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Air Force Institute of Technology

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Articles 241 - 270 of 3078

Full-Text Articles in Physical Sciences and Mathematics

Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth Mar 2024

Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth

Theses and Dissertations

High frequency (HF) communication is a vital aspect of military communication and is highly reliant upon ionospheric conditions. The variation in electron density within the lowest echelon of the ionosphere, the D-region, can significantly impact HF signals, making communication inconsistent and unreliable for these wavelengths. Despite the D-region’s important, research in this area mainly focuses on understanding the impact of space weather anomalies on the upper ionosphere, particularly its higher layers, with relatively little exploration of the D-region. This region, situated closest to the troposphere and stratosphere, has been definitively linked to solar weather events like solar flares and geomagnetic …

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Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman Mar 2024

Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman

Theses and Dissertations

This thesis explores the integration of Autoregressive Integrated Moving Average (ARIMA) models and technical analysis to forecast stock prices, with a focus on Coca-Cola's (KO) and Netflix’s (NFLX) stocks. It examines the effectiveness of combining ARIMA models, known for their predictive accuracy in time-series analysis, with technical indicators, particularly moving averages. The study evaluates whether this integrated approach can enhance the predictive capability of stocks prices beyond traditional methods. The predictive capability is evaluated using error metrics from the ARIMA models, as well as by assessing the return earned using simple rules based on the technical indicators. Utilizing data spanning …

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Housing Preferences And Vertical Expansion Potential In Riyadh City, Nasser R. Alrashed Mar 2024

Housing Preferences And Vertical Expansion Potential In Riyadh City, Nasser R. Alrashed

Theses and Dissertations

This research investigates the demand for apartment living in Riyadh's northern area and assesses its implications for vertical urban development, aligning with Saudi Arabia's Vision 2030. Employing a quantitative methodology, a structured survey was distributed to a diverse cross-section of Riyadh's population, focusing on housing preferences and perceptions of vertical living. Key findings indicate a significant demand for apartments, primarily from young to middle-aged, smaller households in low to middle-income brackets. Notably, a substantial portion of respondents showed a preference for high-rise living, suggesting a readiness for vertical expansion to manage the city's growing population. The study concludes that Riyadh's …

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Small Unmanned Aircraft System Detection And Tracking With Audio, Computer Vision, And Deep Learning Techniques, Anthony C. Brunson Mar 2024

Small Unmanned Aircraft System Detection And Tracking With Audio, Computer Vision, And Deep Learning Techniques, Anthony C. Brunson

Theses and Dissertations

sUAS present significant risks to local and federal agencies when under the control of negligent, reckless, or criminal operators. In the face of an escalating presence of sUAS in shared airspace with traditional aircraft, and their deployment in protected airspace as potential weapons, safeguarding personnel, facilities, and assets becomes paramount. This research seeks to address this emerging threat by investigating the efficacy of integrating low-cost distributed sensors and Machine learning (ML) models to enhance battlespace awareness and complement existing sensing platforms for real-time sUAS detection, classification, and localization. The thesis introduces the conceptualization and development of a Drone Detection Command …

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Performance Of Humans And Agents In A Systems Modeling Language V2 Task: A User-Centered Evaluation Approach, Allen W. Dukes Mar 2024

Performance Of Humans And Agents In A Systems Modeling Language V2 Task: A User-Centered Evaluation Approach, Allen W. Dukes

Theses and Dissertations

The Department of Defense is adopting Digital Engineering practices for its workforce. Simultaneously, the larger Systems Engineering community strives to modernize and define those Digital Engineering practices. These efforts to move from traditionally document-based approaches to pure digital implementations will require enhanced capabilities to manage and digitally track the lifecycle of a program or product. However, this growth must address tool design through an iterative process focusing on usability for many user types. Many tools and technologies exist but often lack an assessment of usability when engineers design tools for other engineers. Including usability when developing solutions for Digital Engineering …

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Advanced Oxidation Of Tert-Butanol With Ultraviolet Light Emitting Diodes And Hydrogen Peroxide, Lauren R. Mainolfi Mar 2024

