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Articles 31 - 60 of 3047
Full-Text Articles in Physical Sciences and Mathematics
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
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 …
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
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 …
Exact And Approximate Conformal Inference For Multi-Output Regression, Chancellor Johnstone, Eugene Ndiaye
Exact And Approximate Conformal Inference For Multi-Output Regression, Chancellor Johnstone, Eugene Ndiaye
Faculty Publications
It is common in machine learning to estimate a response y given covariate information x . However, these predictions alone do not quantify any uncertainty associated with said predictions. One way to overcome this deficiency is with conformal inference methods, which construct a set containing the unobserved response with a prescribed probability. Unfortunately, even with a one-dimensional response, conformal inference is computationally expensive despite recent encouraging advances. In this paper, we explore multi-output regression, delivering exact derivations of conformal inference p-values when the predictive model can be described as a linear function of y . Additionally, we introduce a multivariate …
Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff
Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff
Faculty Publications
Magnetic Anomaly Navigation (MagNav) is a map-based method of navigation which relies on accurately obtaining the anomaly field to a high level of precision to achieve good navigation results. This requires utilizing high quality sensors, accurately modeling disturbance fields from the aircraft & other sources, and creating high-fidelity maps. Aeromagnetic survey data or marine track survey data must be processed into a product that can be used as a reference for a magnetic navigator and a variety of techniques can be utilized for this processing. The data collection for different survey types reflects choices typically made to study the underlying …
Nuclear Structure Of Neutron-Deficient Cesium-126 And Cesium-127, Connor M. Gautam
Nuclear Structure Of Neutron-Deficient Cesium-126 And Cesium-127, Connor M. Gautam
Theses and Dissertations
Lifetimes of seven excited states of 127Cs, including the states populating the isomer, were measured through a combination of spectroscopic methods. The spin and parity of the states leading up to the 171-μs isomeric level of 126Cs were assigned for the first time, new values were measured for the lifetimes of the two isomeric states, and new evidence was presented for the assignment of a detached sequence of gamma rays to the 126Cs nucleus.
Multi-Fidelity Machine Learning Modeling For Aerodynamic Response Prediction Of Aerospace Vehicles, Ethan S. Jackman
Multi-Fidelity Machine Learning Modeling For Aerodynamic Response Prediction Of Aerospace Vehicles, Ethan S. Jackman
Theses and Dissertations
Hypersonic vehicle design requires understanding complex aerodynamic phenomena across the full flight regime. This study presents a novel MF surrogate modeling methodology that enables the prediction the full field response across a vehicle’s surface. A Space-Filling Curve (SFC) is used to convert unstructured data into 1D vectors. The a Convolutional Autoencoder is used with transfer learning to reduce the dimensionality of the data. An Emulator-Embedded Neural Network (E2NN) combines multi-fidelity data for fast, accurate predictions. A benchmark analytical example and hypersonic application are used to evaluate the methodology. Using various numbers of samples and sampling strategies it is found that …
Impacts Of Climate Disruption On Mobility Aircraft Performance In The Pacaf Region, Hannah M. Dauterman
Impacts Of Climate Disruption On Mobility Aircraft Performance In The Pacaf Region, Hannah M. Dauterman
Theses and Dissertations
This thesis investigates the projected impacts of climate disruption on the performance and fuel management of the C-17 Globemaster III, a critical mobility aircraft in the Pacific Air Forces (PACAF) region. As rising global temperatures reduce air density, the performance of aircraft is compromised, resulting in increased fuel consumption, as well as the potential for extended runway requirements and diminished cargo capacity. Using climate projection data from Coupled Model Intercomparison Project Phase 6 (CMIP6), this research analyzes future air temperature trends and their implications for C-17 fuel consumption. Results suggest that by 2049, the U.S. Air Force may incur an …
Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon
Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon
Theses and Dissertations
This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …
Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson
Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson
Theses and Dissertations
Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …
Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas
Trends And Predictive Modeling Of Real Estate Prices In Major Saudi Arabia Cities, Meshal S. Aldahas
Theses and Dissertations
his research examines historical trends and explanatory modeling of real estate prices in major Saudi cities, with a focus on Riyadh, Jeddah, and Dammam. Using a mixed-methods approach, the study integrates quantitative data from 2010–2023, including housing and macroeconomic indicators, with qualitative insights drawn from over 320 survey responses that captured consumer sentiment on affordability, job security, and housing policies. A combination of descriptive statistics, ARIMA and Exponential Smoothing techniques was applied to detect long-term patterns, seasonal variations, and market shocks. Predictive modeling was conducted using Linear Regression, Decision Trees, and Neural Networks, with results showing that job security consistently …
Spin State Of Positronium In Two Dimensions, Emille Bryant
Spin State Of Positronium In Two Dimensions, Emille Bryant
Theses and Dissertations
We investigate the spin state of the electron-positron system positronium to determine experimental criteria that can identify a positronium anyon. Anyons have been posited to be the basis for a truly fault-tolerant quantum computer, but they have not been indisputably observed in experimental systems. Through the analysis of the fully relativistic symmetry group of fermions and bosons in three dimensions, we investigate the symmetry of its subgroups to determine that positronium in two dimensions behaves as a scalar with respect to rotations. We conclude that positronium in two dimensions has an arbitrary relative spin orientation of annihilation photons and only …
Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias
Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias
Theses and Dissertations
Fuel represents over 70% of the logistical resupply demand within the Department of Defense, with the United States Air Force accounting for most of that consumption. While prior fuel efficiency efforts have primarily focused on technical upgrades, this research explores how behavioral interventions can influence pilot decision-making and operational energy outcomes. Using the Theory of Planned Behavior (TPB) as a guiding framework, this study investigates the effects of targeted behavioral strategies on pilots’ attitudes, subjective norms, perceived behavioral control, intentions, and actual fuel-efficient behaviors. A quasi-experimental design was applied through a controlled pilot study using simulator flights. Six participants were …
Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood
Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood
Theses and Dissertations
This study addresses a significant knowledge gap regarding the influence of physical workplace design on employee collaboration and satisfaction with the physical environment within U.S. Space Force technical military organizations. While seminal industry research consistently demonstrates that physical design and indoor environmental quality influence employee satisfaction and collaboration (e.g., Candido et al., 2015; Sailer et al., 2021), the understanding of these impacts within military contexts remains limited. Using a quantitative post-occupancy evaluation survey, adapted from the Sustainable Post Occupancy Evaluation Survey (SPOES), multiple regression analyses revealed that physical elements collectively predict both satisfaction and collaboration. The final simplified model showed …
Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe
Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe
Theses and Dissertations
GeSn (germanium tin) alloys are potentially well suited for near-mid infrared space optoelectronic applications. Alloys of GeSn have similar properties to group III-V and mercury-cadmium-telluride semiconductors and are compatible with cost-effective complementary metal oxide semiconductor (CMOS) manufacturing technology. Recent progress in non-equilibrium remote plasma-enhanced chemical vapor deposition (RPECVD) has enabled the crystalline growth of GeSn with Sn concentrations of up to 10% without Sn surface segregation. Several experimental studies in previous literature report CVD- or molecular beam epitaxy (MBE)-grown GeSn alloys achieving a direct bandgap with 6%-9% Sn content. This novel growth technique opens opportunities for a cost-effective, next-generation optical …
