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At least 217 records · Page 12

Declassified Intelligence Satellite Photography (DISP) Coverage of Antarctica

This report summarizes the results of a nine-week summer project examining all Declassified Intelligence Satellite Photography (DISP) of Antarctica. It was discovered that the data were collected in three separate missions during 1962 and 1963. The first two missions covered only the coastal areas, while the third mission covered the entire continent. Many of the 1782 frames collected were cloudy. This is especially true of West Antarctica. An optimal set of photographs covering the entire Antarctic coastline is identified along with some examples that show changes in the coastline which have occurred since the early 1960s.

Bindschadler, Robert↗

Influence of clouds on the earth's radiation budget determined from GOES data

Estimates of the cloud radiative effects on the earth's regional and zonal radiation budgets derived from GOES data during November 1978 are presented. The diurnal cloud cover variability is shown to affect both the radiation-budget measurements and the estimation of the overall effect of clouds on the net flux. For this data set, the cloud cover causes a decrease in the net flux from the clear-sky value. Thus, the cloud albedo effect outweights the greenhouse effect of the clouds. It is found that the value of the change in the radiation balance is closely related to the amount of incident solar radiation and to the zonal distributions of low, middle, and high cloud cover.

Harrison, E. F.↗

Pin-Retraction Mechanism On Quick-Release Cover

Quick-release cover includes pin-retraction mechanism releasing cover quickly from lower of two sets of pin connections holding cover. Cover released at top by pulling lever as described in "Lever-Arm Pin Puller" (NPO-18788). Removal of cover begins when technician or robot pulls upper-pin-release lever. Cover swings downward until tabs on lower pins are pulled through slots in their receptacles. Lower pins are then free.

Macmartin, Malcolm↗

The Second Annual International Space University Alumni Conference

The papers presented at the conference reflect the multidisciplinary nature of the International Space University (ISU) and its alumni. The first papers presented hold special relevance to the design projects, and cover such topics as lunar-based astronomical instrumentation, solar lunar power generation, habitation on the moon, and the legal issues governing multinational astronauts conducting research in space. The next set of papers cover various technical issues such as project success assessment, satellite networks and space station dynamics, thus reflecting the diverse backgrounds of the ISU alumni.

Johnson, Les↗

E-PiPEline: Quick to Market Emulated-PPE using Commonly Available Materials

The Center for Disease Control has recommended the public to wear cloth face coverings in public settings that reduce potential exposure to COVID-19 where other social distancing measures are difficult to maintain (e.g., grocery stores and pharmacies) especially in areas of significant community based transmission. These face coverings and other Emulated-Personal Protective Equipment (EPPE) can be made by using Commonly Available Materials (CAMs). As part of the Sandia COVID-19 LDRD effort (funded under the Materials Science Investment Area), the Sandia E-PiPEline task evaluated E-PPE design options for face coverings and face shields considering their effectiveness, durability, build difficulty, build cost, and comfort. Observations from this investigation are presented here to provide guidelines for home construction of E-PPE. This executive summary includes a brief roadmap of the analysis methodology, two one-page handouts geared to be distributed to the public at large (one for E-PPE face coverings and one for E-PPE face shields), and additional observations regarding the potential solutions for E-PPE face coverings and face shields included to further support the one-page handouts.

60 APPLIED LIFE SCIENCES↗

The Role of Mass Spectrometry in Structural Studies of Flavin-Based Electron Bifurcating Enzymes

For decades, biologists and biochemists have taken advantage of atomic resolution structural models of proteins from X-ray crystallography, nuclear magnetic resonance spectroscopy, and more recently cryo-electron microscopy. However, not all proteins relent to structural analyses using these approaches, and as the depth of knowledge increases, additional data elucidating a mechanistic understanding of protein function is desired. Flavin-based electron bifurcating enzymes, which are responsible for producing high energy compounds through the simultaneous endergonic and exergonic reduction of two intercellular electron carriers (i.e., NAD + and ferredoxin) are one class of proteins that have challenged structural biologists and in which there is great interest to understand the mechanism behind electron gating. A limited number of X-ray crystallography projects have been successful; however, it is clear that to understand how these enzymes function, techniques that can reveal detailed in solution information about protein structure, dynamics, and interactions involved in the bifurcating reaction are needed. In this review, we cover a general set of mass spectrometry-based techniques that, combined with protein modeling, are capable of providing information on both protein structure and dynamics. Techniques discussed include surface labeling, covalent cross-linking, native mass spectrometry, and hydrogen/deuterium exchange. We cover how biophysical data can be used to validate computationally generated protein models and develop mechanistic explanations for regulation and performance of enzymes and protein complexes. Our focus will be on flavin-based electron bifurcating enzymes, but the broad applicability of the techniques will be showcased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

36 MATERIALS SCIENCE↗

Full-envelope aerodynamic modeling of the Harrier aircraft

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

Mcnally, B. David↗

Retrospective Analysis of NIST Standard Reference Material 1450, Fibrous Glass Board, for Thermal Insulation Measurements