Advanced Oxidation Of Tert-Butanol With Ultraviolet Light Emitting Diodes And Hydrogen Peroxide, Lauren R. Mainolfi

Theses and Dissertations

Tert-butanol (TBA), a versatile chemical widely used in industrial processes, poses exposure risks through inhalation, ingestion, and skin contact. Environmental contamination, often from industrial activities, emphasizes the importance of robust waste management and monitoring to protect water supplies from potential TBA migration and ensure drinking water safety. This study employed hydrogen peroxide (H2O2): TBA molar ratios of 100, 200, 400, and 500:1 in a Continuous Flow Stirred-Tank Reactor (CSTR) with UV-LED as the TBA degradation mechanism in an Advanced Oxidation Process (AOP). The UV-LEDs and H2O2 were synergistically employed to generate hydroxyl radicals in an advanced oxidation process. Gas chromatography–mass …

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Sensor-Based Vehicle Classification Using Machine Learning, Luke Mcfadden Mar 2024

Sensor-Based Vehicle Classification Using Machine Learning, Luke Mcfadden

Theses and Dissertations

This research investigates the classification of vehicles into heavy and light categories using acoustic, seismic, and magnetic sensor data. The effectiveness of using frequency domain data and classical machine learning techniques, is compared with the effectiveness of using time-series data and neural networks. The primary aim in doing so was to understand if modern neural network architectures could effectively remove the need for more traditional frequency based signals processing. A significant deliverable of this thesis was the feature importance determined for each of the three phenomenological types found within the data (acoustic, seismic, and magnetic). By analyzing the importance of …

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The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin Feb 2024

The Behavior Of ½⟨111⟩ Screw Dislocations In W–Mo Alloys Analyzed Through Atomistic Simulations, Lucas A. Heaton, Kevin Chu, Adib J. Samin

Faculty Publications

Analyzing plastic flow in refractory alloys is relevant to many different commercial and technological applications. In this study, screw dislocation statics and dynamics were studied for various compositions of the body-centered cubic binary alloy tungsten–molybdenum (W–Mo). The core structure did not appear to change for different alloy compositions, consistent with the literature. The pure tungsten and pure molybdenum samples had the lowest plastic flow, while the highest dislocation velocities were observed for equiatomic, W0.5Mo0.5 alloys. In general, dislocation velocities were found to largely align with a well-established dislocation mobility phenomenological model supporting two discrete dislocation mobility regimes, …

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Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton Feb 2024

Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton

Faculty Publications

CdSiP2 crystals are used in optical parametric oscillators to produce tunable output in the mid-infrared. As expected, the performance of the OPOs is adversely affected by residual optical absorption from native defects that are unintentionally present in the crystals. Electron paramagnetic resonance (EPR) identifies these native defects. Singly ionized silicon vacancies (V-Si) are responsible for broad optical absorption bands peaking near 800, 1033, and 1907 nm. A fourth absorption band, peaking near 630 nm, does not involve silicon vacancies. Exposure to 1064 nm light when the temperature of the CdSiP2 crystal is near 80K converts …

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Natural Language Processing Analysis Of Online Reviews For Small Business: Extracting Insight From Small Corpora, Benjamin J. Mccloskey, Phillip M. Lacasse, Bruce A. Cox Jan 2024

Natural Language Processing Analysis Of Online Reviews For Small Business: Extracting Insight From Small Corpora, Benjamin J. Mccloskey, Phillip M. Lacasse, Bruce A. Cox

Faculty Publications

Receiving and acting on customer input is essential to sustaining and growing any service organization, particularly a small family business whose livelihood depends on strong relationships with its customers. The competitive advantage offered by advanced analytical approaches for supporting decisions is not trivial, and enterprises across virtually all domains of society are investing heavily in this emerging discipline. Natural Language Processing (NLP) is a subset of computer science that employs computational approaches to analyze human language; it is effective at extracting insight from text data but frequently requires large corpora to train its models, in the scale of thousands or …

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Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen Jan 2024

Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (Es), demonstrating an improvement over current methods. This includes a binary classification model to determine if Es is present, followed by a regression model to estimate the Es ordinary mode critical frequency (foEs), a proxy for the intensity, along with the height at which the Es layer occurs (hEs). Signal-to-noise ratio (SNR) and excess phase profiles from six Global Navigation Satellite System (GNSS) radio occultation (RO) missions during the years 2008–2022 are used as the inputs of the model. Intensity (foEs) and the …

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Editorial: Observations And Simulations Of Layering Phenomena In The Middle/Upper Atmosphere And Ionosphere, Bingkun Yu, Xuguang Cai, Daniel J. Emmons Ii, Chong Wang, Jainfei Wu Jan 2024

Editorial: Observations And Simulations Of Layering Phenomena In The Middle/Upper Atmosphere And Ionosphere, Bingkun Yu, Xuguang Cai, Daniel J. Emmons Ii, Chong Wang, Jainfei Wu

Faculty Publications

The middle/upper atmosphere and ionosphere are the transition between neutral and ionized components of the Earth’s atmosphere, including stratosphere, mesosphere, thermosphere, ionospheric E region and ionospheric F region (Laštovička et al., 2006; Xu, et al., 2007; Smith, 2012). The atmospheric thermal structure and composition are significantly affected by dynamical processes through coupling. The layering phenomena such as mesospheric metal layers, sporadic E layers, and noctilucent clouds are important tracers to study mechanisms of the vertical coupling from the lower to the upper atmosphere (Dou et al., 2010; Plane, 2012; Xue et al., 2013).

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Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won Jan 2024

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …

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Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw Jan 2024

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw

Faculty Publications

Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …

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An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban Jan 2024

An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban

Faculty Publications

Achieving precise 6 degrees of freedom (6D) pose estimation of rigid objects from color images is a critical challenge with wide-ranging applications in robotics and close-contact aircraft operations. This study investigates key techniques in the application of YOLOv5 object detection convolutional neural network (CNN) for 6D pose localization of aircraft using only color imagery. Traditional object detection labeling methods suffer from inaccuracies due to perspective geometry and being limited to visible key points. This research demonstrates that with precise labeling, a CNN can predict object features with near-pixel accuracy, effectively learning the distinct appearance of the object due to perspective …

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Lithium Tetraborate As A Neutron Scintillation Detector: A Review, Elena Echeverria, John W. Mcclory, Lauren Samson, Katherine Shene, Juan A. Colon Santana, Yaroslav V. Burak, Volodymyr T. Adamiv, Ihor M. Teslyuk, Lu Wang, Wai-Ning Mei, Kyle A. Nelson, Douglas S. Mcgregor, Peter A. Dowben, Carolina C. Ilie, James C. Petrosky, Archit Dhingra Dec 2023

Lithium Tetraborate As A Neutron Scintillation Detector: A Review, Elena Echeverria, John W. Mcclory, Lauren Samson, Katherine Shene, Juan A. Colon Santana, Yaroslav V. Burak, Volodymyr T. Adamiv, Ihor M. Teslyuk, Lu Wang, Wai-Ning Mei, Kyle A. Nelson, Douglas S. Mcgregor, Peter A. Dowben, Carolina C. Ilie, James C. Petrosky, Archit Dhingra

Faculty Publications

The electronic structure and translucent nature of lithium tetraborate (Li2B4O7) render it promising as a scintillator medium for neutron detection applications. The inherently large neutron capture cross-section due to 10B and 6Li isotopes and the ease with which Li2B4O7 can be enriched with these isotopes, combined with the facile inclusion of rare earth dopants (occupying the Li+ sites), are expected to improve the luminescent properties, as well as the neutron detection efficiency, of Li2B4O7. The electronic structure of both doped …

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Passive Physical Layer Distinct Native Attribute Cyber Security Monitor, Christopher M. Rondeau, Michael A. Temple, Juan L. Lopez Jr., J. Addison Betances Dec 2023

Passive Physical Layer Distinct Native Attribute Cyber Security Monitor, Christopher M. Rondeau, Michael A. Temple, Juan L. Lopez Jr., J. Addison Betances

