Physical Sciences and Mathematics Commons^™

Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine

Faculty Publications

The authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or …

Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv

Faculty Publications

We design, build, and validate an optical system for generating light beams with complex spatial coherence properties in real time. Beams of this type self-focus and are resistant to turbulence degradation, making them potentially useful in applications such as optical communications. We begin with a general theoretical analysis of our proposed design. Our approach starts by generating a Schell-model (uniformly correlated or shift-invariant) source by spatially filtering incoherent light. We then pass this light through an optical coordinate transformer, which converts the Schell-model source into a nonuniformly correlated field. After the general analysis, we discuss system engineering, including trade-offs among …

Innovation Challenges In The Air Force Sbir Program: From The Small Businesses' Perspective, Hart J. Holt, Amy M. Cox, Scott Drylie, David S. Long, Alfred E. Thal Jr., Robert D. Fass

Faculty Publications

Every year the United States invests $3.2 billion in the Small Business Innovation Research (SBIR) program to promote innovation among the nation’s small businesses. Half of this investment is from the DoD. This research considers the challenges faced by small businesses innovating with the DoD, particularly those awarded SBIR contracts with the United States Air Force. The authors surveyed 286 unique small businesses that were previously awarded an Air Force SBIR contract. By asking the survey respondents open-ended questions and categorizing their responses, they pinpoint unaddressed challenges from the small business perspective. By categorizing survey responses through Qualitative Content Analysis, …

The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe

Faculty Publications

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset …

Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose, Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau

Faculty Publications

The ongoing evolution of malware presents a formidable challenge to cybersecurity: identifying unknown threats. Traditional detection methods, such as signatures and various forms of static analysis, inherently lag behind these evolving threats. This research introduces a novel approach to malware detection by leveraging the robust statistical capabilities of L-moments and the structural insights provided by Abstract Syntax Trees (ASTs) and applying them to PowerShell. L-moments, recognized for their resilience to outliers and adaptability to diverse distributional shapes, are extracted from network analysis measures like degree centrality, betweenness centrality, and closeness centrality of ASTs. These measures provide a detailed structural representation …

Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams

Faculty Publications

A numerical method for evolving the nonlinear Schrödinger equation on a coarse spatial grid is developed. This trains a neural network to generate the optimal stencil weights to discretize the second derivative of solutions to the nonlinear Schrödinger equation. The neural network is embedded in a symmetric matrix to control the scheme’s eigenvalues, ensuring stability. The machine-learned method can outperform both its parent finite difference method and a Fourier spectral method. The trained scheme has the same asymptotic operation cost as its parent finite difference method after training. Unlike traditional methods, the performance depends on how close the initial data …

Advancing Robust Autonomous System Localization: Labeling Optimizations For Convolutional Neural Networks, Jeffrey L. Choate

Theses and Dissertations

AAR is increasingly critical as aircraft autonomy advances, particularly for the Global Strike mission of the USAF, enhancing operational range and endurance. Traditional methods relying on GPS and custom communication links are limited in GPS-denied environments. This dissertation advances a single camera method to estimate object pose across three interconnected studies. The system trains a CNN on synthetic imagery to predict bboxes for object components, Solve-PnP algorithm finds the 6DoF pose, then employs novel pseudo-labeling on real-world images. These findings are pivotal for the AAR community and contribute to robotics, computer vision, and CNN research. By enabling robust GPS-free autonomous …

Integrating Blockchain Technology Into The Software Development Life Cycle To Satisfy The Software Bill Of Materials Requirement For Government Software Systems, Walter T. Scott Ii

Theses and Dissertations

This thesis explores the integration of Blockchain Technology (BT) into the Software Development Life Cycle (SDLC) to satisfy the Software Bill of Materials (SBOM) requirement for government software systems. This study begins by synthesizing a standard SDLC definition from various government and industry references, which may provide the foundation for future efforts to standardize software development practices across the government software development community. This study proceeds to define working definitions for the software supply chain (SSC) and software supply chain management (SCM) before introducing and detailing the SBOM requirement as well as providing an overview of prior research regarding SBOMs …

