Digital Commons Network^™

Comparison Of Anomaly Detection Methods On Event-Based Vision Sensor Data In A High Noise Environment, Will Johnston, Anthony L. Franz, Shannon R. Young, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter

Faculty Publications

Event-based vision sensors (EVSs) provide unique frequency analysis opportunities due to their event data output and high temporal resolution. Anomaly detection methods used in hyperspectral analysis can be used on the event frequency spectra to detect targets. However, the introduction of a strong, flickering interfering source can reduce the EVS sensitivity and obscure targets of interest. Previous work presented a method showing that targets could still be detected through an overwhelming source using frequency analysis, background suppression, and statistical filtering. This paper extends that research and compares the ability of five different eigenanalysis anomaly detection methods (principal component background suppression …

Designing Space-Based Architectures To Discover And Track Hazardous Asteroids Using Mo-Mcts, Adam P. Wilmer, Michael J. Klonowski, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

The discovery and tracking of near-Earth objects (NEOs), such as asteroids and comets, form the foundation of any effective planetary defense mitigation strategy—that is, the process of reducing or eliminating the threat these objects pose to humanity. Establishing sufficient warning time prior to a potential Earth impact is a critical outcome of this capability, as it enables informed decision-making and the selection of viable mitigation options. This study investigates how to optimally pre-position a fleet of NEO discovery and tracking (D&T) spacecraft within the Sun-Earth system. Candidate architectures—one or more pre-positioned spacecraft—are designed using Multi-Objective Monte Carlo Tree Search (MO-MCTS). …

Natural Convection Of Cuo-Water Nanofluid Flow Along A Vertical Plate With Variable Thermophysical Properties And Discrete Heat Sources, Nepal Roy, Ioan Pop, Rama Subba Reddy Gorla

Faculty Publications

Effects of discrete heat sources along a vertical plate are of practical importance due their occurrence in electronic devices. For growing demand of electronic appliances and their advancement, cooling processes of them must be improved. As usual fluids have limited heat transfer, nanofluids made by dispersing nanoparticles into them are utilized to enhance thermal performance. However, flow characteristics and heat transfer of a nanofluid for discrete heat sources along a vertical plate need to be explored. For this reason, this study analyzes the natural convective heat transfer and flow behaviors of CuO-water nanofluid induced by discrete heat sources along a …

Radiation Protection Factor Research: The Keystone For Conventional-Nuclear Integration (Cni), Andrew W. Decker

Faculty Publications

This article briefly describes Defense Threat Reduction Agency (DTRA) vehicle Radiation Protection Factor (RPF) research and explains its critical role in enabling future Operations in a Nuclear Environment (ONE) and Conventional-Nuclear Integration (CNI) on behalf of the US Department of War (DoW).1 As such, the background and practical utility of RPF values is discussed, as well as the justification for renewed Army and DoW investment into RPF research to enhance Joint military planning, survivability, and lethality on tomorrow’s nuclear battlefields. Advances in DTRA RPF research directly strengthen US strategic and extended deterrence efforts and support all Agencies and Departments responsible …

Afit Librarian Newsletter : Check It Out (Second Quarter 2026), D'Azzo Research Library, Air Force Institute Of Technology

AFIT Library Knowledge Base

In this issue:

• Interview with a Featured Library Advocate, Dr. William Cunningham, AFIT/ENS
• Library Display about “Inventing Flight”
• New Librarian: Catherine Stahl
• Staff Book Picks for Spring Reading

Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming

Faculty Publications

Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …

Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee

Faculty Publications

Manufacturers adopt different warranty strategies for remanufactured products, offering shorter, identical, or longer warranty periods compared to new products. However, prior research has only focused on manufacturers offering either shorter or identical warranties. In addition, the existing literature has not captured the diminishing returns of warranties, i.e., as the warranty coverage increases, its incremental benefits begin to decrease but the costs continue to increase. To address these gaps, we develop an optimization model that jointly considers pricing and warranty decisions while accounting for warranty’s diminishing effect on consumer’s willingness to pay for remanufactured products. We show that all three observed …

