Engineering Commons^™

Distinguishing Auroral-E And Sporadic-E In Gnss Radio Occultation Measurements, Sharjeel Hyder, Jeffrey M. Holmes, Kyle E. Fitch, Kyle D. Roberts, Also: Themens, David R.; Emmons, Daniel J., Nimalan Swarnalingam, Dong L. Wu, Cornelius C. J. H. Salinas, David R. Themens, Daniel J. Emmons

Faculty Publications

GNSS radio occultation (RO) is widely used to detect metallic-ion sporadic-E layers on a global scale, but in auroral environments, particle precipitation-driven ionization can produce auroral-E structures with similar RO signatures. This overlap complicates reliable identification of sporadic-E and may bias high-latitude occurrence rate estimates. In this study, we quantify auroral contamination in RO-based sporadic-E detection and evaluate the performance of both threshold-based and multivariate classifier approaches. A dataset of 106 conjunction events was constructed using RO observations from the Spire and COSMIC-1 constellations, together with co-located ionosonde and magnetometer measurements at two high-latitude sites and an ionosonde at a …

Incorporating Advanced New Or Recycled Materials In Reinforced Concrete Structures, Ayman El-Zohairy, Antonio Caggiano

Faculty Publications

No abstract provided.

A Nonlinear Viscoelastic 3d Bellows Microspring Fabricated With Two-Photon Polymerization, Harris J. Hall, Tyler Grunzke, Samuel Campbell, Hengky Chandrahalim

Faculty Publications

In the past decade, two-photon polymerization (TPP) based 3D printing has gained popularity for prototype fabrication of micro and nanoscale structures and mechanical metamaterials. However, practical considerations including response uniformity, nonlinear behaviors, and material aging effects remain challenges for device maturation and are seldom reported. In this work, a pair of cylindrical microscale bellows springs (~ 100 μm diameter), fabricated with a commercial TPP 3D printer, are shown to exhibit nonlinear stiffness profiles under compression (up to ~ 7%), with distinct linear and nonlinear regions, that change significantly after ~ 9–10 months of open air exposure in ambient lab conditions. …

Complementary Thermodynamic Mechanisms Of Boron And Carbon Segregation At Grain Boundaries In Nickel Alloys, Tyler D. Dolezal, Rodrigo Freitas, Ju Li

Faculty Publications

Grain boundary stabilization by light interstitials is central to the performance of Ni-based superalloys, yet the thermodynamic mechanisms governing their interactions with substitutional chemistry remain poorly resolved. Here, we use hybrid Monte Carlo molecular dynamics simulations to quantify how boron and carbon modify the thermodynamic, structural, and chemical ordering of grain boundaries in Ni-Cr alloys. By analyzing interfacial state variables, site-resolved segregation spectra, local chemical ordering, and structural evolution, we show that boron and carbon stabilize grain boundaries through complementary pathways. Carbon drives saturation-controlled stabilization by recruiting Cr and conditioning boundary chemistry, while suppressing temperature-driven structural transformations of the boundary. …

Vehicle Detection And Classification With Compact Sensor Technologies And Convolutional Neural Networks, Jessy Wu, Brett J. Borghetti, Anthony L. Franz, Darren E. Holland, Abigail A. Bickley

Faculty Publications

Unattended ground sensors (UGSs) are passive systems used to detect and classify nearby activity such as the movement of military vehicles or personnel. However, UGS performance is limited in complex environments. This work explores the application of deep learning to classify vehicles as either ‘heavy’ or ‘light’ using seismic, acoustic, and magnetic sensor data collected at varying distances from a road. Two approaches were evaluated: one using features from Short-Time Fourier Transforms (STFTs), and another using convolutional neural networks trained on time series data. Models were also tested under data partitioning strategies involving either spatial or temporal variation. Data fusion …

Application Of Machine Learning To Discover Dynamical Structures In 4d Poincaré Maps In The Circular Restricted Three-Body Problem, Kevin M. Trigg, Daniel J. Broyles, Robert A. Bettinger, Tyler J. Kapolka

Faculty Publications

The spatial Circular Restricted Three-Body Problem (CR3BP) produces complex orbital dynamics that are difficult to classify at scale using traditional, manual Poincaré map analysis. A Poincaré map simplifies continuous orbital motion by recording the points where a trajectory intersects a chosen surface in phase space, converting a continuous path into a discrete set of crossings that reveal underlying topological structure. These crossings make it easier to characterize trajectory behavior, but interpreting them visually becomes impractical for large datasets and as Poincaré maps evolve from two into four dimensions. To address this challenge, an unsupervised clustering pipeline for discovering dynamical structures …