Generation And Implementation Of Mixed Radiation From Laser Interactions On A Liquid Target, Benjamin M. Knight

Theses and Dissertations

The simultaneous generation of different forms of radiation from the same source is highly desirable but technically challenging. We present the generation of D-D fusion neutrons and >MeV-energy x-rays from extreme intensity (∼ 10¹⁹ W/cm² ), high repetition-rate (1 kHz) laser pulses on a thin liquid target. Total neutron fluxes of ∼ 105 neutrons/s and x-ray exposure rates up to ∼ 200 R/hr at 74 cm are measured. Evidence of D-D fusion is verified with a measurement suite including three independent neutron detection systems: an EJ-309 organic scintillator, a ³He proportional counter, and a set of 36 …

Collisional And Spatial Characterization Of Electron Broadening In Rubidium Vapor, Jordan C. Mindrup

Theses and Dissertations

Stark broadening of the 4²D → 12²F transition of rubidium is examined in a rubidium vapor cell with modulated double pump-probe spectroscopy at helium pressures of 0.001 Torr, 3.0 Torr, and 30.0 Torr. A pressure dependent critical rubidium number density was observed after which the presence of electrons becomes dominant. It is observed that after the rubidium density threshold, a linear relationship is seen between rubidium number density and the Stark broadened width of the line shapes, with a slope of 0.079 ± 0.002, 0.18 ± 0.01, and 0.9 ± 0.1 for helium pressures of 0.001 …

Machine Visual Perception For Autonomous Docking Maneuvers, Derek B. Worth

Theses and Dissertations

This dissertation presents a novel approach to autonomous docking using machine learning for visual perception, particularly during probe and drogue aerial refueling. Autonomous vehicles have become pervasive in both civilian and defense sectors, and their ability to interact with their surroundings and each other autonomously is critical for future operations. Traditional methods relying on signals or inertial sensors face significant limitations such as interference, jamming, and drift. This research focuses on developing a computer vision-based solution to overcome these limitations. A novel pipeline, termed relative vectoring, is introduced, which utilizes dual object detection and machine learning to estimate relative positions …

Investigating Temperature And Emissivity Separation Techniques Through The Use Of A Spectral Emissivity Database, Mitchell A. Manzardo

Theses and Dissertations

This study evaluates two temperature and emissivity separation techniques using data from an ABB MR304 FTIR and a Telops Mid-Wave Hyper-Cam on carbon-based samples heated by a high-energy laser. The established Linear Spectral Emissivity Constraint (LSEC) and Gray Body Emissivity (GBE) methods, as well as a new Robust Ratio Linear Fitting (RRF) method are assessed for their applicability in controlled lab environments. A spectral emissivity database aids in analyzing method performance. The RRF method shows promise but has limitations, particularly with low-temperature data and complex Hyper-Cam data. Despite these challenges, the RRF method offers potential for further refinement.

Estimating Dis Performance Using Mininet, Ryan D. Winz

Theses and Dissertations

Real time distributed simulation is an exceptionally useful tool for training and wargaming used by the military and industry alike. This research aims to provide scenarios and structures to evaluate the effect of distributing simulations among different compute nodes. Specific scenarios involve the analysis of performance as a function of latency and the degree network protocols and reliability affect simulation performance. Various standards exist for administering geographically separated simulations. The focus of this thesis will be on the Distributed Interactive Simulation standard, a peer-to-peer open standard for simulation messages to adhere to, but lessons can be extended to other standards.