Improving Hydrogen Storage Kinetics Of Polymeric Composites Via Additions Of La0.6Ce0.4Ni5 And Carbon Particles, Muhammad M. Rahman, Fenil J. Desai, Ramazan Asmatulu, Md. Nizam Uddin, Karina Suarez-Alcantara

Faculty Publications

Nanostructured metal hydrides have garnered interest in their potential to store hydrogen safely and effectively as an energy carrier. By partially substituting lanthanum (La) with cerium (Ce), the structure of lanthanum pentanickel (LaNi₅) was maintained to create a novel encapsulated La–Ce–Ni-based metal hydride (La_0.6Ce_0.4Ni₅). The incorporation of metal-polymer composites can protect metal hydrides from oxidation and enhance cyclic stability. Carbon-based materials such as graphene and multi-walled carbon nanotubes (MWCNTs) not only store hydrogen but also improve the reaction kinetics and address thermal management issues. This study presents La_0.6Ce_0.4Ni …

Characterizing Atmospheric Turbulence With The Lunar Step Response Method, Patrick D. Carattini, Caleb J. Stilp, Katelyn M. Atkinson, Stephen C. Cain

Faculty Publications

Most methods that astronomers use to characterize the strength of atmospheric turbulence in and around their observatories use differential image motion monitors observing a star to provide the necessary data for the measurement. With the Moon becoming a greater national priority, the need to characterize atmospheric paths between observatories on Earth and the Moon is potentially going to grow in the future. To this end, the differential image motion monitor is not an ideal instrument for characterizing turbulence along paths between observatories and the Moon as the bright Moon makes it difficult to detect and locate stars in its vicinity. …

Transfer Learning Neural Networks For Nuclear Forensic Image Morphology Using Image Splitting Techniques, Niko A. Petrocelli, Lee C. Lambert, Brett J. Borghetti, Abigail A. Bickley

Faculty Publications

Manual morphological analysis of actinide particles from scanning electron microscope (SEM) imagery is a critical component of nuclear forensics but is prone to significant inter-analyst variability. To address this challenge, this work develops and evaluates an automated classification method using deep learning. We introduce a methodology based on partitioning 1906 SEM images, representing 13 classes of uranium compounds, into smaller patches for analysis. Three convolutional neural network (CNN) architectures of increasing complexity were compared: a custom baseline CNN, a simple transfer learning model using ResNet50v1, and a complex model featuring hierarchical feature extraction and a spatial attention mechanism built upon …

Rapid-Response Reconnaissance Architecture Design For Planetary Defense With Nested Trajectory Optimization, Adam P. Wilmer, Justin A. Atchison, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

Reconnaissance is a vital component in a comprehensive planetary defense mitigation strategy—aimed at preventing or reducing the impact threat posed by celestial objects on close-approach trajectories to Earth. It provides decision-makers with critical information on the physical and orbital properties of a near-Earth object (NEO), enabling better assessment of size, composition, and trajectory. This study investigates how to optimally pre-position a fleet of reconnaissance spacecraft prior to the discovery of a specific hazardous NEO. It evaluates response timelines and mission success rates for combinations of spacecraft launched from Earth and those maneuvering from pre-deployed locations within the Sun-Earth system. A …

Discovery Of Dynamical Structures Mapping Chaotic Transport Pathways In The Earth–Moon Cr3bp, Tyler J. Kapolka, Christina E. Paljug, Robert A. Bettinger, Rachel Oliver, Bruce A. Cox, Jeremiah A. Specht

