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At least 271 records · Page 15

Blending Education and Polymer Science: Semiautomated Creation of a Thermodynamic Property Database

Structured databases of chemical and physical properties play a central role in the everyday research activities of scientists and engineers. In materials science, researchers and engineers turn to these databases to quickly query, compare, and aggregate various properties, thereby allowing for the development or application of new materials. The vast majority of these databases have been generated manually, through decades of labor-intensive harvesting of information from the literature, yet while there are many examples of commonly used databases, a significant number of important properties remain locked within the tables, figures, and text of publications. The question addressed in our work is whether and to what extent the process of data collection can be automated. Students of the physical sciences and engineering are often confronted with the challenge of finding and applying property data from the literature, and a central aspect of their education is to develop the critical skills needed to identify such data and discern their meaning or validity. To address shortcomings associated with automated information extraction while simultaneously preparing the next generation of scientists for their future endeavors, we developed a novel course-based approach in which students develop skills in polymer chemistry and physics and apply their knowledge by assisting with the semiautomated creation of a thermodynamic property database.

Collaborative/Cooperative Learning↗

DMTN-277: The Monster: A reference catalog with synthetic ugrizy-band fluxes for the Vera C. Rubin observatory

In order to facilitate bootstrap photometric calibrations of early Rubin Observatory data we have created an all sky reference catalog called The Monster. This reference catalog uses a rank-ordered set of other reference catalogs to generate synthetic ugrizy-band fluxes that can be used calibrate images processed with the LSST science pipelines. This document describes the methodology used to create The Monster, documents the input external reference catalogs, and performs basic data validation of the first version of The Monster.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗

Diamond sensors and polycapillary lenses for X-ray absorption spectroscopy

Diamond sensors are evaluated as incident beam monitors for X-ray absorption spectroscopy experiments. These single crystal devices pose a challenge for an energy-scanning experiment using hard X-rays due to the effect of diffraction from the crystalline sensor at energies which meet the Bragg condition. This problem is eliminated by combination with polycapillary lenses. The convergence angle of the beam exiting the lens is large compared to rocking curve widths of the diamond. A ray exiting one capillary from the lens meets the Bragg condition for any reflection at a different energy from the rays exiting adjacent capillaries. This serves to broaden each diffraction peak over a wide energy range, allowing linear measurement of incident intensity over the range of the energy scan. Extended X-ray absorption fine structure data are measured with a combination of a polycapillary lens and a diamond incident beam monitor. These data are of comparable quality to data measured without a lens and with an ionization chamber monitoring the incident beam intensity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

A Novel Approach to β-delayed Neutron Spectroscopy Using the Beta-decay Paul Trap

A new approach to β-delayed neutron spectroscopy has been demonstrated that circumvents the many limitations associated with neutron detection by instead inferring the decay branching ratios and energy spectra of the emitted neutrons by studying the nuclear recoil. Using the Beta-decay Paul Trap, fission-product ions were trapped and confined to within a 1-mm{sup 3} volume under vacuum using only electric fields. Results from recent measurements of {sup 137}I{sup +} and plans for development of a dedicated ion trap for future experiments using the intense fission fragment beams from the Californium Rare Isotope Breeder Upgrade (CARIBU) facility at Argonne National Laboratory are summarized. The improved nuclear data that can be collected is needed in many fields of basic and applied science such as nuclear energy, nuclear astrophysics, and stockpile stewardship.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Template for estimating uncertainties of measured neutron-induced fission cross-sections

A template for estimating uncertainties (unc.) of measured neutron-induced fission, (n,f), cross-sections (cs) is presented. This preliminary template not only lists all expected unc. sources but also supplies ranges of unc., estimates for correlations between unc. of the same and different experiments which can be used if the information is nonexistent. If this template is applied systematically when estimating experimental covariances for an evaluation, it may help in pinpointing missing unc. for individual datasets, identifying unreasonably low unc., and estimating correlations between different experimental datasets. Thus, a detailed unc. estimate – usually, a time-intensive procedure – can be undertaken more consistently and efficiently. As an example, it is shown that unc. and correlations of 239 Pu(n,f) by Merla et al. [Proceedings of the Conference on Nuclear Data for Science and Technology 1991 Jülich (Springer-Verlag, Berlin, 1992) pp. 510–513], which are questionably low in the GMA database underlying the neutron cs standards evaluations, are distinctly larger at 14.7 MeV and more strongly correlated if this template is used for reestimating the associated covariances.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Roles of hot electrons in generating upper-hybrid waves in the earth's radiation belt

