage optimization.

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Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros Mar 2025

Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros

Theses and Dissertations

Classification “flickering,” where the classification of an object changes inconsistently between consecutive video frames, remains a persistent issue in modern object classification algorithms. This problem undermines the reliability of autonomous vision systems and poses significant risks in high-stakes applications such as autonomous vehicles. This thesis explores the use of response surface methodology, a statistical design of experiments technique, to optimize hyperparameters across three object classification pipelines. The first pipeline combines YOLOv8 with SORT to establish a benchmark. The second integrates a Bayesian back-end, while the third employs an exponential smoothing back-end. Hyperparameter tuning was conducted using a two-step process: an …

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Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick Mar 2025

Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick

Theses and Dissertations

The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …

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Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman Mar 2025

Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman

Theses and Dissertations

This study examines the effects of active learning compared to didactic methodologies on two soft skills, namely teamwork and self-efficacy using regression analyses and connected letter reports. Learning styles and personality traits were used as predictors. Findings indicate significant interaction effects between methodology, aural learning style, and personality traits on self-efficacy and teamwork ability. The findings highlight the nuanced role of learner traits in shaping teamwork outcomes across instructional methods. While active learning supports soft skills, individual differences must be considered in instructional design to optimize teamwork in technical education settings.

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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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Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan Mar 2025

Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan

Theses and Dissertations

Autonomous vehicles are increasingly being deployed for use in high-stakes and uncertain environments where safe and efficient navigation is critical. In these scenarios, traditional path planning approaches, which rely primarily on deterministic models and fixed assumptions, fall short due to the inherent uncertainty of dynamic threats, sensor inaccuracies, and incomplete information. This research addresses these challenges by developing a novel path-planning methodology that combines the Chance-Constrained Rapidly Exploring Random Tree* (CC-RRT*) algorithm with a probabilistic risk assessment heuristic. This method models uncertainty in sensor detection zones, obstacles in the environment, and the Autonomous Vehicle itself, which allows for uncertainty during …

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Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens Mar 2025

Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens

Theses and Dissertations

Autonomous aircraft must land without human intervention, but existing methods rely on GPS or marked runways, which may be unavailable in austere environments. This paper presents a vision-based approach using semantic segmentation to detect runways and estimate aircraft pose by comparing camera and satellite imagery. We detail the model’s training and demonstrate its effectiveness with simulated and real UAV data.

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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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Data Lakehouse And Machine Learning Pipeline For Aircraft Fuel Efficiency Experimentation, Skyler G. Kepley Mar 2025

Data Lakehouse And Machine Learning Pipeline For Aircraft Fuel Efficiency Experimentation, Skyler G. Kepley

Theses and Dissertations

Fuel efficiency is crucial for the U.S. Air Force, impacting mission success, aircraft performance, and cost savings. This study presents an information system that integrates flight and maintenance data using a data lakehouse. It automates ingestion, enrichment, and predictive modeling, leveraging AutoML for optimization and SHAP for transparency. A case study on C-130J aircraft shows that optimizing D Check cycles can save 11.52 pounds of fuel per flight hour. These findings highlight the effectiveness of data-driven decision-making in aviation, offering a scalable, automated solution for improving fuel efficiency and reducing costs.

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Machine Learning With Flight Data Recorder Data For Flight Fuel Consumption Predictions, Adam C. Levandowski Mar 2025

Machine Learning With Flight Data Recorder Data For Flight Fuel Consumption Predictions, Adam C. Levandowski

Theses and Dissertations

This study applies advanced Machine Learning (ML) to Flight Data Recorder (FDR) data for fuel consumption predictions. It explores feature engineering, model selection, and Hyper-Parameter Optimization (HPO) across all flight phases. Baseline models like Ordinary Least Squares (OLS) regression, Multi- Layer Perceptrons (MLPs), and decision trees are compared to Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs) with Gated Recurrent Unit (GRU) layers, and XGBoost. Results analyze segmentation strategies, tailored features, and model performance. A counterfactual analysis compares ML models to operational fuel predictions, demonstrating their deployment potential. Findings establish a foundation for future ML-driven advancements in aviation fuel optimization.

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Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros Mar 2025

Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros

Theses and Dissertations

Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.

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Analysis Of An Army Recruiter Allocation Model (Ram), Erik J. Wittendorf Mar 2025

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.