Faculty Publications

Chaos; Deterministic chaos; Earth–Moon system; Poincaré map; Quasi-chaotic; Surface of section /// For the Circular Restricted 3-Body Problem (CR3BP), the topologies present within a Poincaré map enable the extraction of useful information regarding periodic, quasi-periodic, and chaotic trajectory behavior. Aside from the prominent topologies that follow distinct concentric patterns around fixed points, indicative of the periodic and quasi-periodic motion that is often the central focus of CR3BP research, there are also many “dusty” regions on the Poincaré map that appear random without an apparent structure and are indicative of chaotic motion. This paper, for the first time in literature, identifies …

Afit By The Numbers, Fy25, Air Force Institute Of Technology

AFIT Documents

AFIT’s mission is to educate defense professionals to innovatively accomplish the deterrence and warfighting missions of the USAF and USSF. AFIT’s vision of leading defense-focused education, research and consultation to accelerate military superiority across all domains is accomplished through operationally relevant advanced academic education, research, and professional continuing education.

Spline-Based Factor-Graph Optimization With High-Grade Inertial Sensors, Kyle Leland, Clark N. Taylor, David Woodburn, Randal Beard

Faculty Publications

Inertial measurement units (IMUs) are central to global navigation satellite system-based and alternative navigation solutions. This paper combines three lines of research to explore a novel methodology for using inertial sensors: factor graphs, spline-based trajectory estimation, and high-grade inertial sensing. Spline-based factor-graph trajectory estimation is increasingly used in the literature, especially for asynchronous or high-rate sensors. However, prior models neglect the impact of the Earth’s rotation, which is significant for high-grade IMUs. We extend spline-based factor graphs to incorporate accelerometer and gyroscope models that account for the Earth’s rotation. We apply this approach to simulated data from high-grade inertial sensors …

Proposed Methodology For Correcting Fourier-Transform Infrared Spectroscopy Field-Of-View Scene-Change Artifacts, Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectrometers are widely used for spectral measurements. Changes in the field of view during measurement introduce oscillations into the measured spectra known as scene-change artifacts. Field-of-view changes also introduce uncertainty about which target the measured spectrum represents. Though scene-change artifacts are often present in dynamic data, their significance is disputed in the current literature. This work presents a theoretical framework and experimental validation for scene-change artifacts. Field-of-view changes introduce variable interferogram offsets, which standard processing techniques assume are constant. The error between the interferogram offset and its estimate is Fourier-transformed, yielding scene-change artifacts, often confused with noise, in the …

Large-Scale Cubesat Chassis, Matthew D. Evans, Robert A. Bettinger

AFIT Patents

The present invention relates to large-scale CubeSat chassis and methods of making and using same. The disclosed CubeSat comprises specific structural features that can yield up to at least a 27 U CubeSat that has comparable or even better performance and benefits than that of smaller CubeSats. Such volume increase coupled with the structural integrity of Applicants' CubeSats opens up a wide range of CubeSat performance increases including, but not limited to, larger payloads, more diverse payloads and larger CubeSat fuel capacities. Such increased payload capabilities includes, for example, increased focal length capabilities and such improved maneuverability results in, for …

Amp: Single-Shot Ultra-Wide Fisheye-To-Cubemap Pnp Pose Estimation, Ryan M. Raettig, Richard R. Nyquist, Scott L. Nykl, Clark N. Taylor, Christine M. Schubert Kabban

Faculty Publications

Estimating the position and orientation of a rigid object from an image is critical for situational awareness in robotics and autonomous systems. This study explores relative pose estimation using an ultra-wide fisheye camera for unmanned aircraft inspection vehicles. Ultra-wide fisheye lenses introduce radial distortion and capture features beyond the rectilinear image plane, rendering rectilinear Perspective-n-Point (PnP) algorithms inadequate. Designing a bespoke ultra-wide fisheye localization algorithm requires consideration of both the feature detection method and the pose estimator itself. This study proposes a novel method that combines (1) a fisheye-to-cubemap reprojection, (2) a You Only Look Once (YOLO) convolutional neural network …

Articulating Spacecraft Chassis, Christian T. Conkle, Robert A. Bettinger, Philip D. Smith

AFIT Patents

The present invention relates to articulating spacecraft chassis and methods of making and using same. The present invention relates to spacecraft chassis and methods of making and using same. Such spacecraft chassis have a dynamic movement capability that allows the spacecraft to alter its structure while still maintaining industry volumetric launch standards. This capability increases opens up a wide range of achievable volumetric states and increases the ability to meet mission requirements by introducing a new tunable parameter. In addition, the judicious selection of certain dynamic movement parameters can result increased payload capabilities and improved maneuverability.

