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At least 1,153 records · Page 64

Nuclear data sensitivity and uncertainty study of copper-reflected integral experiments [Slides]

This presentation touches on reducing uncertainties in intermediate-energy actinide nuclear data and this continues to be a high priority for many applications. The goal of PARADIGM (PARallel Approach of Differential and InteGral Measurements): accelerate efforts to reduce biases and uncertainties in nuclear data through improvements to the nuclear data pipeline. This presentation includes integral experiments and a summarization of existing copper nuclear data.

Cu63↗

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Attitude profile design program

The Attitude Profile Design (APD) Program was designed to be used as a stand-alone addition to the Simplex Computation of Optimum Orbital Trajectories (SCOOT). The program uses information from a SCOOT output file and the user defined attitude profile to produce time histories of attitude, angular body rates, and accelerations. The APD program is written in standard FORTRAN77 and should be portable to any machine that has an appropriate compiler. The input and output are through formatted files. The program reads the basic flight data, such as the states of the vehicles, acceleration profiles, and burn information, from the SCOOT output file. The user inputs information about the desired attitude profile during coasts in a high level manner. The program then takes these high level commands and executes the maneuvers, outputting the desired information.

Source record↗

Planetary Probe Entry Atmosphere Estimation Using Synthetic Air Data System

This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with an assumed vehicle aerodynamic model. The approach utilizes the full navigation state of the vehicle (position, velocity, and attitude) to recast the vehicle aerodynamic model to be a function solely of the atmospheric state (density, pressure, and winds). Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman-Schmidt filter to estimate the atmospheric conditions. The new method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the new estimation algorithm are compared with results from a Flush Air Data Sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the new proposed estimation method provides estimates consistent with the air data measurements, without the use of pressure measurements. Implications for future missions such as the Mars 2020 entry capsule are described.

Karlgaard, Chris↗

Gamma-ray observations of MAXI J1820+070 during the 2018 outburst

ABSTRACT MAXI J1820+070 is a low-mass X-ray binary with a black hole (BH) as a compact object. This binary underwent an exceptionally bright X-ray outburst from 2018 March to October, showing evidence of a non-thermal particle population through its radio emission during this whole period. The combined results of 59.5 h of observations of the MAXI J1820+070 outburst with the H.E.S.S., MAGIC and VERITAS experiments at energies above 200 GeV are presented, together with Fermi-LAT data between 0.1 and 500 GeV, and multiwavelength observations from radio to X-rays. Gamma-ray emission is not detected from MAXI J1820+070, but the obtained upper limits and the multiwavelength data allow us to put meaningful constraints on the source properties under reasonable assumptions regarding the non-thermal particle population and the jet synchrotron spectrum. In particular, it is possible to show that, if a high-energy (HE) gamma-ray emitting region is present during the hard state of the source, its predicted flux should be at most a factor of 20 below the obtained Fermi-LAT upper limits, and closer to them for magnetic fields significantly below equipartition. During the state transitions, under the plausible assumption that electrons are accelerated up to ∼500 GeV, the multiwavelength data and the gamma-ray upper limits lead consistently to the conclusion that a potential HE and very-HE gamma-ray emitting region should be located at a distance from the BH ranging between 1011 and 1013 cm. Similar outbursts from low-mass X-ray binaries might be detectable in the near future with upcoming instruments such as CTA.

Astronomy & Astrophysics↗

NIR Imaging Spectroscopy of the Inner Few Arcseconds of NGC 4151 with OSIRIS at Keck