AFIT Patents

A method for cyber security monitor includes monitoring a network interface that is input-only configured to surreptitiously and covertly receive bit-level, physical layer communication between networked control and sensor field devices. During a training mode, a baseline distinct native attribute (DNA) fingerprint is generated for each networked field device. During a protection mode, a current DNA fingerprint is generated for each networked field device. The current DNA fingerprint is compared to the baseline DNA fingerprint for each networked field device. In response to detect at least one of RAA and PAA based on a change in the current DNA fingerprint …

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Shock-Wave Tolerant Phase Reconstruction Algorithm For Shack–Hartmann Wavefront Sensor Data, Thomas E. Defoor, Matthew Kalensky, Matthew R. Kemnetz, Timothy J. Bukowski, Mark F. Spencer Dec 2023

Shock-Wave Tolerant Phase Reconstruction Algorithm For Shack–Hartmann Wavefront Sensor Data, Thomas E. Defoor, Matthew Kalensky, Matthew R. Kemnetz, Timothy J. Bukowski, Mark F. Spencer

Faculty Publications

We develop a phase reconstruction algorithm for the Shack–Hartmann wavefront sensor (SHWFS) that is tolerant to phase discontinuities, such as the ones imposed by shock waves. In practice, this algorithm identifies SHWFS locations where the resultant tilt information is affected by the shock and improves the tilt information in these locations using the local SHWFS observation-plane irradiance patterns. The algorithm was shown to work well over the range of conditions tested with both simulated and experimental data. In turn, the reconstruction algorithm will enable robust wavefront sensing in transonic, supersonic, and hypersonic environments.

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Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminate Surrogate Particle From A Military Uniform Fabric, George Cooksey, Jeremy M. Slagley, Casey W. Cooper, Douglas Lewis, Alisha Helm Dec 2023

Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminate Surrogate Particle From A Military Uniform Fabric, George Cooksey, Jeremy M. Slagley, Casey W. Cooper, Douglas Lewis, Alisha Helm

Faculty Publications

In a mass casualty medical evacuation after a bioaerosol (BA) dispersal event, a decontamination (DC) method is needed that can both decontaminate and prevent biological particle (BP) re-aerosolization (RA) of contaminated clothes. However, neither the efficacy of current DC methods nor the risk of BP RA is greatly explored in the existing literature. The goals of this study were to develop a repeatable method to quantify the RA of a biological contaminant off military uniform fabric swatches and to test the efficacy of one DC protocol (high-volume, low-pressure water) using 1 µm polystyrene latex (PSL) spheres as a surrogate. A …

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A Hybrid Cognitive Model For Machine Agents In Project And Action Teams, Joshua A. Lapso Dec 2023

A Hybrid Cognitive Model For Machine Agents In Project And Action Teams, Joshua A. Lapso

Theses and Dissertations

High performing human teams transcend complex domain uncertainty by achieving an emergent state of shared cognition, in which knowledge is organized, represented, and distributed to team members for rapid execution. However, this requires that individuals emit perceivable qualities upon which other members can make inferences about intent. In pursuit of future human and machine team studies, this research presents a hybrid cognitive model for machine agents in fully cooperative and semi-cooperative action and project teams. The hybrid cognitive model unifies the characteristics of the shared mental model and transactive memory system. The resultant model facilitates anytime selection over the two …

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Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding Dec 2023

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

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Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer Dec 2023

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

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Analysis And Requirement Generation For Defense Intelligence Search: Addressing Data Overload Through Human–Ai Agent System Design For Ambient Awareness, Mark C. Duncan, Michael E. Miller, Brett J. Borghetti Nov 2023

Analysis And Requirement Generation For Defense Intelligence Search: Addressing Data Overload Through Human–Ai Agent System Design For Ambient Awareness, Mark C. Duncan, Michael E. Miller, Brett J. Borghetti

Faculty Publications

This research addresses the data overload faced by intelligence searchers in government and defense agencies. The study leverages methods from the Cognitive Systems Engineering (CSE) literature to generate insights into the intelligence search work domain. These insights are applied to a supporting concept and requirements for designing and evaluating a human-AI agent team specifically for intelligence search tasks. Domain analysis reveals the dynamic nature of the ‘value structure’, a term that describes the evolving set of criteria governing the intelligence search process. Additionally, domain insight provides details for search aggregation and conceptual spaces from which the value structure could be …