Thermal conductivity data acquired previously for the establishment of Standard Reference Material (SRM) 1450, Fibrous Glass Board, as well as subsequent renewals 1450a, 1450b, 1450c, and 1450d, are re-analyzed collectively and as individual data sets. Additional data sets for proto-1450 material lots are also included in the analysis. The data cover 36 years of activity by the National Institute of Standards and Technology (NIST) in developing and providing thermal insulation SRMs, specifically high-density molded fibrous-glass board, to the public. Collectively, the data sets cover two nominal thicknesses of 13 mm and 25 mm, bulk densities from 60 kg∙m -3 to 180 kg∙m -3 , and mean temperatures from 100 K to 340 K. The analysis repetitively fits six models to the individual data sets. The most general form of the nested set of multilinear models used is given in the following equation: λ(ρ, T) = α 0 + α 1 ρ +α 2 T + α 3 T 3 +α 4 e - ($\frac{T-a_{5}}{a_{6}}$) 2 = where λ(ρ,T) is the predicted thermal conductivity (W∙m -1 ∙K -1 ), ρ is the bulk density (kg∙m -3 ), T is the mean temperature (K) and $a_i$ (for i = 1, 2, … 6) are the regression coefficients. The least squares fit results for each model across all data sets are analyzed using both graphical and analytic techniques. The prevailing generic model for the majority of data sets is the bilinear model in ρ and T. λ(ρ, T) = α 0 + α 1 ρ +α 2 T One data set supports the inclusion of a cubic temperature term and two data sets with low-temperature data support the inclusion of an exponential term in T to improve the model predictions. Physical interpretations of the model function terms are described. Recommendations for future renewals of SRM 1450 are provided. An Addendum provides historical background on the origin of this SRM and the influence of the SRM on external measurement programs.

regression analysis↗

Prince Albert National Park Forest Cover Data in Vector Format

This data set provides detailed canopy, understory, and ground cover height, density, and condition information for PANP in the western portion of the BOReal Ecosystem-Atmosphere Study (BOREAS) Southern Study Area (SSA) in vector form. The original biophysical resource data set was produced in 1978 based on aerial photographs taken in 1968 and field work conducted in the mid-1970s, and PANP's update/revision of the data set was completed in 1994. The data are stored in an ARC/INFO export file.

Fitzsimmons, Michael↗

Developing A Fully Implicit Compressible Flow Valve Model in RELAP-7 and Its Application in Short Term BWR Station Black-Out Analyses

This paper presents a set of dynamical models for SRV simulation and their implementation in the RELAP-7 code, which is a new reactor system analysis code being developed at INL. RELAP-7 is based on the MOOSE (the Multi-Physics Object-Oriented Simulation Environment) framework. The compressible flow SRV model covers three different sets of models: fully closed case, subsonic case, and choking case. The RELAP-7 is a fully implicit code and the preconditioned Jacobian-free Newton-Krylov (JFNK) method is used to solve the discretized nonlinear problem. The JFNK method generally needs a good preconditioning scheme to be effective and efficient. There are different ways to precondition the JFNK method. In RELAP-7, two main options are used to obtain the preconditioning matrix: (1) FDP (Finite Difference Preconditioning) option which uses the default finite differencing method provided in the PETSc package. PETSc is the numerical solver software developed by Argonne National Laboratory and used by MOOSE as the numerical solution engine; (2) SMP (Single Matrix Preconditioning) option which requires code developers to provide approximate analytical Jacobian inputs for the important diagonal and off-diagonal terms. Due to the strong discontinuity in the residual vector space when the compressible flow valve model switches from one set of model to another, FDP option cannot guarantee convergence. Instead, accurate analytical Jacobain terms are provided for the compressible flow valve model. With the SMP option selected, the compressible flow valve model can be solved efficiently under different cases. The developed compressible flow valve model has been used for SRV component simulation in several simplified BWR SBO (Station Black-Out) simulations with RELAP-7. This paper only presents cases for short-term SBO in which all the safety systems fail to start and function properly when SBO occurs. Consequently, only the SRVs automatically open and close periodically to control the primary system pressure and discharge the high temperature and high pressure steam into the suppression pool. Although simplified, this case is quite similar to what happened in Fukushima Daiichi Unit 1. Unit 1 had no RCIC system, while the isolation condenser system was believed to be non-functioning, or only available for a very short period of time during the accident. Therefore, the Unit 1 reactor core reached a fuel failure temperature only a few hours into the accident. Two short-term SBO cases will be compared: one with single SRV discharge line which represents all the SRV lines and another case with multi-group SRVs which represent each group of SRV line with different setting points.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Short-distance matrix elements for $D$-meson mixing for 2+1 lattice QCD

