Digital Commons Network^™

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.

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 …

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 …

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 …

An Improved Saliency Map With Trustworthiness For Localizing Abnormalities In Medical Imaging, Nolan C. Skelly

Theses and Dissertations

Saliency maps are a widely used methodology to make deep learning models more interpretable. They provide post-hoc explanations through identification of the most pertinent areas of an input medical image. These techniques have been assessed based on 1) localization utility, 2) sensitivity to model weight randomization, 3) repeatability, and 4) reproducibility. Ten saliency map techniques will be tested, Grad, Smooth Grad, Integrated Gradients, Smooth Integrated Gradients, XRAI, Grad-CAM, Guided Backpropagation, Guided GradCAM, GradCAM++, and ScoreCAM. The neural networks used to predict and read medical information require a reliable solution to provide medical practitioners intelligible results. Using the information of two, …

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. …

A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design, Eric T. Sommer

Theses and Dissertations

As the capabilities provided by space-based systems offer significant contributions toward defense applications, potential adversaries stand to gain significant value in disrupting them. Therefore, the United States must pursue the development and operation of resilient space architectures, capable of delivering capabilities in the face of disruptions. To support this development, systems engineering methods require innovation to effectively ensure design of complex space architectures to meet their objectives. This thesis recommends and demonstrates a System-Theoretic Process Analysis (STPA) framework to qualitatively analyze space architectures. The analysis outputs identify design considerations, requirements, and constraints required for resilience. To enable a model-based systems …

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 …

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 …

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 …

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 …

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 …

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 …

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patnaik

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

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 …

Deconstructing The Software Factory: A Practical Application Of Interorganizational Network Analysis, Zachary O. Ryan, Mark Reith, Clay Koschnick

Faculty Publications

Over the past 5 years, the number of DoD software organizations that employ nontraditional organizational structures has increased. These organizations, commonly referred to as software factories, often employ the network-based organizational structures found within high-technology industries. This article details ways in which network analysis techniques can be used to create a big picture view of these nontraditional organizations. Drawing on methodologies employed by network researchers, the authors develop and present an interorganizational analysis process that highlights a program's social and economic structures. Following the case history approach, they demonstrate the applicability of this approach by analyzing an emergent DoD software …

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor

Faculty Publications

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but …

Influencing Air Force Logisticians' Information Seeking During The Covid-19 Pandemic: The Role Of Organizational Meetings In An Expanded Prism Framework, Matthew D. Roberts, Christopher T. Price, Seong-Jong Joo

Faculty Publications

Purpose: This research aims to understand how organizational workplace meetings surrounding the COVID-19 pandemic impacted logistics Airmen across the United States Air Force and how these meetings impacted their risk seeking behavior on social media.

Design/methodology/approach: This survey research tested an extended Planned Risk Information Risk Seeking Model (PRISM) with organizational meetings as an antecedent to determine if current meetings influenced an Airman's perceived behavioral control, attitude toward seeking, subjective norms, knowledge sufficiency and intention to seek information regarding COVID-19.

Findings: Results of the CFA showed that the expanded PRISM model had good model fit. Additionally, using …

Risks From Spacecraft Breakup Events In Near Rectilinear Halo Orbits, Nathan R. Boone, Robert A. Bettinger, Bryan D. Little

Faculty Publications

Spacecraft breakup events were simulated in the vicinity of the Lunar Gateway’s Near Rectilinear Halo Orbit to evaluate the risk of debris collision with the station. The Monte Carlo simulations model the breakup of an object shortly after deployment from the Gateway, and using the propagated trajectories of over a million particles across 5,000 random breakup events, the likelihood of collision with the Gateway is statistically evaluated. Approaches within 10 km were observed for only 2.4% of the breakup events, suggesting a low risk of collision, but approaches at larger distances that might still generate a debris avoidance maneuver were …

Comparison Of A Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Densities With Ionosondes And Firi, Dylan J. Shaver, Dong L. Wu, Nimalan Swarnalingam, Anthony L. Franz, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

High-frequency skywave propagation can be heavily impacted by D- and E-region dynamics requiring accurate global measurements to optimize performance. A standard measurement technique is to use ionosondes, but they are unable to measure below 1 MHz and are only available at a limited number of land-locked sites around the globe. In contrast, the Global Navigation Satellite System radio occultation (GNSS-RO) bottom-up method is a new approach specifically designed to generate electron density profiles in the D- and E- region ionosphere. It takes advantage of satellite constellations that currently provide over 20,000 daily measurements and global coverage. In this paper, GNSS-RO …

Ironnetinjector: Weaponizing .Net Dynamic Language Runtime Engines, Anthony J. Rose, Scott R. Graham, Jacob Krasnov

