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Air Force Institute of Technology

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Articles 691 - 720 of 3057

Full-Text Articles in Physical Sciences and Mathematics

Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley Aug 2020

Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley

Faculty Publications

This paper explores the through-the-wall inverse scattering problem via machine learning. The reconstruction method seeks to discover the shape, location, and type of hidden objects behind walls, as well as identifying certain material properties of the targets. We simulate RF sources and receivers placed outside the room to generate observation data with objects randomly placed inside the room. We experiment with two types of neural networks and use an 80-20 train-test split for reconstruction and classification.

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Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson Aug 2020

Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson

Faculty Publications

All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have constrained faults to biases and designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with valid measurement models, none of which are guaranteed for all-source systems. As part of an overall all-source assured or resilient navigation …

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Simulated Experince Evaluation In Developing Multi-Agent Coordination Graphs, Andrew J. Watson Jul 2020

Simulated Experince Evaluation In Developing Multi-Agent Coordination Graphs, Andrew J. Watson

Theses and Dissertations

Cognitive science has proposed that a way people learn is through self-critiquing by generating 'what-if' strategies for events (simulation). It is theorized that people use this method to learn something new as well as to learn more quickly. This research adds this concept to a graph-based genetic program. Memories are recorded during fitness assessment and retained in a global memory bank based on the magnitude of change in the agent’s energy and age of the memory. Between generations, candidate agents perform in simulations of the stored memories. Candidates that perform similarly to good memories and differently from bad memories are …

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Turbulence Profiling Using Pupil Plane Wavefront Data Derived Fried Parameter Values For A Dynamically Ranged Rayleigh Beacon, Steven M. Zuraski, Elizabeth Beecher, Jack E. Mccrae, Steven T. Fiorino Jul 2020

Turbulence Profiling Using Pupil Plane Wavefront Data Derived Fried Parameter Values For A Dynamically Ranged Rayleigh Beacon, Steven M. Zuraski, Elizabeth Beecher, Jack E. Mccrae, Steven T. Fiorino

Faculty Publications

Long-range optical imaging applications are typically hindered by atmospheric turbulence. The effect of turbulence on an imaging system can manifest itself as an image blur effect usually quantified by the phase distortions present in the system. The blurring effect can be understood on the basis of the measured strength of atmospheric optical turbulence along the propagation path and its impacts on phase perturbation statistics within the imaging system. One method for obtaining these measurements is by the use of a dynamically ranged Rayleigh beacon system that exploits strategically varied beacon ranges along the propagation path, effectively obtaining estimates of the …

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Measurements Of Optical Turbulence Over 149-Km Path, Jack E. Mccrae, Santasri Bose-Pillai, Steven T. Fiorino, Aaron J. Archibald, Joel Meoak, Brannon Elmore, Thomas Kesler, Christopher A. Rice Jul 2020

Measurements Of Optical Turbulence Over 149-Km Path, Jack E. Mccrae, Santasri Bose-Pillai, Steven T. Fiorino, Aaron J. Archibald, Joel Meoak, Brannon Elmore, Thomas Kesler, Christopher A. Rice

Faculty Publications

An experiment was conducted to study turbulence along a 149-km path between the Mauna Loa and Haleakala mountain tops using digital cameras and light-emitting diode (LED) beacons. Much of the path is over the ocean, and a large portion of the path is 3 km above sea level. On the Mauna Loa side, six LED beacons were placed in a roughly linear array with pair spacings from 7 to 62 m. From the Haleakala side, a pair of cameras separated by 83.8 cm observed these beacons. Turbulence along the path induces tilts on the wavefronts, which results in displacements of …

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Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: I. Using Steady-State Simulations, Mark F. Spencer Jul 2020

Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: I. Using Steady-State Simulations, Mark F. Spencer

Faculty Publications

Part I of this two-part paper uses wave-optics simulations to look at the Monte Carlo averages associated with turbulence and steady-state thermal blooming (SSTB). The goal is to investigate turbulence thermal blooming interaction (TTBI). At wavelengths near 1 μm, TTBI increases the amount of constructive and destructive interference (i.e., scintillation) that results from high-power laser beam propagation through distributed-volume atmospheric aberrations. As a result, we use the spherical-wave Rytov number and the distortion number to gauge the strength of the simulated turbulence and SSTB. These parameters simplify greatly given propagation paths with constant atmospheric conditions. In addition, we use the …