We present H- and K-band data from the inner arcsecond of the Seyfert 1.5 galaxy NGC 4151 obtained with the adaptive optics assisted near-infrared imaging field spectrograph OSIRIS at the Keck Observatory. The angular resolution is about a few parsecs on-site and thus competes easily with optical images taken previously with the Hubble Space Telescope. We present the morphology and dynamics of most species detected but focus on the morphology and dynamics of the narrow line region (as traced by emission of [FeII]λ1.644 μm), the interplay between plasma ejected from the nucleus (as traced by 21 cm continuum radio data) and hot H2 gas and characterize the detected nuclear HeIλ2.058 μm absorption feature as a narrow absorption line (NAL) phenomenon. Emission from the narrow line region (NLR) as traced by [FeII] reveals a biconical morphology and we compare the measured dynamics in the [FeII] emission line with models proposing acceleration of gas in the NLR and simple ejection of gas into the NLR. In the inner 2.5 arcseconds the acceleration model reveals a better fit to our data than the ejection model.We also see evidence that the jet very locally enhances emission in [FeII] at certain positions in our field-of-view such that we were able to distinct the kinematics of these clouds from clouds generally accelerated in the NLR. Further, the radio jet is aligned with the bicone surface rather than the bicone axis such that we assume that the jet is not the dominant mechanism responsible for driving the kinematics of clouds in the NLR. The hot H2 gas is thermal with a temperature of about 1700 K. We observe a remarkable correlation between individual H2 clouds at systemic velocity with the 21 cm continuum radio jet. We propose that the radio jet is at least partially embedded in the galactic disk of NGC 4151 such that deviations from a linear radio structure are invoked by interactions of jet plasma with H2 clouds that are moving into the path of the jet because of rotation of the galactic disk of NGC 4151. Additionally, we observe a correlation of the jet as traced by the radio data, with gas as traced in Brγ and H2, at velocities between systemic and +/- 200 km/s at several locations along the path of the jet. The HeIλ2.058 μm line in NGC 4151 appears in emission with a blueshifted absorption component from an outflow. The emission (absorption) component has a velocity offset of 10 km/s (-280 km/s) with a Gaussian (Lorentzian) full-width (half-width) at half maximum of 160 km/s (440 km/s). The absorption component remains spatially unresolved and its kinematic measures differ from that of UV resonance absorption lines. From the amount of absorption we derive a lower limit of the HeI 2S column density of 1 × 10(exp 14) cm−2 with a covering factor along the line-of-sight of C(sub los) approximately equal to 0.1.

K-band data↗

A Measurement of the Eta Meson Radiative Decay Width via the Primakoff Effect

The ? meson is an interesting tool to study fundamental symmetries in Quantum Chromodynamics (QCD). In particular, its radiative decay width, ? p? Ñ ??q, is an important quantity that can be predicted in the framework of Chiral Perturbation Theory. A precision measurement of this quantity would provide critical inputs to understanding the mixing of the ? and ?1 mesons and extracting constants with wide-ranging applications in low-energy QCD. This decay width has been measured in the past using two different experimental techniques. The more popular technique utilized e`e´ collisions to produce ? mesons through electromagnetic interactions. Today, the Particle Data Group (PDG) averages the results of five such experiments to obtain their currently-accepted value of the decay width as: 0.515?0.018 keV. However the first measurement of this quantity was obtained from a fixed-target experiment that measured the cross section for photoproduction of ? mesons on a nuclear target via the Primakoff effect. Their result of 0.324?0.046 keV shows strong tension with the average of the collider measurements, motivating a new, high precision measurement using the Primakoff method. For this purpose, the PrimEx-eta experiment was conducted in Hall D of the Thomas Jefferson National Accelerator Facility (Jefferson Lab or JLab). The data is currently being analyzed to measure the differential cross section for the photoproduction of ? mesons on a liquid, 4He target. Preliminary results obtained from the analysis of the first phase of the PrimEx-eta experiment show reasonable agreement with the currently-accepted PDG value of the radiative decay width. However, as will be discussed, there are many challenges to this precision measurement which must be studied before any results can be finalized and compared with previous measurements. In parallel to the ? decay width measurement, the PrimEx-eta experiment measured the total cross section for the fundamental, Quantum Electrodynamics (QED) process of Compton scattering from the atomic electrons inside the target. The results obtained from this measurement are in strong agreement with the next-to-leading order QED calculations, and the total combined uncertainties are below 3% for incident photon energies between 7-10 GeV. In addition to providing the first precision measurement of the total Compton scattering cross section within this beam energy range, this measurement verifies the capability of the PrimEx-eta experimental setup to perform absolute cross section measurements at forward angles, and serves as a reference process for the calibration of systematic uncertainties.

Smith, Andrew↗

Brief Overview of the ASD Integrated Test Stand, Activities and Hazards

The ITS venue provides the first opportunity to fully assemble and test the performance of the injector; integrate, assemble and test four modules; measure the severity of the Beam Break-Up instability and perform the first set of beam measurements. Figure 1 shows a high level configuration of the ITS without the system of overhead cable management trays. The final configuration will integrate the injector, 4 modules (12 accelerator cells), 264 SSPP Line Replaceable Units (LRUs), global controls, data acquisition, and a subset of the downstream transport, Table 1. This was chosen because it provides the minimum accelerator cells required to measure the Beam Break-Up (BBU) instability and perform measurements required to validate the ASD beam transport computer models, which are priority measurements for commissioning.