Feasibility Evaluation Of Secure Offline Large Language Models With Retrieval-Augmented Generation For Cpu-Only Inference, Erick Tyndall, Torrey J. Wagner, Colleen Gayheart, Alexandre Some, Brent T. Langhals
Feasibility Evaluation Of Secure Offline Large Language Models With Retrieval-Augmented Generation For Cpu-Only Inference, Erick Tyndall, Torrey J. Wagner, Colleen Gayheart, Alexandre Some, Brent T. Langhals
Faculty Publications
Recent advances in large language models and retrieval-augmented generation, a method that enhances language models by integrating retrieved external documents, have created opportunities to deploy AI in secure, offline environments. This study explores the feasibility of using locally hosted, open-weight large language models with integrated retrieval-augmented generation capabilities on CPU-only hardware for tasks such as question answering and summarization. The evaluation reflects typical constraints in environments like government offices, where internet access and GPU acceleration may be restricted. Four models were tested using LocalGPT, a privacy-focused retrieval-augmented generation framework, on two consumer-grade systems: a laptop and a workstation. A technical …
Impact Of Retrieval Augmented Generation And Large Language Model Complexity On Undergraduate Exams Created And Taken By Ai Agents, Erick S. Tyndall, Colleen Gayheart, Alexandre Some, Joseph Genz, Torrey J. Wagner, Brent T. Langhals
Impact Of Retrieval Augmented Generation And Large Language Model Complexity On Undergraduate Exams Created And Taken By Ai Agents, Erick S. Tyndall, Colleen Gayheart, Alexandre Some, Joseph Genz, Torrey J. Wagner, Brent T. Langhals
Faculty Publications
The capabilities of large language models (LLMs) have advanced to the point where entire textbooks can be queried using retrieval-augmented generation (RAG), enabling AI to integrate external, up-to-date information into its responses. This study evaluates the ability of two OpenAI models, GPT-3.5 Turbo and GPT-4 Turbo, to create and answer exam questions based on an undergraduate textbook. 14 exams were created with four true-false, four multiple-choice, and two short-answer questions derived from an open-source Pacific Studies textbook. Model performance was evaluated with and without access to the source material using text-similarity metrics such as ROUGE-1, cosine similarity, and word embeddings. …
Computer-Automated Systems And Methods For Using Language Models To Generate Text Based On Reading Errors, Scott Sosso, Siyu Chen, Ciara Figliuolo, Jack Mostow, Marlies Goes
Computer-Automated Systems And Methods For Using Language Models To Generate Text Based On Reading Errors, Scott Sosso, Siyu Chen, Ciara Figliuolo, Jack Mostow, Marlies Goes
AFIT Patents
A computer-implemented system and method generate personalized text based on statistics derived from input received from a user representing the user's attempts to decode graphemes into phonemes. Such statistics may be measured and recorded at the grapheme-phoneme level, and may include substitutions, insertions, deletions, and correct utterances of phonemes by the user when reading text. A language model may be trained based on characteristics of the user, such as the user's age and/or reading grade level, and the personalized text may be generated after such training of the language model. Generating the personalized text may include generating a text creation …
The Effects Of I-127 On A High-Granularity Lii(Eu) Bonner Sphere Spectrometer Response Matrix, Adam Card, Andrew W. Decker
The Effects Of I-127 On A High-Granularity Lii(Eu) Bonner Sphere Spectrometer Response Matrix, Adam Card, Andrew W. Decker
Student Publications
The measurement of neutron energy spectra using a Bonner Sphere Spectrometer (BSS) requires spectrum unfolding. One necessary component of spectrum unfolding is an accurate neutron response matrix, which describes the energy shift experienced by neutrons when passing through different moderation configurations prior to detection. Leveraging the recently-released ENDF/B-VIII.0 cross-section library, this work details the development of a new LiI(Eu) scintillator response matrix that features improved energy binning granularity as well as increased isotopic and statistical accuracy. Using MCNP6.2, detector responses were modeled at 105 discrete log-equi-spaced incident neutron energies from 1.000 × 10−9 to 2.512 × 101 MeV …