Twisted Spatiotemporal Optical Vortex Beams In Dispersive Media, Milo W. Hyde Iv

Faculty Publications

We derive a closed-form expression for the mutual coherence function (MCF) of a twisted spatiotemporal optical vortex (STOV) beam after propagating a distance in a linear dispersive medium. A twisted STOV beam is a partially coherent optical field that possesses a coherent STOV and a stochastic twist coupling its space and time dimensions. These beams belong to a special class of space–time-coupled light fields that carry transverse (to the direction of propagation) orbital angular momentum, making them potentially useful in numerous applications including quantum optics, optical manipulation, and optical communications. After presenting the derivation, we validate our new general MCF …

Autonomous Experimentation For Accelerated Calibration Of Fused Deposition Modeling 3d Printers, Graig S. Ganitano

Theses and Dissertations

Additive Manufacturing (AM), also known as 3D printing, has emerged as a key component of Industry 4.0, enabling reduced cost, quick production, greater sustainability, and increased design complexity compared to its traditional manufacturing counterpart. Currently, Fused Deposition Modeling (FDM) technology dominates the AM market with respect to the number of 3D printers in use. However, the FDM process is sensitive to changes in system configuration, especially the feedstock material. Utilizing a new feedstock requires a time-consuming trial-and-error process to identify optimal settings for a large number of process parameters, acting as a barrier to the technology.

To enable greater accessibility …

Open-Loop Wavefront Sensing In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers

Faculty Publications

In this paper, we show that speckle averaging helps to reduce the measurement error associated with a Shack–Hartmann wavefront sensor (SHWFS); however, this reduction is rendered ineffective with increasing beacon anisoplanatism. We do so operating in a weak-scintillation regime, where the SHWFS offers robust performance, and using in-plane translation of the illuminated rough surface to accomplish frame-to-frame speckle diversity. Understanding these trade-space limitations is critical when performing wavefront sensing with noncooperative, extended-source beacons.

Strength Measurement Of The E_Α^Lab = 830 Kev Resonance In The Ne 22 ( Α , N ) Mg 25 Reaction Using A Stilbene Detector, Shahina S., R. J. Deboer, J. Gorres, R. Fang, Michael T. Febbraro, R. Kelmar, M. Matney, K. Manukyan, J. T. Nattress, E. Robles, T. J. Rutland, T. T. King, A. Sanchez, R. S. Sidhu, E. Stech, M. Wiescher

Faculty Publications

The interplay between the ²²Ne (��,��)²⁶Mg reaction and the competing ²²Ne(��,��)²⁵Mg reaction determines the efficiency of the latter as a neutron source at the temperatures of stellar helium burning. In both cases, the rates are dominated by the ��-cluster resonance at 830 keV. This resonance plays a particularly important role in determining the strength of the neutron flux for both the weak and main �� process as well as the �� process. Recent experimental studies based on transfer reactions suggest that the neutron and ��-ray strengths for this resonance are approximately equal. In this …

Testing Of An Organic Metal Halide Perovskite For Fast Neutron Detection, Wyatt Panaccione, Zhifang Shi, Praneeth Kandlakunta, Taylor M. Nichols, Susan White, Jinsong Huang, Lei R. Cao

Student Publications

In this work, we synthesized and characterized the Methylhydrazinium Lead Trichloride MHyPbCl₃(CH₃NH₂NH₂PbCl₃) perovskite as a fast neutron detector. The high hydrogen density of MHyPbCl3 enables efficient energy conversion from a fast neutron into a recoiled proton through the 1H(n,n)1H elastic scattering interaction, thereby, allowing for direct charge detection. Through IV characterization and X-Ray excitation, the crystal demonstrated a high resistivity at 4.43E11 ω cm and a good mobility-lifetime product (μτ) of 9.1E-3 ^cm2/_V respectively, under C₆₀/BCP/Cu and Au contact configuration to form an ohmic-ohmic …

An Integrated Space Test Lexicon: A Taxonomy For The Integrated Test And Evaluation Of Space Systems, Stephen K. Tullino, Andrew S. Keys, Robert A. Bettinger, Amy M. Cox, David R. Jacques