Electrostatic fluctuations near upper-hybrid frequency, which are sometimes accompanied by multiple-harmonic electron cyclotron frequency bands above and below the upper-hybrid frequency, are common occurrences in the Earth's radiation belt, as revealed through the twin Van Allen Probe spacecrafts. It is customary to use the upper-hybrid emissions for estimating the background electron density, which in turn can be used to determine the plasmapause locations, but the role of hot electrons in generating such fluctuations has not been discussed in detail. The present paper carries out detailed analyses of data from the Waves instrument, which is part of the Electric and Magnetic Field Instrument Suite and Integrated Science suite onboard the Van Allen Probes. Combined with the theoretical calculation, it is shown that the peak intensity associated with the upper-hybrid fluctuations might be predominantly determined by tenuous but hot electrons and that denser cold background electrons do not seem to contribute much to the peak intensity. This finding shows that upper-hybrid fluctuations detected during quiet time are not only useful for the determination of the background cold electron density but also contain information on the ambient hot electrons population as well.

79 ASTRONOMY AND ASTROPHYSICS↗

Scaling Graph Community Detection on the Tilera Many-core Architecture

In an era when power constraints and data movement are proving to be significant barriers for the application of high-end computing, the Tilera many-core architecture offers a low-power platform exhibiting many important characteristics of future systems, including a large number of simple cores, a sophisticated network-on-chip, and fine-grained control over memory and caching policies. While this emerging architecture has been previously studied for structured compute-intensive kernels, benchmarking the platform for data-bound, irregular applications present significant challenges that have remained unexplored. Community detection is an advanced prototypical graph-theoretic operation with applications in numerous scientific domains including life sciences, cyber security, and power systems. In this work, we explore multiple design strategies toward developing a scalable tool for community detection on the Tilera platform. Using several memory layout and work scheduling techniques we demonstrate speedups of up to 46x on 36 cores of the Tilera TileGX36 platform over the best serial implementation, and also show results that have comparable quality and performance to mainstream x86 platforms. To the best of our knowledge this is the first work addressing graph algorithms on the Tilera platform. This study demonstrates that through careful design space exploration, low-power many-core platforms like Tilera can be effectively exploited for graph algorithms that that embody all the essential characteristics of an irregular application.

community detection↗

Fission in a Plasma

A three-year theory project was undertaken to study the fission process in extreme astrophysical environments, such as the crust of neutron stars. In the first part of the project, the effect of electron screening on the fission process was explored using a microscopic approach. For the first time, these calculations were carried out to the breaking point of the nucleus. In the second part of the project, the population of the fissioning nucleus was calculated within the same microscopic framework. These types of calculations are extremely computer-intensive and have seldom been applied to heavy deformed nuclei, such as fissioning actinides. The results, tools and methodologies produced in this work will be of interest to both the basic-science and nuclear-data communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

Nonlinear Optimization Methods for Large-Scale Learning

Future advances in large-scale machine learning depend heavily on the availability of new and more powerful nonlinear optimization methods. The goal of this project is to address this challenge by designing new optimization algorithms that can deal with the scale, nonlinearity and stochasticity arising in machine learning models. Our research will provide the theoretical foundations for the new methods, and will involve intensive numerical testing on state-of-the-art machine learning systems. The project is organized into three interrelated projects that constitute a broad research agenda in the area of large-scale stochastic optimization for data science.