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Maintenance Strategy And Budgeting Optimization For United States Air Force Facilities, Sophia C. Hirtle Mar 2025

Maintenance Strategy And Budgeting Optimization For United States Air Force Facilities, Sophia C. Hirtle

Theses and Dissertations

Mission readiness in the United States Air Force (USAF) is critically dependent on the sustainment and maintenance of aging facilities. However, budgetary and manpower constraints have led to a significant backlog of deferred maintenance, estimated at $137 billion. To address these challenges, this research develops an optimization model that aids in prioritizing facility maintenance strategies within a fixed budget. The methodology incorporates existing USAF data from BUILDER, NexGenIT, and financial records to create a simulation-based optimization framework at the base level. The model evaluates four different maintenance strategies—replacement only, preventative maintenance only, corrective maintenance only, and a combination of preventative …

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Statistical Analysis Of Spreading Code Authentication (Sca) Performance Under Varying Signal Conditions And Marker Quantization Schemes, Joseph Quinones-Ocasio Mar 2025

Statistical Analysis Of Spreading Code Authentication (Sca) Performance Under Varying Signal Conditions And Marker Quantization Schemes, Joseph Quinones-Ocasio

Theses and Dissertations

This thesis analyzes Spreading Code Authentication (SCA) in the GPS L1C signal using the PyChips software-defined receiver (SDR)framework. Monte Carlo simulations evaluate authentication performance under varying signal conditions, assessing the impact of double-precision and quantized data on signal integrity. Results demonstrate that authentication remains achievable at low signal-to-noise ratio(SNR) conditions but introduces trade-offs in memory usage and authentication time. These findings provide insights into optimizing SCAfor resource-constrained environments, contributing to secure GPS operations in critical applications such as aviation, autonomous systems,and national defense.

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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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Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner Mar 2025

Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner

Theses and Dissertations

This research formulates the medical evacuation (MEDEVAC) dispatching problem as a sequential decision process and investigates the application of reinforcement learning under nonstationary conditions. We model the dynamic arrival rate of MEDEVAC requests using a nonstationary Hawkes process and design a Double Deep Q-Network algorithm that incorporates belief states to anticipate future requests. Through computational experimentation, we analyze the impact of belief formulation on decision quality and system performance. Results indicate that policies incorporating belief states significantly outperform myopic dispatching policies, reducing urgent casualty wait times by up to 49.68% and increasing on-time evacuations by up to 21.91%.

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Evaluating Atmospheric Water Generation For The Indo-Pacific: Predictive Modeling, Energy Considerations, And Regional Viability, Jose I. De La Serna Mar 2025

Evaluating Atmospheric Water Generation For The Indo-Pacific: Predictive Modeling, Energy Considerations, And Regional Viability, Jose I. De La Serna

Theses and Dissertations

Atmospheric Water Generator (AWG) technology presents a promising solution for extracting and harvesting water from ambient air through condensation methods. This innovative approach offers a viable alternative for water production in regions with limited or unreliable water sources. AWGs operate most effectively in hot and humid environments, typically at temperatures of 80°F and relative humidity levels of 80%. As of 2020, the Department of Defense (DoD) has identified the Indo-Pacific region as a strategic focus for addressing future greatpower competition. Within the framework of Agile Combat Employment, this study evaluates the feasibility and performance of AWG technology at pre-determined locations …

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Discovering Design Requirements For Next Generation Arctic Tension Fabric Shelters, Mark W. Mcveigh Mar 2025

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 …

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An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves Mar 2025

An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves

Theses and Dissertations

This research establishes a novel agent-based modeling framework to establish the linkage between disaster-induced facility damage and mental health outcomes and the evaluation of treatment methods within the civilian and USAF mental health spheres. The study models the degradation and recovery of agent mental health using simulated data and evaluates the efficacy of three distinct treatment approaches through statistical methods. The methodology integrate agent-based modeling with resilient engineering concepts to simulate mental health resilience curves based on vulnerability, exposure, and facility damage. Agents’ mental health indices were tracked through phases of degradation, stagnation, and recovery based on the three treatments …

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Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei Mar 2025

Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei

Theses and Dissertations

Recent advancements in 3D cargo scanning and machine learning offer solutions to improve cargo processing reliability. This study enhances a 3D cargo scanning system by addressing software crashes, connectivity failures, and image accuracy issues limiting its operational effectiveness. A systematic approach identified the primary causes of system failures. System updates were implemented, followed by 30 pre- and post-update trials to evaluate reliability improvements. Statistical t-tests showed a significant reduction in failures, although processing time slightly increased. Results indicated that targeted hardware and software updates enhanced cargo scanning efficiency and dependability. Future work will focus on refining sensor calibration, optimizing network …

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Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy Mar 2025

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 …

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Understanding The Acceptance Of Digital Tools Within An Air Force Environment Using The Utaut2 Model, Britton J. Edwards Mar 2025

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 …

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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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Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy Mar 2025

Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy

Theses and Dissertations

Military airfields and civilian airports serve as foundational nodes in the global transportation network, enabling travel, economic growth, and the projection of national security. This study investigates the relationship between climate variables projected through climate change and pavement degradation, with a focus on Fairchild Air Force Base (AFB). Using principal component regression (PCR), the research integrates historical pavement condition index (PCI) data with climate variables, including snowfall, precipitation, freeze-thaw cycles, solar irradiance, and wind speed to develop a predictive model of pavement performance under future climate scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. These models, for both Portland …

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Material Classification With Spectropolarimetric Lidar, Alexander J. Watson Mar 2025

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, …

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