Investigation Of The Flow Field Morphology Of Film Cooling In Supersonic Flow, Umberto Sandri, Massimiliano Ferro, Alessio Picchi, Antonio Andreini, Bruno Facchini, Marc D. Polanka

Faculty Publications

Film cooling is widely implemented in highly thermally stressed gas turbine components. Its performance has been extensively investigated for several decades and many results are available in the literature. In conventional gas turbines, regions of supersonic flow are not prevalent and should generally be avoided. For this reason, results relative to film cooling in supersonic flow are limited. Nevertheless, a new interest related to Rotating Detonation Combustors (RDC) and supersonic turbines is growing. The implementation of those engine components in a gas turbine is likely to need film cooling for thermal protection. In this context, it becomes crucial to gain …

Statistical Overview Of Long-Lived Active Regions Observed Across Multiple Carrington Rotations, Emily I. Mason, Kara L. Kniezewski

Student Publications

The study of solar active regions (ARs) is of central importance to a range of fundamental science, as well as the practical applications of space weather. Active region emergence and life cycles are two areas of particular interest, yet the lack of consistent full-Sun observations has made long-term studies of active regions difficult. Here, we present results from a study to identify and characterize long-lived active regions (LLARs), defined as those which were observed during at least two consecutive Carrington rotations and which did not undergo significant successive flux emergence once the decay phase began. Such active regions accounted for …

Air Force Institute Of Technology Research Report 2023, Air Force Institute Of Technology

AFIT Documents

This report summarizes the research activities of the Air Force Institute of Technology's Graduate School of Engineering and the Graduate School of Logistics and Acquisition Management. It describes research interests and faculty expertise; list student theses/dissertations; identifies research sponsors and contributions; and outlines the procedure for contacting either school.

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Gaber, Mohamed Abdelraheem

Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

Preliminary Investigation Of Cislunar Disposal Reachability Via Electric Propulsion For Selected L2 Lagrange Point Orbit Families, Ryan M. Sargent, Robert A. Bettinger, Carl R. Hartsfield

Faculty Publications

This paper investigates the disposal of end-of-life spacecraft from selected orbit families in the Earth-Moon system, specifically the L₂ Lyapunov and Halo families. Rather than focusing on impulsive burns with chemical propulsion systems, this paper examines disposal using continuous thrust generated by Hall thrusters, a form of electric propulsion. Leveraging the Circular Restricted Three Body Problem (CR3BP) as the dynamical framework, various levels of ΔV are evaluated in single-maximum burn and multiple-burn concepts of operation to evaluate the potential for spacecraft minimizing their transit of cislunar space and reaching the Earth’s gravitational sphere of influence in order to enter …

Applying Machine Learning Methods To Laser Acceleration Of Protons: Synthetic Data For Exploring The High Repetition Rate Regime, John J. Felice, Ronak Desai, Nathaniel Tamminga, Joseph R. Smith, Alona Kryshchenko, Christopher M. Orban, Michael L. Dexter, Anil K. Patnaik

Faculty Publications

Advances in ultra‐intense laser technology have increased repetition rates and average power for chirped‐pulse laser systems, which offer a promising solution for many applications including energetic proton sources. An important challenge is the need to optimize and control the proton source by varying some of the many degrees of freedom inherent to the laser‐plasma interactions. Machine learning can play an important role in this task, as our work examines. Building on our earlier work in Desai et al. 2024, we generate a large ∼1.5 million data point synthetic data set for proton acceleration using a physics‐informed analytic model that we …