Faculty Publications

The proposed Integrated Space Test Lexicon is intended to amalgamate the numerous definitions of integrated (IT or IT&E), development test (DT or DT&E), and operational test (OT or OT&E) into unified, service-wide definitions, aligned with the Space Test Enterprise Vision. Refining such definitions will help distill the core characteristics of these fundamental test types to first identify space system activities composing what is traditionally known as DT and OT, then to provide a means of how these activities fit into the IT paradigm and support space system development. In forging a common understanding of how DT and OT support space …

Phase Error Scaling Law In Two-Wavelength Adaptive Optics, Milo W. Hyde Iv, Matthew Kalensky, Michael J. Spencer

Faculty Publications

We derive a simple, physical, closed-form expression for the optical-path difference (OPD) of a two-wavelength adaptive-optics (AO) system. Starting from Hogge and Butts’ classic OPD variance integral expression, we apply Mellin transform techniques to obtain series and asymptotic solutions to the integral. For realistic two-wavelength AO systems, the former converges slowly and has limited utility. The latter, on the other hand, is a simple formula in terms of the separation between the AO sensing (i.e., the beacon) and compensation (or observation) wavelengths. We validate this formula by comparing it to the OPD variances obtained from the aforementioned series and direct …

Impact Of Operational Ladar Occlusions On Point Cloud Instance Segmentation, Andrew D. Gibson

Theses and Dissertations

Data exploitation techniques are the enabler for technological advancements in military ISR applications of ladar ISR. By identifying instances of military objects in observed scenes, point cloud deep learning models can unlock new standards of real-time information delivery to warfighters. Although current deep learning training datasets do not include real-world collection occlusions consistent with military applications, this research characterizes SPT model performance by adding occlusions to the DALESObjects dataset via artificial flyby simulations.We find that a baseline model trained on unoccluded data suffers performance degradation on both semantic and instance segmentation tasks when evaluated on occluded data, but that the …

Collisional Broadening And Shift Of Rubidium 42D5/2 → N2F Line Shapes With Helium And Electrons, Dillon T. Nice

Theses and Dissertations

Line shapes for three rubidium 4²D_5/2 → n²F transitions were collected using pump probe spectroscopy. Broadening rates for Rb-He collisions ranged from 139–171 MHz/Torr and shift rates ranged from 113–146 MHz/Torr. Then, line shapes were collected at different alkali densities to measure electron density. Electron density had a clear “runaway ionization density threshold” around 1.5×10¹³ cm⁻³. The three transitions agreed within 2% on the observed fractional ionization when calculated using the observed Stark width but did not agree on the observed fractional ionization when calculated using the observed Stark shift. These results …

Remote Profiling Of Atmospheric Turbulence: Enhanced Resolution With Stacked Rayleigh Beacons In Tardis, Benjamin C. Wilson

Theses and Dissertations

A stacked beacon turbulence profiling methodology has been introduced and applied to have increased profiling on the Turbulence and Aerosol Research and Investigation System (TARDIS). The model was derived and demonstrated the applicability through discussion on data processing and inversion processes. The methodology was applied for two different nighttime experiments, one in Summer and one in Fall. C 2 n profiles were derived into the 1300 m altitude ranges for both nights and the summer experiment was compared to a co-located DELTA Sky measurements and LEEDR generated Climatological profiles. The comparison implied promise in the methodology with additional work needed …

Exporting Sysml Designs To Simulink, Drew Q. Broadbent

Theses and Dissertations

Various software systems have been developed to aid a systems engineer in evaluating system requirements, such as Dassault’s Magic System of Systems Architect (MSOSA) and MathWorks’ Simulink. Both software packages have different strengths; therefore, it is beneficial to export models from one software package to another. MSOSA provides a built-in tool that facilitates this transfer, built upon the Extension for Physical Interaction and Signal Flow Simulation (SysPhS) standard. However, the process is often unreliable and error prone and online documentation is largely lacking. This research used extensive trial and error to fill in the documentation gaps and create a method …