43 PARTICLE ACCELERATORS↗

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗

Structural analysis of the controlled impact demonstration of a jet transport airplane

An analytical method has been developed for assessing crash dynamics of large transport aircraft, such as in the NASA Controlled Impact Demonstration (CID) jet crash test on December 1, 1984. The DYCAST nonlinear finite-element computer code was used in a series of progressively more difficult tasks to model complete transport aircraft crashes. Single aircraft frames and fuselage section vertical drop tests were modeled and analyzed to obtain comparisons with experimental data and to develop hybrid element crash springs for use in the large CID model. Predictions of crash and acceleration levels from a symmetric CID model agreed well with data from the CID experiment.

Fasanella, E. L.↗

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning guided optimal composition selection of niobium alloys for high temperature applications

Nickel- and cobalt-based superalloys are commonly used as turbine materials for high-temperature applications. However, their maximum operating temperature is limited to about 1100 °C. Therefore, to improve turbine efficiency, current research is focused on designing materials that can withstand higher temperatures. Niobium-based alloys can be considered as promising candidates because of their exceptional properties at elevated temperatures. The conventional approach to alloy design relies on phase diagrams and structure–property data of limited alloys and extrapolates this information into unexplored compositional space. In this work, we harness machine learning and provide an efficient design strategy for finding promising niobium-based alloy compositions with high yield and ultimate tensile strength. Unlike standard composition-based features, we use domain knowledge-based custom features and achieve higher prediction accuracy. We apply Bayesian optimization to screen out novel Nb-based quaternary and quinary alloy compositions and find these compositions have superior predicted strength over a range of temperatures. We develop a detailed design flow and include Python programming code, which could be helpful for accelerating alloy design in a limited alloy data regime.

Mohanty, Trupti (ORCID:0000000342701430)↗

Toward the Neutrino Discovery Platform: An Auditable, Uncertainty-Bearing Toolchain for MINERvA Open-Data Cross-Section Analysis

The Neutrino Discovery Platform (NDP) aims to accelerate DUNE-era science by making the neutrino program's existing datasets analyzable through fast, reproducible, and auditable workflows. We report a working version of two of its layers, data curation and agentic orchestration, built and tested end to end on MINERvA open data. The guiding lesson throughout is that a cross section is a measurement, and not just a plotted shape, only if it carries a defensible systematic-uncertainty budget, a trustworthy unfolding, and a reproducible record. Using a single medium-energy playlist pair from the MINERvA open-data release (about $2.05\times10^{17}$ protons on target of data), we first reproduced the shapes of two published charged-current inclusive $\nu_\mu$ measurements through a complete extraction ladder: selection, background subtraction, D'Agostini unfolding, efficiency correction, and flux normalization. These shape-level reproductions ran and tracked the published results, but they lacked the systematic-uncertainty machinery that defines a MINERvA cross section. To supply it, we vendored and built the MINERvA Analysis Toolkit and developed a many-universe systematic-uncertainty tool that produces a portable covariance artifact, a parallel event-loop runner, and a per-run auditability harness. Validated against a published covariance release, the toolchain reproduces the released statistical, flux, and muon-energy-scale terms and shows that they account for roughly 63\% of the total variance, with the remainder unreleased. Using this same infrastructure, we then performed a measurement of our own design, the hadronic recoil-energy distribution of low-energy ($E_\nu<2.5$~GeV) charged-current inclusive events, and found data/simulation shape agreement of $\chi^2/\mathrm{ndf}=1.26$. Together these results show that the platform supports original physics and not only reproductions.

Breaux, Auto [Tulane U. (main)]↗

Positrons from accelerated particle interactions

Positron production from the decay of radioactive nuclei produced in nuclear interactions of accelerated particles is treated in detail. Laboratory data as well as theoretical considerations are used to construct energy-dependent cross sections for the production of a large number of radioactive positron emitters resulting from proton and alpha-particle interactions with ambient cosmic matter. Using these cross sections, positron production rates are calculated for a variety of energetic particle spectra, assuming solar abundances for both the energetic particles and the ambient medium. These results can be used for the study of astrophysical sites which emit annihilation radiation. In particular, the results have been applied to solar flares, where the observed 0.511 MeV line is shown to be due to positrons resulting from accelerated particle reactions.