Intrinsic Defects (Vacancies And Antisites) In Neutron Irradiated Cdsip2 Crystals, Timothy D. Gustafson, Elizabeth M. Scherrer, Nancy C. Giles, Kevin T. Zawilski, Peter G. Schunemann, Jonathan E. Slagle, Kent L. Averett, Larry E. Halliburton

Faculty Publications

Cadmium silicon phosphide (CdSiP₂) is a nonlinear optical material widely used in optical parametric oscillators. Intrinsic defects (vacancies and antisites) are responsible for unwanted broad optical absorption bands in these crystals that degrade the performance of the devices. In the present work, optical absorption and electron paramagnetic resonance (EPR) spectra are acquired (at room temperature and 12 K, respectively) from a neutron-irradiated CdSiP₂ crystal. After the irradiation, the crystal is highly absorbing from the band edge near 600 nm to beyond 1.3 μm because of overlapping defect-related absorption bands. Heating to 550 °C removes nearly all the …

Authenticating Electronic Devices Via Multi Tone Analysis, Carl Bohman Jr., Aaron Jennings, Christian Eakins, Mark B. Skouson, Richard Ott, Jamin Mccue

AFIT Patents

Methods and systems for authenticating electronic devices via multi tone analysis. A method for authenticating a device under test (DUT) of a type of DUT includes imparting voltage tones to the DUT. The voltage tones are proximate a frequency of interest that is associated with the type of DUT. Using a measurement response of the DUT to the voltage tones, an electronic signature of the DUT is determined. The DUT is determined to be authentic when the electronic signature of the DUT substantially matches an electronic signature of an authority DUT of the type of DUT.

Afit Librarian Newsletter : Check It Out (Fourth Quarter 2025), D'Azzo Research Library, Air Force Institute Of Technology

AFIT Library Knowledge Base

No abstract provided.

An Event-Based Time-Incremented Snn Architecture Supporting Energy-Efficient Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Recent advances in Radio Frequency (RF)-based device classification have shown promise in enabling secure and efficient wireless communications. However, the energy efficiency and low-latency processing capabilities of neuromorphic computing have yet to be fully leveraged in this domain. This paper is a first step toward enabling an end-to-end neuromorphic system for RF device classification, specifically supporting development of a neuromorphic classifier that enforces temporal causality without requiring non-neuromorphic classifier pre-training. This Spiking Neural Network (SNN) classifier streamlines the development of an end-to-end neuromorphic device classification system, further expanding the energy efficiency gains of neuromorphic processing to the realm of RF …

Occulation Observations With Event-Based Vision Sensors [ Poster ], Rachel Oliver, Paul Rickerhauser, Brian Mcreynolds

Faculty Publications

Event-based vision sensors (EVS) offer exceptional change detection capabilities due to their asynchronous and independent pixels which record binary events with changes in their photocurrent. The resulting address event representation data is a sparse timeseries list.

Microarchitectural Malware Detection Via Translation Lookaside Buffer (Tlb) Events, Cristian Agredo, Daniel F. Koranek, Christine M. Schubert Kabban, Jose R. Gutierrez Del Arroyo, Scott R. Graham

Faculty Publications

Prior work has shown that Translation Lookaside Buffer (TLB) data contains valuable behavioral information. Many existing methodologies rely on timing features or focus solely on workload classification. In this study, we propose a novel approach to malware classification using only TLB-related Hardware Performance Counters (HPCs), explicitly excluding any dependence on timing features such as task execution duration or memory access timing. Our methodology evaluates whether TLB data alone, without any timing information, can effectively distinguish between malicious and benign programs. We test this across three classification scenarios: (1) A binary classification problem involving distinguishing malicious from benign tasks, (2) a …