97 MATHEMATICS AND COMPUTING↗

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Parallel asynchronous systems and image processing algorithms

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Coon, D. D.↗

Functional requirements document for the Earth Observing System Data and Information System (EOSDIS) Scientific Computing Facilities (SCF) of the NASA/MSFC Earth Science and Applications Division, 1992

Five scientists at MSFC/ESAD have EOS SCF investigator status. Each SCF has unique tasks which require the establishment of a computing facility dedicated to accomplishing those tasks. A SCF Working Group was established at ESAD with the charter of defining the computing requirements of the individual SCFs and recommending options for meeting these requirements. The primary goal of the working group was to determine which computing needs can be satisfied using either shared resources or separate but compatible resources, and which needs require unique individual resources. The requirements investigated included CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A review of computer industry directions and a market survey of computing hardware provided information regarding important industry standards and candidate computing platforms. It was determined that the total SCF computing requirements might be most effectively met using a hierarchy consisting of shared and individual resources. This hierarchy is composed of five major system types: (1) a supercomputer class vector processor; (2) a high-end scalar multiprocessor workstation; (3) a file server; (4) a few medium- to high-end visualization workstations; and (5) several low- to medium-range personal graphics workstations. Specific recommendations for meeting the needs of each of these types are presented.

Botts, Michael E.↗

Radiation modeling using the Uintah heterogeneous CPU/GPU runtime system. In: XSEDE '12 Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond, Article No. 4

The Uintah Computational Framework was developed to provide an environment for solving fluid-structure interaction problems on structured adaptive grids on large-scale, long-running, data-intensive problems. Uintah uses a combination of fluid-flow solvers and particle-based methods for solids, together with a novel asynchronou task-based approach with fully automated load balancing. Uintah demonstrates excellent weak and strong scalability at full machine capacity on XSEDE resources such as Ranger and Kraken, and through the use of a hybrid memory approach based on a combination of MPI and Pthreads, Uintah now runs on up to 262k cores on the DOE Jaguar system. In order to extend Uintah to heterogeneous systems, with ever-increasing CPU core counts and additional on-node GPUs, a new dynamic CPU-GPU task scheduler is designed and evaluated in this study. This new scheduler enables Uintah to fully exploit these architectures with support for asynchronous, out-of-order scheduling of both CPU and GPU computational tasks. A new runtime system has also been implemented with an added multi-stage queuing architecture for efficient scheduling of CPU and GPU tasks. This new runtime system automatically handles the details of asynchronous memory copies to and from the GPU and introduces a novel method of pre-fetching and preparing GPU memory prior to GPU task execution. In this study this new design is examined in the context of a developing, hierarchical GPU-based ray tracing radiation transport model that provides Uintah with additional capabilities for heat transfer and electromagnetic wave propagation. The capabilities of this new scheduler design are tested by running at large scale on the modern heterogeneous systems, Keeneland and TitanDev, with up to 360 and 960 GPUs respectively. On these systems, we demonstrate significant speedups per GPU against a standard CPU core for our radiation problem.

Humphrey, Alan↗

Using Citizen Science Reports to Define the Equatorial Extent of Auroral Visibility

An aurora may often be viewed hundreds of kilometers equatorward of the auroral oval owing to its altitude. As such, the NOAA Space Weather Prediction Center (SWPC) Aurora Forecast product provides a "view line" to demonstrate the equatorial extent of auroral visibility, assuming that it is sufficiently bright and high in altitude. The view line in the SWPC product is based upon the latitude of the brightest aurora, for each hemisphere, as specified by the real-time oval variation, assessment, tracking, intensity, and online nowcasting (OVATION) Prime (2010) aurora precipitation model. In this study, we utilize nearly 500 citizen science auroral reports to compare with the view line provided by an updated SWPC aurora forecast product using auroral precipitation data from OVATION Prime (2013). The citizen science observations were recorded during March and April 2015 using the Aurorasaurus platform and cover one large geomagnetic storm and several smaller events. We find that this updated SWPC view line is conservative in its estimate and that the aurora is often viewable further equatorward than Is indicated by the forecast. By using the citizen reports to modify the scaling parameters used to link the OVATION Prime (2013) model to the view line, we produce a new view line estimate that more accurately represents the equatorial extent of visible aurora. An OVATION Prime (2013) energy flux-based equatorial boundary view line is also developed and is found to provide the best overall agreement with the citizen science reports, with an accuracy of 91 percent.

Case, N. A.↗