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Detailed Characterization Of A Khz-Rate Laser-Driven Fusion At A Thin Liquid Sheet With A Neutron Detection Suite, Benjamin M. Knight, Connor M. Gautam, Colton R. Stoner, Bryan V. Egner, Joseph R. Smith, Christopher M. Orban, Juan J. Manfredi, Kyle Frische, Michael L. Dexter, Enam A. Chowdury, Anil K. Patnaik Nov 2023

Detailed Characterization Of A Khz-Rate Laser-Driven Fusion At A Thin Liquid Sheet With A Neutron Detection Suite, Benjamin M. Knight, Connor M. Gautam, Colton R. Stoner, Bryan V. Egner, Joseph R. Smith, Christopher M. Orban, Juan J. Manfredi, Kyle Frische, Michael L. Dexter, Enam A. Chowdury, Anil K. Patnaik

Faculty Publications

We present detailed characterization of laser driven fusion and neutron production (∼105/second) employing 8 mJ, 40fs laser pulses on a thin (< 1 µm) D2O liquid sheet employing a measurement suite. At relativistic intensity (∼5×1018W/cm2) and high repetition-rate (1 kHz), the system produces consistent D-D fusion, allowing for consistent neutron generation. Evidence of D-D fusion neutron production is verified b y a measurement suite with three independent detection systems: an EJ-309 organic scintillator with pulse-shape discrimination, a 3He proportional counter, and a set of 36 bubble detectors. Time-of-flight analysis of the scintillator data shows …

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A Computational Approach For Mapping Electrochemical Activity Of Multi-Principal Element Alloys, Jodie A. Yuwono, Xinyu Li, Tyler D. Dolezal, Adib J. Samin, Javen Qinfeng Shi, Zhipeng Li, Nick Birbilis Nov 2023

A Computational Approach For Mapping Electrochemical Activity Of Multi-Principal Element Alloys, Jodie A. Yuwono, Xinyu Li, Tyler D. Dolezal, Adib J. Samin, Javen Qinfeng Shi, Zhipeng Li, Nick Birbilis

Faculty Publications

Multi principal element alloys (MPEAs) comprise an atypical class of metal alloys. MPEAs have been demonstrated to possess several exceptional properties, including, as most relevant to the present study a high corrosion resistance. In the context of MPEA design, the vast number of potential alloying elements and the staggering number of elemental combinations favours a computational alloy design approach. In order to computationally assess the prospective corrosion performance of MPEA, an approach was developed in this study. A density functional theory (DFT) – based Monte Carlo method was used for the development of MPEA ‘structure’; with the AlCrTiV alloy used …

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Legendre Pairs Of Lengths ℓ ≡ 0 (Mod 5), Ilias S. Kotsireas, Christopher Koutschan, Dursun A. Bulutoglu, David M. Arquette, Jonathan S. Turner, Kenneth J. Ryan Nov 2023

Legendre Pairs Of Lengths ℓ ≡ 0 (Mod 5), Ilias S. Kotsireas, Christopher Koutschan, Dursun A. Bulutoglu, David M. Arquette, Jonathan S. Turner, Kenneth J. Ryan

Faculty Publications

By assuming a type of balance for length ℓ = 87 and nontrivial subgroups of multiplier groups of Legendre pairs (LPs) for length ℓ = 85 , we find LPs of these lengths. We then study the power spectral density (PSD) values of m compressions of LPs of length 5 m . We also formulate a conjecture for LPs of lengths ℓ ≡ 0 (mod 5) and demonstrate how it can be used to decrease the search space and storage requirements for finding such LPs. The newly found LPs decrease the number of integers in the range ≤ 200 for …

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System-Level Noise Performance Of Coherent Imaging Systems, Derek J. Burrell, Joshua H. Follansbee, Mark F. Spencer, Ronald G. Driggers Nov 2023

System-Level Noise Performance Of Coherent Imaging Systems, Derek J. Burrell, Joshua H. Follansbee, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