Enhancing The Bearing Capacity And Settlement Performance Of Soft Clay Using Geocell Reinforcement: A 3d Numerical Parametric Study, Alaa Ata, Engy E. Elbasuny, Ayman Metodiev El-Zohairy, Marwa Nabil

Faculty Publications

Problematic soils pose a risk to structures due to excessive or uneven settlement, swelling, and limited bearing capacity. To address some of these issues, mechanical reinforcement using geosynthetic products such as geocells can be employed, given their ease and speed of implementation. The purpose of this study was to assess the impact of geocells on the behavior of soft clay soil in Port Said, Egypt, using a three-dimensional finite element model, namely, the PLAXIS 3D software. The results show that replacing the top 1.5 m of the soft clay with sand significantly reduced settlement. This improvement was further enhanced by …

The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban

Faculty Publications

Nondestructive evaluation (NDE) methods are powerful tools for detecting and characterizing flaws in structural components, but their reliability must be evaluated before they can be used in critical applications. For more than 50 years, probabilistic and statistical methods have been used effectively to estimate reliability by describing an NDE system’s Probability of Detection (POD) for flaws of realistic sizes. The POD methods used by the USAF and NASA, like Hit/Miss, Signal-Response (â vs. a), and Point Estimate method (PEM, a.k.a. 29/29) have evolved, alongside newer approaches like Limited Sample POD (LS-POD) method, and Model Assisted Probability of Detection …

Finite-Time Braiding Dynamics Within Topological Nanowire Qubits, Adrian D. Scheppe, Michael V. Pak

Faculty Publications

Topological quantum computing has largely evolved toward a paradigm of manipulating edge-localized Majorana within p-wave topological superconducting nanowires. To bridge the gap between physical qubit systems and quantum algorithms, we perform a dynamical analysis to extend what is known in the adiabatic regime, providing time-dependent gate elements for further qubit and algorithm modeling efforts. Our analysis covers dynamical considerations for two methods of shuttling domain edge bound Majoranas in a single nanowire system, which both function by applying spatiotemporally dependent onsite and hopping parameters within the system’s Hamiltonian. We then complicate this model by converting it into the T-qubit to …

Quantification Of Uncertainty Propagation For Transient Heat Transfer In A Hollow Sphere, Rama Subba Reddy Gorla, Lochlan Joyce, Elie John Barbari

Faculty Publications

Uncertainty propagation and transient heat transfer for a hollow sphere are analyzed. The stochastic Biot number, stochastic linear non-dimensional initial conditions, and various boundary conditions are introduced to define uncertainty propagation influencing the temperature distribution throughout the hollow sphere. The resulting uncertainty amplitude was observed to have transient evolution in time. The uncertainty can either increase or decrease depending on the stochastic parameters. Results are presented for the variation in temperature due to uncertainties in the initial conditions and particular boundary conditions.

The Use Of Machine Learning Models For Predicting The Dielectric Strength Of Gases, Matthew Mileski, Paul W. Groth, Timothy S. Wolfe, Adib J. Samin

Faculty Publications

Technological advancements in high voltage systems have pushed sulfur hexafluoride (SF6) to its operational limits. Furthermore, this gas has other drawbacks including a high liquefaction temperature and a high global warming potential. Therefore, there has been an urgent need to find alternative gases with high dielectric strength (DS). In this work, density functional theory (DFT) is used to calculate molecular descriptors that are fed into an artificial neural network (ANN) and a random forest (RF). These machine learning (ML) models are then used to predict the DS for hundreds of molecules. A finite element model (FEM) is also used to …

Enhancing A Mid-Wave Infrared Fourier Transform Hyperspectral Imager For Explosions, James T. Stofel, Kody A. Wilson, Martin Larivière-Bastien, Anthony L. Franz, Michael L. Dexter

Faculty Publications

Capturing reliable hyperspectral imager data at a meaningful frame rate for explosions and other fast-changing scenes is not possible in the mid-wave infrared region under traditional sensor operating configurations and processing techniques, which typically have frame rates on the order of 0.5–2.0 Hz. To combat these shortcomings, the scene acquisition parameters were tailored for explosions and a new method for processing optical signatures of fast transient scenes with Fourier-transform infrared hyperspectral imagers was developed. For this technique, the instrument was first configured to collect asymmetric interferograms while optimizing the number of measurement points on the short side of the interferogram. …

Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons

Faculty Publications

A high resolution two-dimensional multi-fluid model of sporadic-E layers was developed and driven with physically realistic mesosphere, lower thermosphere (MLT) winds measured over Albuquerque, New Mexico. The realistic E-region winds are produced by the HYdrodynamic Point-wise Environment Reconstructor (HYPER) model that ingests meteor derived wind observations from a Spread-spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) system combined with the Navier-Stokes equations to provide high resolution three-dimensional wind fields over time. Sporadic-E dynamics are simulated using both realistic winds from HYPER as well as idealized hyperbolic tangent windshears to compare and contrast. Overall, the model shows greater inhomogeneity and irregularity …

A Thickness-Invariant Origami Robot With Integrated Actuation And Multimodel Locomotion, Larry L. Howell, Davis Wing, Nathan Usevitch, Sam Bridge, William Bowler

Faculty Publications

ABSTRACT Origami robots possess the potential for advanced reconfigurability in various contexts and environments. This paper describes and demonstrates the function of an origami robot following a thickness-invariant version of the Yoshimura tessellation. This thickness-invariance allows for the simple folding pattern to be expanded vertically, allowing all robotics components to be housed within the panels of the robot without impacting the functional relationships between folds of the pattern, or requiring other, more complex forms of thickness accommodation. The mathematics and engineering to create such a robot are presented to enable the use of these techniques in creating other origami-based robots. …

Automated Guided Wave Characterization Of Marcelling: In-Plane Fiber Waviness In Thermoplastic Composites, Sourav Banerjee, Ana Tudor, Corey Leydig, Thomas Ferguson, Tally Bovender, Darun Barazanchy, Josh Widosky, Paul Ziehl

Faculty Publications

Thermoplastic composite (TPC) materials often develop in-plane fiber waviness during manufacturing, a defect known as marcelling. Marcelling negatively impacts the strength and overall performance of the composite and are hard to control. While it may appear as a surface imperfection, it can also extend partially through the thickness of the material. Currently, there is no established nondestructive evaluation (NDE) method to reliably detect and quantify marcelling in composites after manufacturing. As marcelling is not a local defect but spans across the surface in in-plane dimensions of the structure, traditional pulse-echo and phased-array ultrasonic NDE are ineffective. Automated multi-directional guided …

Evaluating The Suitability Of Commercial Off-The-Shelf Software Radio Peripheral Front-Ends For High-Fidelity Satnav Monitoring Applications, Mark J. Carroll, Sanjeev Gunawardena, Timothy I. Machin, Christine M. Schubert Kabban, Joseph J. Rushanan

Faculty Publications

Signal quality monitoring is an essential portion of the Global Positioning System (GPS) enterprise. Through monitoring, accuracy and normality are achieved for each satellite and signal. GPS users rely on this information from monitoring stations to ensure safe and successful operation. Traditional monitoring has been performed with hardware receivers or custom radio frequency front-ends. These receivers have known and measured impacts on the distortions of the received signal. This research aims to elucidate and quantify the amount of distortion introduced by the front-ends of general-purpose commercial off-the-shelf software-defined radio (SDR) peripherals. Monitoring stations outfitted with SDRs are more flexible and …

Instructional Slides From Molten Salt Electrochemistry Symposium (Moses) 2026, Devin Rappleye, Carlos Mejia, Alex Peroff

Faculty Publications

This instructional slide set was developed for the 2026 Molten Salt Electrochemistry Symposium (MoSES) as an introduction and review of fundamental electrochemical concepts and methods used in molten salt systems. The material is intended for students, researchers, and practitioners seeking to better understand and interpret electrochemical measurements in high-temperature molten salts.

Topics include electrochemical thermodynamics, kinetics, mass transfer, electrode potentials, cyclic voltammetry, chronopotentiometry, chronoamperometry, square-wave voltammetry, electrochemical impedance spectroscopy (EIS), and common approaches for analyzing electrochemical data. Emphasis is placed on building physical intuition, understanding underlying assumptions, recognizing common experimental artifacts, and connecting electrochemical signals to real chemical and transport …

Property Tables For Thermally Perfect Gases At Low Pressure, Travis J. Moore, Matthew R. Jones