Method For Target Detection In A High Noise Environment Through Frequency Analysis Using An Event-Based Vision Sensor, Will Johnston, Shannon Young, David Howe, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter
Method For Target Detection In A High Noise Environment Through Frequency Analysis Using An Event-Based Vision Sensor, Will Johnston, Shannon Young, David Howe, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter
Faculty Publications
Event-based vision sensors (EVSs), often referred to as neuromorphic cameras, operate by responding to changes in brightness on a pixel-by-pixel basis. In contrast, traditional framing cameras employ some fixed sampling interval where integrated intensity is read off the entire focal plane at once. Similar to traditional cameras, EVSs can suffer loss of sensitivity through scenes with high intensity and dynamic clutter, reducing the ability to see points of interest through traditional event processing means. This paper describes a method to reduce the negative impacts of these types of EVS clutter and enable more robust target detection through the use of …
A Molecular Dynamics Study Of Single Crystal And Intergranular Crack Growth Behavior In WX M1−X Binary Aloys (M = V, Mo, Ta, Re), Samuel C. Wagers, Adib J. Samin
A Molecular Dynamics Study Of Single Crystal And Intergranular Crack Growth Behavior In WX M1−X Binary Aloys (M = V, Mo, Ta, Re), Samuel C. Wagers, Adib J. Samin
Faculty Publications
This study employs molecular dynamics simulations to investigate the fracture behavior of four binary refractory alloys WxM1−x (M = V, Mo, Ta, Re) and their dependence on crystallographic orientation, composition, and grain boundary (GB) structure, focusing on six distinct low-sigma grain boundaries. The simulations reveal that the effect of composition is complex with the most pronounced effect, accompanied by the maximum or minimum stress intensity factor, generally occurring at intermediate compositions. All compositions showed a higher fracture resistance in the [110] orientation compared to the [100] orientation. There was a strong thermodynamic tendency for Mo and V, …
Exploring The Translation Lookaside Buffer (Tlb) For Low-Level Task Differentiation And Classification, Cristian Agredo, Daniel F. Koranek, Christine M. Schubert, Jose A. Gutierrez Del Arroyo, Tor J. Langehaug, Scott R. Graham
Exploring The Translation Lookaside Buffer (Tlb) For Low-Level Task Differentiation And Classification, Cristian Agredo, Daniel F. Koranek, Christine M. Schubert, Jose A. Gutierrez Del Arroyo, Tor J. Langehaug, Scott R. Graham
Faculty Publications
The primary focus of modern Central Processing Unit (CPU) technologies is performance improvement, with security often considered a secondary concern. As a result, vulnerabilities within the system are overlooked. While significant research, both offensive and defensive, has been conducted on CPU caches, relatively little attention has been given to the Translation Lookaside Buffer (TLB) due to its perceived lack of data granularity. Prior studies have typically combined multiple Hardware Performance Counters (HPCs) or relied on timing analysis to extract meaningful insights. In contrast, this study introduces a novel methodology that leverages only TLB related HPCs for multi-task classification, without incorporating …
The Spectral Response Of Time-Resolved Piv In A Turbulent Boundary Layer, Peter Manovski, Wagih Abu Rowin, Henry Ng, Paul Gulotta, Matteo Giacobello, Charitha De Silva, Nicholas Hutchins, Ivan Marusic
The Spectral Response Of Time-Resolved Piv In A Turbulent Boundary Layer, Peter Manovski, Wagih Abu Rowin, Henry Ng, Paul Gulotta, Matteo Giacobello, Charitha De Silva, Nicholas Hutchins, Ivan Marusic
Student Publications
This study presents the application of time-resolved particle image velocimetry (TR-PIV) to measure the mean and fluctuating velocity components in a turbulent boundary layer (TBL) over an axisymmetric body of revolution. A narrow wall-normal strip of the flow was captured using a synchronised high-speed laser and camera at a recording frequency of up to 80 kHz. The resulting streamwise and wall-normal velocity TR-PIV data were validated against hot-wire anemometry measurements and direct numerical simulations (DNS) of a flat plate under matched flow conditions. The mean flow results showed good agreement between all methods, while the expected attenuation due to the …
Contract Quality Feature Extraction Using Llm, Aaron C. Washington
Contract Quality Feature Extraction Using Llm, Aaron C. Washington
Theses and Dissertations
This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.