Kozlovsky, B.↗

Fermi Gamma-Ray Pulsars: Understanding the High-Energy Emission from Dissipative Magnetospheres

Based on the Fermi observational data, we reveal meaningful constraints for the dependence of the macroscopic conductivity (sigma) of dissipative pulsar magnetosphere models on the corresponding spin-down rate, epsilon(sup dot). Our models are refinements of the FIDO (Force-free Inside, Dissipative Outside) models, which have dissipative regions that are restricted on the equatorial current sheet outside of the the light-cylinder. Taking into account the observed cutoff energies of all of the Fermi pulsars and assuming that (a) the corresponding gamma-ray pulsed emission is due to curvature radiation at the radiation-reaction-limit regime, and (b) this emission is produced at the equatorial current sheet near the light cylinder, we show that the Fermi data provide clear indications about the corresponding accelerating electric-field components. A direct comparison between the Fermi cutoff energies and the model ones reveals that if sigma increases with epsilon(sup dot) for high epsilon(sup dot)-values, while it saturates for low ones. This comparison indicates also that the corresponding gap width increases toward low epsilon(sup dot)-values. Assuming the Goldreich-Julian flux for the emitting particles, we calculate the total gamma-ray luminosity (L(sub gamma)). A comparison between the dependence of the Fermi L(sub gamma)-values and the model ones on epsilon(sup dot) indicates an increase of the emitting particle multiplicity with epsilon(sup dot). Our modeling, guided by the Fermi data alone, enhances our understanding of the physical mechanisms behind the high-energy emission in pulsar magnetospheres.

Kalapotharakos, Constantinos↗

Operation and Maintenance of PV Systems: Data Science, Analysis, and Standards

This effort improves the effectiveness and reduce uncertainty in O&M cost through four primary objectives/tasks: 1) institutionalize standards for reliability and availability reporting for large PV power plants; 2) bridge systemic O&M knowledge gaps around important topics affecting O&M; 3) characterize systemic failure modes and patterns and accelerate O&M experiential learning cycles using field data; and 4) establish a baseline understanding of UPVS O&M cost drivers. Key results of this effort include publication of IEC standards, published topical papers on O&M topics, training, and characterize field data for climate- and service-related patterns (additional details below). Integrating these results serves to reduce performance risk and facilitate improvement in the way solar projects are operated and maintained. Results are well received and two publications are among the most successful SETO publications at NREL ("Model of Operation and Maintenance Costs for Photovoltaic Systems with over 40,000 downloads and "Best Practices in Operation and Maintenance of PV Systems, 3rd Ed." with over 90,000 downloads).

14 SOLAR ENERGY↗

High-speed inlet research program and supporting analyses

A Mach 5 cruise aircraft was studied in a joint program effort. The propulsion system chosen for this aircraft was an over-under turbojet/ramjet system. The ramjet portion of the inlet is to be tested in NASA Lewis' 10 x 10 SWT. Goals of the test program are to obtain performance data and bleed requirements, and also to obtain analysis code validation data. Supporting analysis of the inlet using a three-dimensional Navier-Stokes code (PEPSIS) indicates that sidewall shock/boundary layer interactions cause large separated regions in the corners underneath the cowl. Such separations generally lead to inlet unstart, and are thus a major concern. As a result of the analysis, additional bleed regions were added to the inlet model sidewalls and cowl to control separations in the corners. A two-dimensional analysis incorporating bleed on the ramp is also presented. Supporting experiments for the Mach 5 programs were conducted in the Lewis' 1 x 1 SWT. A small-scale model representing the inlet geometry up to the ramp shoulder and cowl lip was tested to verify the accelerator plate test technique and to obtain data on flow migration in the ramp and sidewall boundary layers. Another study explored several ramp bleed configurations to control boundary layer separations in that region. Design of a two-dimensional Mach 5 cruise inlet represents several major challenges including multimode operation and dual flow, high temperatures, and three-dimensional airflow effects.

Coltrin, Robert E.↗

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