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Articles 7681 - 7710 of 41021

Full-Text Articles in Engineering

Characterizing Gesn Alloys By Sem/Eds And Photoluminescence Spectroscopy, Christopher M. Sutphin Mar 2023

Characterizing Gesn Alloys By Sem/Eds And Photoluminescence Spectroscopy, Christopher M. Sutphin

Theses and Dissertations

Germanium tin (GeSn) alloys are being studied as potential transition metal (Group IV) photoelectric semiconductors or optical detectors. GeSn alloys could be employed as an optically active material within a computer. Compared to current technologies, a direct band gap GeSn alloy can be engineered to operate with higher thermal stability and efficiency. The GeSn alloy studied was composed of Ge and Si substrates with various Sn percentages grown using remote plasma-enhanced chemical vapor deposition (RPECVD). Photoluminescence spectroscopy (PL) techniques were initially used to determine the GeSn properties, including the band gap. The Ge91.2Sn8.8 PL spectra suggested the …

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Simulation Of Neutron Generation From Laser-Driven Fusion In A Liquid D2o Sheet Using Novel Warpx Module, Colton R. Stoner Mar 2023

Simulation Of Neutron Generation From Laser-Driven Fusion In A Liquid D2o Sheet Using Novel Warpx Module, Colton R. Stoner

Theses and Dissertations

Using WarpX’s new nuclear fusion module, this work attempts to model an experimental system at the ELL at the AFIT with WarpX and draw conclusions about fusion products from resulting simulations. Recently, a table-top, high repetition rate, mixed radiation source was demonstrated at the ELL employing a HIL to fuse the deuterium nuclei present in a unique liquid target of heavy water. Analysis of the simulations predicted an isotropic output of neutrons from deuterium-deuterium fusion. These simulated neutrons were created in tens of femtoseconds from dense bodies of deuterons that were perturbed by the laser. However, it was found that …

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A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor Mar 2023

A Reinforcement Learning Approach To A Beyond Visual Range Air Combat Maneuvering Problem, Caleb A. Taylor

Theses and Dissertations

A one-versus-one air combat maneuvering problem is considered wherein a friendly autonomous aircraft must engage and defeat an adversary autonomous aircraft in a beyond visual range environment. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) is leveraged to model the complex and interdependent operations of aircraft, sensors, and weapons utilized in beyond visual range air combat. We formulate a Markov decision process to obtain high-quality decision policies wherein our autonomous aircraft makes maneuvering and missile firing decisions. We utilize a reinforcement learning solution procedure that implements a linear value function approximation to represent state-decision pairs due to the high …

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Modeling Radiation Exposure On Flight Missions To Analyze Aircrew Risk, Camila V. Quintero Hilsaca Mar 2023

Modeling Radiation Exposure On Flight Missions To Analyze Aircrew Risk, Camila V. Quintero Hilsaca

Theses and Dissertations

GCR and SPE comprise the majority of the ionizing radiation experienced in the upper atmosphere within flight-altitude environments. Although previous studies have analyzed radiation doses from single sources on civilian flight operations, there is a lack of research focused on dose received by military personnel during flight from both sources simultaneously. In-flight radiation environments are modeled through the MCNP6 for two separate aircraft, an Air Force A-10 and a Boeing 737. Particle fluence values for galactic cosmic rays and solar particle events for four separate flight paths are determined using the CARI-7A software and the SIRE2 toolkit, respectively. MCNP6 code …

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Pulsed Power Neutron Production With Deuterated Polymer Accelerator Targets, Anthony O. Hagey Mar 2023

Pulsed Power Neutron Production With Deuterated Polymer Accelerator Targets, Anthony O. Hagey

Theses and Dissertations

This document presents an investigation of the effect of deuterated polyethylene accelerator targets on the neutron fluence from a local mass injection dense plasma focus driven by the United States Naval Research Laboratory’s Hawk pulsed-power generator. After successful production of thin targets, the acquisition of thicker targets, and testing inside Hawk, it was found that the presence of a deuterated polyethylene target increased the neutron fluence. Results suggested that fluence can significantly increase with the presence of a deuterated target vs a nondeuterated target. Additive manufacturing printing was used as a production method in order to determine if deuterated accelerator …

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The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold Mar 2023

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …

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Classifying Open-Air Target Measurements Using Simulation-Trained Convolutional Neural Networks, Matthew M. Rofrano Mar 2023

Classifying Open-Air Target Measurements Using Simulation-Trained Convolutional Neural Networks, Matthew M. Rofrano

Theses and Dissertations

This research focuses on the development of machine learning networks that can identify and classify airborne targets using their radar cross section response. Simulation and measurement data for five targets was collected using Altair's CadFEKO software, and the Air Force Institute's Compact Radar Range. Three machine learning models were trained using simulation data, and evaluated using the collected measurement data. Variability is introduced to the training data by applying random gaussian noise to simulation results. Gaussian noise is added to the measurement data prior to evaluation in-order to model "hostile noise jamming." Network performance is measured against a baseline performance …

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Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson Mar 2023

Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson

Theses and Dissertations

The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …

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Temporal And Spatial Variability Of Specific Energy Consumption For Atmospheric Water Generators, Anthony T. Brenes Mar 2023

Temporal And Spatial Variability Of Specific Energy Consumption For Atmospheric Water Generators, Anthony T. Brenes

Theses and Dissertations

Atmospheric Water Generators (AWG) produce potable water from the moisture in the air, providing a potentially viable water source in austere locations or emergency response scenarios. In this study, the operating constraints of three existing commercially available AWG devices are investigated, compared to historical weather data from across the continental United States. Utilizing linear regression modeling and weather station data for the years of 1985-2019, the monthly and spatial trends of energy demand to produce water from these devices are evaluated. Energy and water production efficiencies for the devices are highly dependent on environmental conditions with relative humidity and temperature …

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Net Zero Water Air Force Installations, Kenneth R. Mcknight Mar 2023

Net Zero Water Air Force Installations, Kenneth R. Mcknight

Theses and Dissertations

The United States continues to face problems of a reduction in quality and quantity of groundwater sources because water extraction exceeds natural source recharge. The Air Force has recognized the importance of these groundwater sources but has put minimal effort into determining their contribution to the depletion of these sources. The purpose of this study is to determine this contribution by determining whether Air Force installations are net zero water. This is done using a geospatial information system to determine the volume of water recharging groundwater sources associated with an Air Force installation. This volume is then compared to the …

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Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill Mar 2023

Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill

Theses and Dissertations

Federated learning (FL) is a budding machine learning (ML) technique that seeks to keep sensitive data private, while overcoming the difficulties of Big Data. Specifically, FL trains machine learning models over a distributed network of devices, while keeping the data local to each device. We apply FL to a Parkinson’s Disease (PD) telemonitoring dataset where physiological data is gathered from various modalities to determine the PD severity level in patients. We seek to optimally combine the information across multiple modalities to assess the accuracy of our FL approach, and compare to traditional ”centralized” statistical and deep learning models.

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Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston Mar 2023

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

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Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim Mar 2023

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

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Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King Mar 2023

Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King

Theses and Dissertations

The United States Air Force (USAF) has struggled with a sustained pilot shortage over the past several years; senior military and government leaders have been working towards a solution to the problem, with no noticeable improvements. Both attrition of more experienced pilots as well as wash out rates within pilot training contribute to this issue. This research focuses on pilot training attrition. Improving the process for selecting pilot candidates can reduce the number of candidates who fail. This research uses historical specialized undergraduate pilot training (SUPT) data and leverages select machine learning techniques to determine which factors are associated with …

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Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian Mar 2023

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …

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Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald Mar 2023

Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald

Theses and Dissertations

This research examines the Cadet to Air Force Specialty Code (AFSC) Matching Problem (CAMP). Currently, the matching problem occurs annually at the Air Force Personnel Center (AFPC) using an integer program and value focused thinking approach. This paper presents a novel method to match cadets with AFSCs using a generalized structure of the Hospitals Residents problem with special emphasis on lower quotas. This paper also examines the United States Army Matching problem and compares it to the techniques and constraints applied to solve the CAMP. The research culminates in the presentation of three algorithms created to solve the CAMP and …

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Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia Mar 2023

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.

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Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller Mar 2023

Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller

Theses and Dissertations

The purposes of this study are to confirm the applicability of survival analysis for predicting recurrent failures of a component of a military aircraft and to provide practical insights to maintenance managers and mission planners. The results of this study also can help the United States Department of Defense improve the CBM+ program. This study was able to predict recurrent failures of the component using Nelson-Aalen cumulative estimates. In addition, this study used a Cox proportional hazards regression model with shared frailty for measuring the effect of covariates on recurrent failures and unidentified heterogeneity in the model, which warranted future …

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Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid Mar 2023

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

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Analysis And Optimization Of Contract Data Schema, Franklin Sun Mar 2023

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …

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Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith Mar 2023

Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith

Theses and Dissertations

Determining whether a simulation model is operationally valid requires the rigorous assessment of agreement between observed functional responses of the simulation model and the corresponding real world system or process of interest. This research seeks to extend and formulate the probability of agreement approach to the operational validation of simulation models. The first paper provides a methodological approach and an initial demonstration which leverages bootstrapping to overcome situations where one’s ability to collect real-world data is limited. The second paper extends the probability of agreement approach to account for second-order heteroscedastic variability structures and establishes a weighted probability of agreement …

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Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy Mar 2023

Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy

Theses and Dissertations

The analysis for the overall theoretical debris survivabilty of mega-constellation architectures, with an emphasis on space-based ballistic missile defense constellation (SB-BMD), is explored via three extensive different Monte Carlo simulations: preliminary analysis of low Earth Orbit (LEO) mega-constellation survivabilty following a fragmentation event within the constellation, analysis of LEO mega-constellation survivability with a fragmentation event occurring on a satellite performing a maneuver to insert itself within the constellation, and the analysis of LEO mega-constellation survivabilty after a fragmentation event resulting from the destruction of a missile. The LEO mega-constellations represent the SB-BMD constellation. The first two analysis sections will include …