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Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: Ii. Using Time-Dependent Simulations, Mark F. Spencer Jul 2020

Wave-Optics Investigation Of Turbulence Thermal Blooming Interaction: Ii. Using Time-Dependent Simulations, Mark F. Spencer

Faculty Publications

Part II of this two-part paper uses wave-optics simulations to look at the Monte Carlo averages associated with turbulence and time-dependent thermal blooming (TDTB). The goal is to investigate turbulence thermal blooming interaction (TTBI). At wavelengths near 1 μm, TTBI increases the amount of constructive and destructive interference (i.e., scintillation) that results from high-power laser beam propagation through distributed-volume atmospheric aberrations. As a result, we use the spherical-wave Rytov number, the number of wind-clearing periods, and the distortion number to gauge the strength of the simulated turbulence and TDTB. These parameters simply greatly given propagation paths with constant atmospheric conditions. …

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Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham, James Anderson, Conrad Rife, Bryce Heitmeyer, Pranav R. Patel, Scott L. Nykl, Alan C. Lin, Laurence D. Merkle Jul 2020

Cyberspace Odyssey: A Competitive Team-Oriented Serious Game In Computer Networking, Kendra Graham, James Anderson, Conrad Rife, Bryce Heitmeyer, Pranav R. Patel, Scott L. Nykl, Alan C. Lin, Laurence D. Merkle

Faculty Publications

Cyber Space Odyssey (CSO) is a novel serious game supporting computer networking education by engaging students in a race to successfully perform various cybersecurity tasks in order to collect clues and solve a puzzle in virtual near-Earth 3D space. Each team interacts with the game server through a dedicated client presenting a multimodal interface, using a game controller for navigation and various desktop computer networking tools of the trade for cybersecurity tasks on the game's physical network. Specifically, teams connect to wireless access points, use packet monitors to intercept network traffic, decrypt and reverse engineer that traffic, craft well-formed and …

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Applications Of Portable Libs For Actinide Analysis, Ashwin P. Rao, John D. Auxier Ii, Dung Vu, Michael B. Shattan Jul 2020

Applications Of Portable Libs For Actinide Analysis, Ashwin P. Rao, John D. Auxier Ii, Dung Vu, Michael B. Shattan

Faculty Publications

A portable LIBS device was used for rapid elemental impurity analysis of plutonium alloys. This device demonstrates the potential for fast, accurate in-situ chemical analysis and could significantly reduce the fabrication time of plutonium alloys.

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Implications Of Four-Dimensional Weather Cubes For Improved Cloud-Free Line-Of-Sight Assessments Of Free-Space Optical Communications Link Performance, Steven T. Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin J. Keefer Jul 2020

Implications Of Four-Dimensional Weather Cubes For Improved Cloud-Free Line-Of-Sight Assessments Of Free-Space Optical Communications Link Performance, Steven T. Fiorino, Santasri Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, Kevin J. Keefer

Faculty Publications

We advance the benefits of previously reported four-dimensional (4-D) weather cubes toward the creation of high-fidelity cloud-free line-of-sight (CFLOS) beam propagation for realistic assessment of autotracked/dynamically routed free-space optical (FSO) communication datalink concepts. The weather cubes accrue parameterization of optical effects and custom atmospheric resolution through implementation of numerical weather prediction data in the Laser Environmental Effects Definition and Reference atmospheric characterization and radiative transfer code. 4-D weather cube analyses have recently been expanded to accurately assess system performance (probabilistic climatologies and performance forecasts) at any wavelength/frequency or spectral band in the absence of field tests and employment data. The …

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Effects Of Temperature And Antioxidants On The Oxidation Of Biodiesel Derived From Waste Vegetable Oil, Randy L. Maglinao, Torrey J. Wagner, Keegan Duff Jun 2020

Effects Of Temperature And Antioxidants On The Oxidation Of Biodiesel Derived From Waste Vegetable Oil, Randy L. Maglinao, Torrey J. Wagner, Keegan Duff