We study the short-distance hadronic matrix elements for D-meson mixing with partially quenched N f = 2+1 lattice QCD. We use a large set of the MIMD Lattice Computation Collaboration's gauge configurations with a 2 tadpole-improved staggered sea quarks and tadpole-improved Lüscher-Weisz gluons. We use the a 2 tadpole-improved action for valence light quarks and the Sheikoleslami-Wohlert action with the Fermilab interpretation for the valence charm quark. Our calculation covers the complete set of five operators needed to constrain new physics models for D-meson mixing. We match our matrix elements to the MS-NDR scheme evaluated at 3 GeV. We report values for the Beneke-Buchalla-Greub-Lenz-Nierste choice of evanescent operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗

IMS/Satellite Situation Center report. Predicted orbit plots for Hawkeye 1, 1976

The predicted orbit plots are shown in three projections. The time period covered by each set of projections is 2 days 1 hour, corresponding approximately to the period of Hawkeye 1. The three coordinate systems used are the Geocentric Solar Ecliptic system (GSE), the Geocentric Solar Magnetospheric system (GSM), and the Solar Magnetic system (SM). For each of the three projections, time ticks and codes are given on the satellite trajectories. The codes are interpreted in the table at the base of each plot. Time is given in the table as year/day/decimal hour. The total time covered by each plot is shown at the bottom of each table, and an additional variable is given in the table for each time tick. For the GSM and SM projection this variable is the geocentric distance to the satellite in earth radii, and for the GSE projection the variable is satellite ecliptic latitude in degrees.

Source record↗

IMS/Satellite Situation Center report. Predicted orbit plots for IMP-H-1976

Predicted orbit plots are shown in three projections. The time period covered by each set of projections is 12 days 6 hours, corresponding approximately to the period of IMP-H satellite. The three coordinate systems used are the Geocentric Solar Ecliptic system (GSE), the Geocentric Solar Magnetospheric system (GSM), and the Solar Magnetic system (SM). For each of the three projections, time ticks and codes are given on the satellite trajectories. The codes are interpreted in the table at the base of each plot. Time is given in the table as year/day/decimal hour. The total time covered by each plot is shown at the bottom of each table. An additional variable is given in the table for each time tick. For the GSM and SM projection this variable is the geocentric distance to the satellite in earth radii, and for the GSE projection the variable is satellite ecliptic latitude in degrees.

Source record↗

IMS/Satellite Situation Center report: Predicted orbit plots for IMP-J-1976

Predicted orbit plots for the IMP-J satellite were given for the time period January-December 1976. These plots are shown in three projections. The time period covered by each set of projections is 12 days and 6 hours, corresponding approximately to the period of IMP-J. The three coordinate systems used are the Geocentric Solar Ecliptic system (GSE), the Geocentric Solar Magnetospheric system (GSM), and the Solar Magnetic system (SM). For each of the three projections, time ticks and codes are given on the satellite trajectories. The codes are interpreted in the table at the base of each plot. Time is given in the table as year/day/decimal hour, and the total time covered by each plot is shown at the bottom of each table.

Source record↗

DOE FAIR Surrogate Benchmarks Supporting AI and Simulation Research (SBI Surrogate Benchmark Initiative) (Final Report)

Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia(UVA). SBI repositories include data, code, and all relevant collateral artifacts, that the science and engineering community needs to use and reuse these data sets and surrogates. SBI repositories generate active research from both participants in SBI and the broader AI and domain science communities. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and capture them as surrogate benchmarks with a rich set of metadata, covering. Data; Model; Metrics specification; Machine specification; Science, Speed, Power Results, We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non Surrogate benchmarks that have many common features and similar issues regarding FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, benchmarks have datasets, models, and metadata, and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates, including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).

97 MATHEMATICS AND COMPUTING↗

N-BODY SIMULATION OF THE STEPHAN'S QUINTET

The evolution of compact groups of galaxies may represent one of the few places in the nearby universe in which massive galaxies are being forged through a complex set of processes involving tidal interaction, ram-pressure stripping, and perhaps finally 'dry mergers' of galaxies stripped of their cool gas. Using collisionless N-body simulations, we propose a possible scenario for the formation of one of the best-studied compact groups: Stephan's Quintet. We define a serial approach which allows us to consider the history of the group as a sequence of galaxy-galaxy interactions seen as relatively separate events in time, but chained together in such a way as to provide a plausible scenario that ends in the current configuration of the galaxies. By covering a large set of parameters, we claim that it is very unlikely that both major tidal tails of the group have been created by the interaction between the main galaxy and a single intruder. We propose instead a scenario based on two satellites orbiting the main disk, plus the recent involvement of an additional interloper, coming from the background at high speed. This purely N-body study of the quintet will provide a parameter-space exploration of the basic dynamics of the group that can be used as a basis for a more sophisticated N-body/hydrodynamic study of the group that is necessary to explain the giant shock structure and other purely gaseous phenomena observed in both the cold, warm and hot gas in the group.

79 ASTRONOMY AND ASTROPHYSICS↗