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Description Of Reaction And Vibrational Energetics Of Co2-Nh3interaction Using Quantum Computing Algorithms, Manh Tien Nguyen, Yueh-Lin Lee, Dominic Alfonso, Qing Shao, Yuhua Duan Mar 2023

Description Of Reaction And Vibrational Energetics Of Co2-Nh3interaction Using Quantum Computing Algorithms, Manh Tien Nguyen, Yueh-Lin Lee, Dominic Alfonso, Qing Shao, Yuhua Duan

Markey Cancer Center Faculty Publications

CO2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO2. Thus, it is crucial to study the chemical absorption of CO2 by amine-based solvents to better understand and optimize CO2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3. Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular …

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Improved Object Re-Identification Via More Efficient Embeddings, Ertugrul Bayraktar Mar 2023

Improved Object Re-Identification Via More Efficient Embeddings, Ertugrul Bayraktar

Turkish Journal of Electrical Engineering and Computer Sciences

Object reidentification (ReID) in cluttered rigid scenes is a challenging problem especially when same-looking objects coexist in the scene. ReID is accepted to be one of the most powerful tools for matching the correct identities to each individual object when issues such as occlusion, missed detections, multiple same-looking objects coexisting in the same scene, and disappearance of objects from the view and/or revisiting the same region arise. We propose a novel framework towards more efficient object ReID, improved object reidentification (IO-ReID), to perform object ReID in challenging scenes with real-time processing in mind. The proposed approach achieves distinctive and efficient …

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A Modified Space Vector Modulation Based Rotor Flux Oriented Control Of Six-Phase Asymmetrical Induction Motor Drive, Krunal Shah, Rakesh Maurya Mar 2023

A Modified Space Vector Modulation Based Rotor Flux Oriented Control Of Six-Phase Asymmetrical Induction Motor Drive, Krunal Shah, Rakesh Maurya

Turkish Journal of Electrical Engineering and Computer Sciences

In view of the attractive features like improved torque density, reduction torque pulsation, superior fault tolerance, reduced power rating of voltage source converter, and sterling noise characteristics of six-phase asymmetrical induction motor (SPAIM) as compared to its three-phase counterpart, the SPAIM is considered for the study. In this paper, mathematical modelling of SPAIM is carried out in the synchronous reference frame and then indirect rotor field-oriented control (IRFOC) of SPAIM using a modified carrier wave-based space vector modulation (SVM) scheme is developed. A Simulink model of the proposed system configuration is developed and a simulation study is carried out. In …

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Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi Mar 2023

Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi

Theses and Dissertations

Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 …

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Are Natural Fractures In Sandstone Reservoir: Water Wet – Mixed Wet – Or Oil Wet?, Salah Almudhhi, Laila Abdullah, Waleed Al-Bazzaz, Saleh Alsayegh, Hussien Alajaj, Ralph E. Flori Mar 2023

Are Natural Fractures In Sandstone Reservoir: Water Wet – Mixed Wet – Or Oil Wet?, Salah Almudhhi, Laila Abdullah, Waleed Al-Bazzaz, Saleh Alsayegh, Hussien Alajaj, Ralph E. Flori

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This study accurately measures the wettability contact angle of native Kuwaiti sandstone reservoir that hosts mixed pore size distributions in both the tight sandstone matrix as well as the natural fracture (NF) embedded in it. Also, this study, effectively, investigates the geometrical size and shape of natural available voids whether matrix voids or NF voids captured in the rock 2D image frame system. Correspondingly, this study is, successfully, measure tight matrix, NF Pore wall, and NF pore opening wettability performance and recovery efficiency contributions inside the sandstone reservoir. A model pore/ grain contact angle wettability is generated. Therefore, this study …

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A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang Mar 2023

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …

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Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons Mar 2023

Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons

Faculty Publications

The coronal magnetic field over NOAA Active Region 11,429 during a X5.4 solar flare on 7 March 2012 is modeled using optimization based Non-Linear Force-Free Field extrapolation. Specifically, 3D magnetic fields were modeled for 11 timesteps using the 12-min cadence Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager photospheric vector magnetic field data, spanning a time period of 1 hour before through 1 hour after the start of the flare. Using the modeled coronal magnetic field data, seven different magnetic field parameters were calculated for 3 separate regions: areas with surface |Bz| ≥ 300 G, areas of flare brightening seen …

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Design And Concept Of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems In Bangladesh, Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, Mohammad K. Basher, Mohammad A. Islam, Narottam Das, Mohammad Nur-E-Alam Mar 2023

Design And Concept Of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems In Bangladesh, Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, Mohammad K. Basher, Mohammad A. Islam, Narottam Das, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Bangladesh’s railway system mostly uses typical manual railway crossing techniques or boom gates through its 2955.53 km rail route all over the country. Accidents frequently happen at railway crossings due to the lack of quickly operating gate systems, and to fewer safety measures at the railway crossing as well. Currently, there are very few automatic railway crossing systems available (without obstacle detectors). Additionally, all of them are dependent on the national power grid, without a backup plan for any emergency cases. Bangladesh is still running a bit behind in generating enough power for its consumption; hence, it is not possible …

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