Faculty Publications

Biodiesel offers several environmental benefits and improvements to some fuel performance properties, but its poor oxidative stability has been a major concern. Currently, the accepted practice to improve biodiesel oxidative stability is the addition of antioxidants; numerous antioxidants have been studied but their effectiveness in inhibiting biodiesel oxidation is difficult to predict due to variation with resonance stability, solubility, reactivity, and volatility. To improve prediction efforts, this study explored the Rapid Small-Scale Oxidation Test (RSSOT) as a means to investigate how biodiesel oxidation is affected by antioxidant concentration and temperature, and compared its results with the oxidative stability index test. …

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Fourier Propagation Tool For Aberration Analysis And A Point Spread Function Calculation Of Systems With Curved Focal Planes, Stephen C. Cain Jun 2020

Fourier Propagation Tool For Aberration Analysis And A Point Spread Function Calculation Of Systems With Curved Focal Planes, Stephen C. Cain

Faculty Publications

This paper describes a new Fourier propagator for computing the impulse response of an optical system with a curved focal plane array, while including terms ignored in Fresnel and Fraunhofer calculations. The propagator includes a Rayleigh-Sommerfeld diffraction formula calculation from a distant point through the optical system to its image point predicted by geometric optics on a spherical surface. The propagator then approximates the neighboring field points via the traditional binomial approximation of the Taylor series expansion around that field point. This technique results in a propagator that combines the speed of a Fourier transform operation with the accuracy of …

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Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal Jun 2020

Statistical Photo-Calibration Of Photo-Detectors For Radiometry Without Calibrated Light Sources Comprising An Arithmetic Unit To Determine A Gain And A Bias From Mean Values And Variance Values, Adrian M. Catarius, Nicholas Yielding, Stephen C. Cain, Michael D. Seal

AFIT Patents

Calibration of a radiometry system uses a readout circuit of a photo-detector to provide first and second measurements collected over first and second integration times, respectively, where the first and second measurements are related to a photonic input to the photo-detector by a gain and a bias. First mean and variance values are computed for a plurality of first measurements. Second mean and variance values are computed for a plurality of second measurements. The gain and bias are determined from the first and second mean values and the first and second variance values without the use of a calibrated source. …

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Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei Jun 2020

Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei

Theses and Dissertations

Operation of Unmanned Aerial Vehicles (UAV) support many critical missions in the United State Air Force (USAF). Monitoring abnormal behavior is one of many responsibilities of the operator during a mission. Some behaviors are hard to be detect by an operator, especially when flying one or more autonomous vehicles; as such, detections require a high level of attention and focus to flight parameters. In this research, a monitoring system and its algorithm are designed and tested for a target fixed-wing UAV. The Autonomy Monitoring Service (AMS) compares the real vehicle or simulated Vehicle with a similar simulated vehicle using Software …

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Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery Jun 2020

Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery

Theses and Dissertations

This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …

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Neural Network Models For Nuclear Treaty Monitoring: Enhancing The Seismic Signal Pipeline With Deep Temporal Convolution, Joshua T. Dickey Jun 2020

Neural Network Models For Nuclear Treaty Monitoring: Enhancing The Seismic Signal Pipeline With Deep Temporal Convolution, Joshua T. Dickey

Theses and Dissertations

Seismic signal processing at the IDC is critical to global security, facilitating the detection and identification of covert nuclear tests in near-real time. This dissertation details three research studies providing substantial enhancements to this pipeline. Study 1 focuses on signal detection, employing a TCN architecture directly against raw real-time data streams and effecting a 4 dB increase in detector sensitivity over the latest operational methods. Study 2 focuses on both event association and source discrimination, utilizing a TCN-based triplet network to extract source-specific features from three-component seismograms, and providing both a complimentary validation measure for event association and a one-shot …

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Battlespace Next™: Developing A Serious Game To Explore Multi-Domain Operations, Nathaniel Flack, Alan C. Lin, Gilbert L. Peterson, Mark G. Reith Jun 2020

Battlespace Next™: Developing A Serious Game To Explore Multi-Domain Operations, Nathaniel Flack, Alan C. Lin, Gilbert L. Peterson, Mark G. Reith

Faculty Publications

Changes in the geopolitical landscape and increasing technological complexity have prompted the U.S. Military to coin the terms Multi-Domain Operations (MDO) and Joint All-Domain Command and Control (JADC2) as over-arching strategy to frame the complexity of warfare across both traditional and emerging warfighting domains. Teaching new concepts associated with these terms requires both innovation as well as distinct education and training tools in order to realize the cultural change advocated by senior military leaders. Battlespace Next™ (BSN) is a serious game designed to teach concepts integral to MDO and initiate discussion on military strategy while conserving time, money, and manpower. …