Faculty Publications

As adversaries evolve their Tactics, Techniques, and Procedures (TTPs) to stay ahead of defenders, Microsoft’s .NET Framework emerges as a common component found in the tradecraft of many contemporary Advanced Persistent Threats (APTs), whether through PowerShell or C#. Because of .NET’s ease of use and availability on every recent Windows system, it is at the forefront of modern TTPs and is a primary means of exploitation. This article considers the .NET Dynamic Language Runtime as an attack vector, and how APTs have utilized it for offensive purposes. The technique under scrutiny is Bring Your Own Interpreter (BYOI), which is the …

Reinvigorating Engineered Noise Controls: A Systems Approach, Jeremy Slagley, Adam Dudarewicz, Pawlaczyk-Łuszczyńska Małgorzata, Francis Slagley

Faculty Publications

Excerpt: Hearing loss is a major worldwide health issue affecting an estimated 1.5 billion people. Causes of hearing loss include genetics, chemicals, medications, lifestyle habits such as smoking, and noise. Noise is probably the largest contributing factor for hearing loss. Noise arises from the workplace, ambient environment, and leisure activities. The easiest noise sources to control are workplace and environmental. Workplace noise is unique in that the employer is responsible for the noise and the worker. Also, workers may be exposed to much higher levels of noise than they would accept elsewhere. Employers follow the traditional hierarchy of controls (substitution/engineering, …

Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette

Theses and Dissertations

With applications spanning myriad disciplines, Hadamard matrices have tremendous utility. Infinitely many have been discovered, but there is no general proof of their existence. Proving the Hadamard conjecture would provide a significant technological edge. Hadamard matrices are difficult to construct in general; however, they can be created directly from Legendre pairs (LPs). While LPs are not trivial to find, a breakthrough in this area would be pivotal in the quest to prove the Hadamard conjecture. Most recent efforts rely upon refined search algorithms, and we seek to either develop a better such algorithm or discover an altogether new theoretical construction. …

Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane

Theses and Dissertations

The modeling, simulation, and analysis of high energy laser propagation is a research topic of significant interest to the defense community. A detailed understanding of the phenomenon of thermal blooming is crucial as it is detrimental to the propagation of lasers over long distances and in the presence of aerosols. The simulation of thermal blooming has historically relied on wave optics models and scaling laws for the fluid response to the laser. Since thermal blooming occurs in the presence of natural convection, however, there is a need for simulating this coupled fluid-beam effect using a first principles approach. In this …

Advanced Statistical Methodology For The Modern Probability Of Detection, Christine E. Knott

Theses and Dissertations

Probability of detection (POD) is an invaluable part of the calculations used by the USAF to validate the capabilities of nondestructive inspection systems for detecting defects in critical structural components on aircraft. A POD study consists of a designed experiment, linear modeling, and a probability of detection verses defect size curve. This curve is useful for determining how often an aircraft should be re-inspected. Some POD studies are unsuccessful in creating realistic POD curves because the statistical modeling used has two common limitations: (1) a lack of convergence leading to no solution and, (2) violated assumptions leading to incorrect solutions. …

Numerical Simulation Of Nonlinear Wave Equations With Machine Learning, Kristina O. F. Williams

Theses and Dissertations

A machine learning procedure is proposed to create numerical schemes for solutions of certain types of nonlinear wave equations on coarse grids. This method trains stencil weights of a discretization of the equation, with the truncation error of the scheme as the objective function for training. A neural network is used as a model for the stencil weights. The method uses centered finite differences to initialize the optimization routine and a second-order implicit-explicit time solver as a framework. Symmetry conditions are enforced on the learned operator to ensure a stable method. The procedure is applied to the Korteweg - de …

Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum

Theses and Dissertations

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the …

Analysis Of Multi-Agent Routing Solution Methodologies Exploring A Mosaic Warfare Strategy, Stephen D. Donnel

Theses and Dissertations

Recognizing that communication between assets may be possible locally but not globally (e.g., due to disruptions to a communication network), Mosaic Warfare requires the movement and operation of multiple, dispersed assets in smaller groups (i.e., tiles), within which exist hierarchical, functional relationships between assets. This research first evaluates a heuristic for an enterprise of aerial assets comprised of airborne sensors, command and control, and strike aircraft seeking to move towards and destroy stationary targets. Next, we examine routing multiple assets of different types over a network to service demands in a collaborative manner, in that, when servicing a demand, …

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

Evaluating The Chief Of Staff Of The Air Force 2016 Initiative To Revitalize The Squadron: A Thematic Content Analysis Of Appreciative Inquiry Mechanisms, John M. Huntz

Theses and Dissertations

A thorough thematic analysis and literature review were undertaken to understand better the integration of AI mechanisms within the Revitalize the Squadron initiative. To facilitate the initiative's implementation, the aim is to provide commanders with practical instances, dimensions, findings, and results. Throughout the coding process, instances of AI’s mechanisms were discovered in the literature. The link between PE and HQR boosted the overall vitality within the squadron, where vitality was determined to be the goal. AI, as a whole, was not found in the literature, but the analysis determined that the Revitalize the Squadron initiative was “Appreciative” in nature.