We provide an in-depth analysis of noise considerations in coherent imaging, accounting for speckle and scintillation in addition to “conventional” image noise. Specifically, we formulate closed-form expressions for total effective noise in the presence of speckle only, scintillation only, and speckle combined with scintillation. We find analytically that photon shot noise is uncorrelated with both speckle and weak-to-moderate scintillation, despite their shared dependence on the mean signal. Furthermore, unmitigated speckle and scintillation noise tends to dominate coherent-imaging performance due to a squared mean-signal dependence. Strong coupling occurs between speckle and scintillation when both are present, and we characterize this behavior …

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Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim Nov 2023

Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim

Faculty Publications

Microelectromechanical systems (MEMS) resonators use is widespread, from electronic filters and oscillators to physical sensors such as accelerometers and gyroscopes. These devices' ubiquity, small size, and low power consumption make them ideal for use in systems such as CubeSats, micro aerial vehicles, autonomous underwater vehicles, and micro-robots operating in radiation environments. Radiation's interaction with materials manifests as atomic displacement and ionization, resulting in mechanical and electronic property changes, photocurrents, and charge buildup. This study examines silicon (Si) ion irradiation's interaction with piezoelectrically transduced MEMS resonators. Furthermore, the effect of adding a dielectric silicon oxide (SiO2) thin film is …

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Strong Evidence For 9N And The Limits Of Existence Of Atomic Nuclei, R. J. Charity, J. Wylie, S. M. Wang, T. B. Webb, K. W. Brown, G. Cerizza, Z. Chajecki, J. M. Elson, J. Estee, D. E. M. Hoff, S. A. Kuvin, W. G. Lynch, Juan J. Manfredi, N. Michel, D. G. Mcneel, P. Morfouace, W. Nazarewicz, C. D. Pruitt, C. Santamaria, S. Sweany, J. Smith, L. G. Sobotka, M. B. Tsang, A. H. Wuosmaa Oct 2023

Strong Evidence For 9N And The Limits Of Existence Of Atomic Nuclei, R. J. Charity, J. Wylie, S. M. Wang, T. B. Webb, K. W. Brown, G. Cerizza, Z. Chajecki, J. M. Elson, J. Estee, D. E. M. Hoff, S. A. Kuvin, W. G. Lynch, Juan J. Manfredi, N. Michel, D. G. Mcneel, P. Morfouace, W. Nazarewicz, C. D. Pruitt, C. Santamaria, S. Sweany, J. Smith, L. G. Sobotka, M. B. Tsang, A. H. Wuosmaa

Faculty Publications

The boundaries of the chart of nuclides contain exotic isotopes that possess extreme proton-to-neutron asymmetries. Here we report on strong evidence of 9N, one of the most exotic proton-rich isotopes where more than one half of its constitute nucleons are unbound. With seven protons and two neutrons, this extremely proton-rich system would represent the first-known example of a ground-state five-proton emitter. The invariant-mass spectrum of its decay products can be fit with two peaks whose energies are consistent with the theoretical predictions of an open-quantum-system approach; however, we cannot rule out the possibility that only a single resonancelike peak …

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Active-Illumination Extension To The Priest And Meier Pbrdf, Mark F. Spencer, Milo W. Hyde Iv, Santasri R. Bose-Pillai, Michael A. Marciniak Oct 2023

Active-Illumination Extension To The Priest And Meier Pbrdf, Mark F. Spencer, Milo W. Hyde Iv, Santasri R. Bose-Pillai, Michael A. Marciniak

Faculty Publications

This paper develops a 3D vector solution for the scattering of partially coherent laser-beam illumination from statistically rough surfaces. Such a solution enables a rigorous comparison to the well-known Priest and Meier polarimetric bidirectional reflectance distribution function (pBRDF) [Opt Eng 41(5),988 (2002).]. Overall, the comparison shows excellent agreement for the normalized spectral density and the degree of polarization. Based on this agreement, the 3D vector solution also enables an extension to the Priest and Meier pBRDF that accounts for the effects of active illumination. In particular, the 3D vector solution enables the development of a closed-form expression for the spectral …

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