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A Physics-Based Machine Learning Study Of The Behavior Of Interstitial Helium In Single Crystal W–Mo Binary Alloys, Adib J. Samin May 2020

A Physics-Based Machine Learning Study Of The Behavior Of Interstitial Helium In Single Crystal W–Mo Binary Alloys, Adib J. Samin

Faculty Publications

In this work, the behavior of dilute interstitial helium in W–Mo binary alloys was explored through the application of a first principles-informed neural network (NN) in order to study the early stages of helium-induced damage and inform the design of next generation materials for fusion reactors. The neural network (NN) was trained using a database of 120 density functional theory (DFT) calculations on the alloy. The DFT database of computed solution energies showed a linear dependence on the composition of the first nearest neighbor metallic shell. This NN was then employed in a kinetic Monte Carlo simulation, which took into …

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Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan May 2020

Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan

Faculty Publications

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …

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Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola Apr 2020

Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola

Faculty Publications

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …

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Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides Apr 2020

Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides

Faculty Publications

We present a novel light detection and ranging (LiDAR) polarimeter that enables measurement of 12 of 16 sample Mueller matrix elements in a single, 10 ns pulse. The new polarization state generator (PSG) leverages Kerr phase modulation in a birefringent optical fiber, creating a probe pulse characterized by temporally varying polarization. Theoretical expressions for the Polarization State Generator (PSG) Stokes vector are derived for birefringent walk-off and no walk-off and incorporated into a time-dependent polarimeter signal model employing multiple polarization state analyzers (PSA). Polarimeter modeling compares the Kerr effect and electro-optic phase modulator–based PSG using a single Polarization State Analyzer …

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Experimental Determination Of The (0/−) Level For Mg Acceptors In Β-Ga2O3 Crystals, Christopher A. Lenyk, Timothy D. Gustafson, Sergey A. Basun, Larry E. Halliburton, Nancy C. Giles Apr 2020

Experimental Determination Of The (0/−) Level For Mg Acceptors In Β-Ga2O3 Crystals, Christopher A. Lenyk, Timothy D. Gustafson, Sergey A. Basun, Larry E. Halliburton, Nancy C. Giles

Faculty Publications

Electron paramagnetic resonance (EPR) is used to experimentally determine the (0/−) level of the Mg acceptor in an Mg-doped β-Ga2O3 crystal. Our results place this level 0.65 eV (±0.05 eV) above the valence band, a position closer to the valence band than the predictions of several recent computational studies. The crystal used in this investigation was grown by the Czochralski method and contains large concentrations of Mg acceptors and Ir donors, as well as a small concentration of Fe ions and an even smaller concentration of Cr ions. Below room temperature, illumination with 325 nm laser light …

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Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki Mar 2020

Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki

Theses and Dissertations

Performing flight tests is a natural part of researching cutting edge sensors and filters for sensor integration. Unfortunately, tests are expensive, and typically take many months of planning. A sensible goal would be to make previously collected data readily available to researchers for future development. The Air Force Institute of Technology (AFIT) has hundreds of data logs potentially available to aid in facilitating further research in the area of navigation. A database would provide a common location where older and newer data sets are available. Such a database must be able to store the sensor data, metadata about the sensors, …

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Cyber-Physical System Intrusion: A Case Study Of Automobile Identification Vulnerabilities And Automated Approaches For Intrusion Detection, David R. Crow Mar 2020

Cyber-Physical System Intrusion: A Case Study Of Automobile Identification Vulnerabilities And Automated Approaches For Intrusion Detection, David R. Crow

Theses and Dissertations

Today's vehicle manufacturers do not tend to publish proprietary packet formats for the controller area network (CAN), a network protocol regularly used in automobiles and manufacturing. This is a form of security through obscurity -it makes reverse engineering efforts more difficult for would-be intruders -but obfuscating the CAN data in this way does not adequately hide the vehicle's unique signature, even if these data are unprocessed or limited in scope. To prove this, we train two distinct deep learning models on data from 11 different vehicles. Our results clearly indicate that one can determine which vehicle generated a given sample …