Faculty Publications

Tables giving gas properties at low pressure enable the efficient analysis of processes in which the gas is approximated as thermally perfect but not calorically perfect. In addition to specific enthalpy and specific internal energy, thermally perfect gas tables include special functions that depend only on temperature—relative pressure and relative specific volume. These functions may be used to determine pressure, volume, and temperature of thermally perfect gases undergoing hypothetical isentropic processes. However, the definitions of these functions included in widely used thermodynamics textbooks are vague, inconsistent, or incorrect. The intent of this work is to discuss common inaccuracies in the …

Incorporating Increased Road User Costs Into Pavement Management Modeling: A Case Study Of Two-Lane Rural Highways, Khaled A. Abaza, Mohamed S. Yamany

Faculty Publications

The impact of increased road user costs on optimal pavement rehabilitation plans has been investigated using a simplified pavement management model. The increased road user costs include elevated vehicle operating costs (VOCs) due to work-zone lane closures and traveling on severely deteriorated pavements. A model is proposed for estimating the VOC for work-zone lane closures on two-lane rural highways, considering both stopping and idling costs. Another model for approximating the increased VOC associated with driving on poor/bad pavements is suggested as a function of the relevant VOC rate and a proportionality factor. Sample results are presented for a two-lane rural …

Comprehensive Analytical Framework For Prestressed Steel–Concrete Composite Beams: Verification And Parametric Evaluation, Islam Salama, Ayman El-Zohairy

Faculty Publications

This study develops a comprehensive analytical framework to predict the flexural behavior of externally prestressed steel–concrete composite I-girders (EPCIBs) subjected to positive bending. The analytical model is formulated using strain compatibility and internal force equilibrium and accounts for elastic–plastic behavior of concrete, structural steel, and external tendons. Validation against three independent experimental programs demonstrated strong accuracy, with differences in ultimate moment within 5–8%, mid-span deflection within 6–10%, and tendon stress increments within less than 6% compared with measured results. Additional validation against nonlinear ABAQUS finite element (FE) models confirmed similar accuracy, with ultimate moment discrepancies generally below 8%. A comprehensive …

Comparative Evaluation Of Yolo Models For Real-Time Detection Of Multiple Construction Resources Using Single- And Multi-Source Data, Mohamed Yamany, Mohamed F. Ghozi, Rana Khallaf, Hany Abd Elshakour Mohamed

Faculty Publications

The evolution of technology facilitates efficient construction-site monitoring, hence improving the assessment of project performance and resource utilization. You Only Look Once (YOLO) algorithms are employed for real-time object detection; however, their applicability for multiple construction resources is limited, their performance requires enhancement, and their tendency to overfit necessitates further investigation. This paper uses recent YOLO algorithms to develop real-time object detection models for recognizing three construction resource categories. This study evaluates newly established YOLO algorithms and conducts a cross-source generalization analysis utilizing single- and multi-source datasets to boost model adaptability across various construction environments. Three different datasets of construction …

Atomistic Simulations Of Crystallographic Anisotropy And Defects In Shock Loading, Benjamin P. Helman, Andre Archer, Logan Nagy, Samuel C. Wagers, Douglas E. Spearot, Adib J. Samin

Faculty Publications

The impact of crystallographic orientation, select grain boundaries, and vacancies on the shock response of aluminum was investigated using molecular dynamics simulations. Shock loading in the [001], [011], and [111] directions was explored, revealing anisotropic behavior in shock speed, generated dislocation density, and melting. The Hugoniot elastic limit (HEL) in the [100], [110], and [111] directions were calculated as 18.7 GPa, 17.8 GPa, and 22.5 GPa, respectively. These results were found to be an order of magnitude larger than the uniaxial compressive yield strengths computed at high strain rate using an affine loading scheme. Metastable melting in the [011] and …

Boiling Flow Estimation For Aero-Optic Phase Screen Generation, Jeffrey W. Utley, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Aero-optic effects due to turbulence can reduce the effectiveness of transmitting light waves to a distant target. Methods to compensate for turbulence typically rely on realistic turbulence data, which can be generated by i) experiment, ii) high-fidelity computational fluid dynamics (CFD), iii) low-fidelity CFD, and iv) autoregressive methods. However, each of these methods has significant drawbacks, including monetary and/or computational expense, limited quantity, inaccurate statistics, and overall complexity. By contrast, the boiling flow algorithm is a simple, computationally efficient model that can generate atmospheric phase screen data with only a handful of parameters. However, boiling flow has not been widely …

Assessing Planetiq Gnss-Ro Ionospheric Electron Density And Tecusing Ground-Based Ionosondes And Cosmic-2, Mohammed Alheyf, Mohamed S. Yamany, Ibrahim F. Ahmed