Residential Factors Associated With Mental Health In United States Veterans, Air Force Military, And Air Force Employees, Andrew J. Hoisington, Christopher A. Stamper, Molly Penzenik, Meredith Reitter, Elizabeth J. Kovacs, Nazanin H. Bahraini, Lisa A. Brenner
Residential Factors Associated With Mental Health In United States Veterans, Air Force Military, And Air Force Employees, Andrew J. Hoisington, Christopher A. Stamper, Molly Penzenik, Meredith Reitter, Elizabeth J. Kovacs, Nazanin H. Bahraini, Lisa A. Brenner
Faculty Publications
Individuals in Westernized countries spend most of their time indoors. However, exploration of residential building factors that may influence occupants’ mental health is limited in scientific literature. The purpose of this study was to explore investigator's perceived areas of importance in residences to mental health via survey methods. To that end, we administered the Housing, Occupancy, Materials, and Environment (HOME) survey to assess factors that may influence mental health to those working in the United States (US) Air Force (n = 230) or past military members, US Veterans (n = 180). Self-reported mental health surveys were also administered to the …
Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling
Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling
Theses and Dissertations
Gravimeters are devices that measure gravitational acceleration which can be used by the United States Air Force (USAF) in the areas of navigation and remote sensing. Fused-silica microelectromechanical systems (MEMS) devices offer capabilities to make inexpensive relative gravimeters with higher thermal stability than common silicon devices while maintaining good gravitational sensitivity. The fused-silica devices in this research were designed, simulated, fabricated, and tested to observe their performance as gravimeters. The devices exhibit properties of highly sensitive accelerometers but the current designs do not qualify as gravimeters. This study provides information to improve the sensitivity and stability of these fused-silica MEMS …
Equiangularity From Compatible Orthobiangularity, Tyler J. Myers
Equiangularity From Compatible Orthobiangularity, Tyler J. Myers
Theses and Dissertations
An equiangular tight frame (ETF) is an equal norm sequence of vectors in a Hilbert space whose coherence achieves equality in the Welch bound. Such sequences necessarily have minimal coherence and thus are, in some sense, as "spread out" in space as possible. ETFs have a variety of applications, such as compressed sensing and waveform design. The main problem in the study of ETFs is determining the pairs (D, N) for which an ETF with N vectors in a D-dimensional space exists. Real ETFs are moreover equivalent to a special subset of a well-studied class of graphs known as strongly …
Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith
Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith
Theses and Dissertations
This thesis explores the requirements on nuclear data uncertainties needed for the use of the 19F(α, n)22Na reaction for nuclear non-proliferation applications. An overview of how neutrons are produced from alpha decays in a UF6 medium is discussed. Calculation demonstrate the role nuclear data uncertainties effect the neutron yield and energy spectra as a function of enrichment.
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Theses and Dissertations
The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …
Enhanced Nuclear Binding Near The Proton Drip Line Opens Possible Bypass Of The 64Ge Rapid Proton Capture Process Waiting Point, Zachary Meisel, W.-J Ong, J. S. Ranhawa
Enhanced Nuclear Binding Near The Proton Drip Line Opens Possible Bypass Of The 64Ge Rapid Proton Capture Process Waiting Point, Zachary Meisel, W.-J Ong, J. S. Ranhawa
Faculty Publications
We performed astrophysics model calculations with updated nuclear data to identify a possible bypass of the 64Ge waiting point, a defining feature of the rapid proton capture (rp) process that powers type I X-ray bursts on accreting neutron stars. We find that the rp-process flow through the 64Ge bypass could be up to 36% for astrophysically relevant conditions. Our results call for new studies of 65Se, including the nuclear mass, β-delayed proton emission branching, and nuclear structure as it pertains to the 64As(p, γ) reaction rate at X-ray burst temperatures.
Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen
Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen
Faculty Publications
Sporadic-E (Es) is an ionospheric phenomenon defined by strong layers of plasma which may interfere with radio wave propagation. In this work, we develop deep learning models to improve the understanding of Es, including the presence, intensity and height of the layers. We developed three separate models. The first, building off earlier work in (J. A. Ellis et al., 2024, link in AFIT Scholar, 10.1029/2023sw003669), includes only the main features from radio occultation (RO) measurements. The second adds to that time, date, location, geomagnetic and solar indices, solar winds, x-ray flux, weather and lightning. A …