Improving 2–5 Qubit Quantum Phase Estimation Circuits Using Machine Learning, Charles Woodrum, Torrey J. Wagner, David E. Weeks

Faculty Publications

Quantum computing has the potential to solve problems that are currently intractable to classical computers with algorithms like Quantum Phase Estimation (QPE); however, noise significantly hinders the performance of today’s quantum computers. Machine learning has the potential to improve the performance of QPE algorithms, especially in the presence of noise. In this work, QPE circuits were simulated with varying levels of depolarizing noise to generate datasets of QPE output. In each case, the phase being estimated was generated with a phase gate, and each circuit modeled was defined by a randomly selected phase. The model accuracy, prediction speed, overfitting level …

Analysis Of Modeled 3d Solar Magnetic Field During 30 X/M-Class Solar Flares, Seth H. Garland, Vasyl B. Yurchyshyn, Robert D. Loper, Benjamin F. Akers, Daniel J. Emmons Ii

Faculty Publications

Using non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |B_z|≥ 300 G (active region—AR) and areas above the photosphere with the …

Quantification Of Surface Layer Turbulence Using Sensible Heat Values From Energy Balance Versus Aerodynamic Methods, Steven T. Fiorino, Yogendra Raut, Jaclyn Schmidt, Laura Slabaugh, Blaine Fourman, Jack E. Mccrae, Benjamin C. Wilson, Santasri R. Bose-Pillai

Faculty Publications

Surface layer optical turbulence values in the form of the refractive index structure function C_n^2 are often calculated from surface layer temperature, moisture, and wind characteristics and compared to measurements from sonic anemometers, differential temperature sensors, and imaging systems. A key derived component needed in the surface layer turbulence calculations is the sensible heat value. Typically, the sensible heat is calculated using the bulk aerodynamic method that assumes a certain surface roughness and a friction velocity that approximates the turbulence drag on temperature and moisture mixing from the change in the average surface layer vertical wind velocity. These assumptions/approximations generally …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Investigating Turbulence Distribution In The Lower Atmosphere Using Time-Lapse Imagery From A Camera Bank, Benjamin C. Wilson, Santasri R. Bose-Pillai, Jack E. Mccrae, Steven T. Fiorino, Robert P. Freeman, Laura R. Slabaugh

Faculty Publications

The atmosphere’s surface layer (first 50–100 m above the ground) is extremely dynamic and is influenced by surface radiative properties, roughness, and atmospheric stability. Understanding the distribution of turbulence in the surface layer is critical to many applications, such as directed energy and free space optical communications. Several measurement campaigns in the past have relied on weather balloons or sonic detection and ranging (SODAR) to measure turbulence up to the atmospheric boundary layer. However, these campaigns had limited measurements near the surface. We have developed a time-lapse imaging technique to profile atmospheric turbulence from turbulence-induced differential motion or tilts between …

Deep Selenium Donors In Zngep2 Crystals: An Electron Paramagnetic Resonance Study Of A Nonlinear Optical Material, Timothy D. Gustafson, Larry E. Halliburton, Nancy C. Giles, Peter G. Schunemann, Kevin T. Zawilski, J. Jesenovec, Kent L. Averett, Jonathan E. Slagle [*]

Faculty Publications

Zinc germanium diphosphide (ZnGeP₂) is a ternary semiconductor best known for its nonlinear optical properties. A primary application is optical parametric oscillators operating in the mid-infrared region. Controlled donor doping provides a method to minimize the acceptor-related absorption bands that limit the output power of these devices. In the present study, a ZnGeP₂ crystal is doped with selenium during growth. Selenium substitutes for phosphorus and serves as a deep donor. Significant concentrations of native defects (zinc vacancies, germanium-on-zinc antisites, and phosphorous vacancies) are also present in the crystal. Electron paramagnetic resonance (EPR) is used to establish the …