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Sliver: Simulation-Based Logic Bomb Identification/Verification For Unmanned Aerial Vehicles, Jake M. Magness Mar 2020

Sliver: Simulation-Based Logic Bomb Identification/Verification For Unmanned Aerial Vehicles, Jake M. Magness

Theses and Dissertations

This research introduces SLIVer, a Simulation-based Logic Bomb Identification/Verification methodology, for finding logic bombs hidden within Unmanned Aerial Vehicle (UAV) autopilot code without having access to the device source code. Effectiveness is demonstrated by executing a series of test missions within a high-fidelity software-in-the-loop (SITL) simulator. In the event that a logic bomb is not detected, this methodology defines safe operating areas for UAVs to ensure to a high degree of confidence the UAV operates normally on the defined flight plan. SLIVer uses preplanned flight paths as the baseline input space, greatly reducing the input space that must be searched …

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Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman Mar 2020

Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman

Theses and Dissertations

The objective of this research is to develop a numerical method to characterize heat transfer and wear rates for samples of Vascomax® 300, or Maraging 300, steel. A pin-on-disc experiment was conducted in which samples were exposed to a high-pressure, high-speed, sliding contact environment. This sliding contact generates frictional heating that influences the temperature distribution and wear characteristics of the test samples. A two-dimensional nonlinear heat transfer equation is discretized and solved via a second-order explicit finite difference scheme to predict the transient temperature distribution of the pin. This schematic is used to predict the removal of material from the …

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Honeyhive - A Network Intrusion Detection System Framework Utilizing Distributed Internet Of Things Honeypot Sensors, Zachary D. Madison Mar 2020

Honeyhive - A Network Intrusion Detection System Framework Utilizing Distributed Internet Of Things Honeypot Sensors, Zachary D. Madison

Theses and Dissertations

Exploding over the past decade, the number of Internet of Things (IoT) devices connected to the Internet jumped from 3.8 billion in 2015 to 17.8 billion in 2018. Because so many IoT devices remain upatched, unmonitored, and left on, they have become a tantalizing target for attackers to gain network access or add another device to their botnet. HoneyHive is a framework that uses distributed IoT honeypots as Network Intrusion Detection Systems (NIDS) sensors that beacon back to a centralized Command and Control (C2) server. The tests in this experiment involve four types of scans and four levels of active …

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Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest Mar 2020

Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest

Theses and Dissertations

The Air Forces Pilot Training Next (PTN) program seeks a more efficient pilot training environment emphasizing the use of virtual reality flight simulators alongside periodic real aircraft experience. The PTN program wants to accelerate the training pace and progress in undergraduate pilot training compared to traditional undergraduate pilot training. Currently, instructor pilots spend excessive time planning and scheduling flights. This research focuses on methods to auto-generate the planning of in-flight events using hybrid filtering and deep learning techniques. The resulting approach captures temporal trends of user-specific and program-wide student performance to recommend a feasible set of graded flight events for …

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Extracting Range Data From Images Using Focus Error, Erik M. Madden Mar 2020

Extracting Range Data From Images Using Focus Error, Erik M. Madden

Theses and Dissertations

Air-to-air refueling (AAR) has become a staple when performing long missions with aircraft. With modern technology, however, people have begun to research how to perform this task autonomously. Automated air-to-air refueling (A3R) is this exact concept. Combining many different systems, the idea is to allow computers on the aircraft to link up via the refueling boom, refuel, and detach before resuming pilot control. This document lays out one of the systems that is needed to perform A3R, namely, the system that extracts range data. While stereo cameras perform such tasks, there is interest in finding other ways of accomplishing the …

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An Analysis Of A Lighting Prediction Threshold For 45th Weather Squadron Electric Field Mill Data, Charles A. Skrovan Mar 2020

An Analysis Of A Lighting Prediction Threshold For 45th Weather Squadron Electric Field Mill Data, Charles A. Skrovan

Theses and Dissertations

The mission of the 45th Weather Squadron (45 WS) is to “exploit the weather to assure safe access to air and space” for Patrick Air Force Base, Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC) in support of various operations (United States Air Force, n.d.). To support that mission the 45 WS hosts a suite of weather detection instruments that include a lightning warning system that consists of an array of 31 electric field mills (EFM) and a lightning detection and ranging system (Department of the Air Force, 1976). Electric field mills at Cape Canaveral continuously record …

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