Faculty Publications

Radio occultation (RO) has become a key technique for monitoring the ionosphere by deriving electron density (Ne) profiles and total electron content (TEC) from GNSS signals. This study assesses the newly deployed PlanetiQ GNOMES constellation by validating its ionospheric Ne profiles and profile-based TEC against collocated measurements from ionosondes and the COSMIC-2 mission under both quiet and disturbed geomagnetic conditions. Data matching for the statistical validation uses conservative spatial thresholds of less than 1◦ in latitude and longitude and temporal limits of 30 min for ionosondes and 1 hfor COSMIC-2, supported by a dedicated sensitivity analysis, whereas storm-time case studies …

Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik

Faculty Publications

Hong–Ou–Mandel (HOM) dip from a biphoton source in a two-photon interferometer provides a myriad of quantum tools for quantum communication and sensing. But the stringent requirements for spatial coherence between the photon pair makes it prohibitively difficult to observe high-fidelity HOM dip in long-distance free-space implementations, e.g., for the photon pairs involved in quantum communication need to match the two path lengths within a few 10 s of micron because of the short coherence width of the two-photon wave-packet. While many techniques for the pathlength balancing of two interferometric arms have been studied and applied extensively, such balancing is further …

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

A Memory And Retrieval Transformer-Based Unsupervised Learning Model For Anomaly Detection And Segmentation, Jaiwei Guo, Ge Song, Yi Wang

Faculty Publications

Unsupervised learning models have recently advanced anomaly detection, especially for complex vision-based datasets, but most still yield coarse anomaly masks with vague shapes and locations. To address these limitations, this paper presents Unsupervised Segmentation and Anomaly Gradient Interpretation (USAGI), a novel transformer-based unsupervised learning approach designed for accurate anomaly detection and segmentation. We propose two novel components, the Memory Transformer and Retrieval Transformer: the former builds a memory bank from normal features during training, while the latter retrieves and compares features during testing to enable fine-grained anomaly reconstruction and segmentation. USAGI achieves salient …

The Impact Of Dispatch Weight Restrictions On Derivative Aircraft Propulsion Technology Evaluation, Timothy T. Takahashi

Faculty Publications

This paper arises from an ARPA-E-sponsored project seeking design opportunities to retrofit existing aircraft with hybrid electric propulsion systems. Engineers typically configure aircraft to fly a given payload over a long range, which is subject to field performance constraints. In practice, operators fly transport aircraft (civilian and military) in a manner where dispatch consciously trades payload and/or range to enable safe operations to and from short runways. This work describes a simple yet novel analytical process suitable for inclusion in conceptual design or technology portfolio trade study evaluations to assess the impacts of weight-restricted dispatch upon usable payloads. We find …

Advanced Finite Element Modeling And Design Enhancement Of Slender Square Concrete-Filled Double-Skin Steel Tubular Columns, Mahmoud T. Nawar, Ayman El-Zohairy, Mohamed Emara, Raghda I. Halima

Faculty Publications

Limited research exists on the behavior of square CFDST slender columns, especially under the consideration of the relation global buckling and confinement effect. This study evaluates square concrete-filled double-skin steel tubular (CFDST) columns using nonlinear finite element analysis (FEA) to simulate structural behavior under axial and eccentric loads until failure. Parametric analyses of extensive specimens of square CFDST pinended columns evaluate various parameters, providing design insights for engineering applications. The study was conducted over a wide range of slenderness ratios. Four concrete varieties with compressive strengths were tested: normal concrete (NC), engineered cementitious composites (ECCs), high-strength concrete (HSC), and ultra-high-strength …

Effects Of Niobium On The Mechanical And Oxidation Properties Of Additively Manufactured Tungsten, Alexander Lesieur, Cayla Eckley, Ryan A. Kemnitz

Faculty Publications

Although additive manufacturing presents a novel and customizable approach to fabricating tungsten (W) alloys, the layer-by-layer production technique presents a unique set of processing challenges which are further exacerbated by the metal’s refractory properties. In this study, additions of niobium (Nb) were found to improve the mechanical properties and oxidation resistance of additively manufactured W. Microstructural investigation revealed the effect of Nb on the cracking, grain size, and texture in the as-built material. Mechanical compression testing showed significant improvement in ductility with increasing Nb content. The low concentrations of Nb used did not induce large changes in the yield strength …