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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

IWG_CACTI

The Interagency Working Group for Airborne Data and Telemetry Systems (IWGADTS) is developing a suite of tools to promote standardization of instrument interface, data format and data processing. ARM Arial Facility uses the IWGADTS ("IWG1") format and the detailed information can be found at: http://www.eol.ucar.edu/iwgadts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

3D Continuous Forcing Dataset from 3D Constrained Variational Analysis at SGP

The continuous 3D large-scale forcing (VARANAL3D) data set derived from 3D constrained variational analysis (3DCVA) extends the conventional constrained variational analysis method by incorporating multiple sub-columns within the analysis domain. This advancement introduces spatial variability into the large-scale forcing fields, thereby enriching the data set’s applicability. The VARANAL3D data set spans from 2004 to 2018 and covers a region of 5˚×4.5˚ domain around the ARM SGP site. The analysis domain is divided into 10×9 sub-columns with 0.5˚ resolution. The 3D large-scale forcing data provides necessary variables to drive and evaluate single-column models (SCM), cloud-resolving models (CRM) ,and large-eddy simulations (LES), as well as information for testing model sensitivity to spatial variability of the large-scale forcing data, facilitating more rigorous testing and refinement of physical processes in SCM/CRM/LES.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography [PowerPoint]

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Stereo Camera Deployment in Support of TRACER (Field Campaign Report)

An improved understanding of the salient environmental controls on cloud formation, evolution, and eventual dissipation is critical to address ongoing challenges with cloud process and parameterization representations in global climate and Earth system models. One goal for the recent U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Tracking Aerosol Convection Interactions Experiment (TRACER) campaign was to collect a comprehensive data set that enabled such convective cloud process studies and key demonstrations for those controls that influenced cloud life cycle (i.e., aerosols, thermodynamics) in the Houston, Texas region. To help accomplish this, ARM instrumentation during TRACER was tasked with tracking a large number of individual, isolated convective cells – and to follow the evolution of these cells at high spatiotemporal resolution to characterize changes in cloud dynamic and microphysical properties. Since Houston experiences a range of convective clouds, it was known that the standard ARM Mobile Facility (AMF) instruments may not be sufficient to completely document initiating, transient, or dissipating low- or shallow-cloud behaviors that were also expected during this campaign (in terms of sensitivity, resolution, and/or operational availability). As one partial solution, a supplemental stereo camera deployment (this sub-campaign) was requested to augment the ARM AMF instrumentation to better address shallow and shallow-to-deep transitional types of cloud process drivers during TRACER (ARM stereo cameras for clouds [STEREOCAM]; Romps and Öktem 2018). The primary scientific focus was the relationships between cloud properties and the ambient conditions, which points to several key TRACER science questions including: ‘What is the relationship between cloud size or updraft intensity to the environmental wind shear and/or humidity?’ Overall, the ARM TRACER stereo camera deployment demonstrated unique effectiveness in observing a wide range of critical shallow, congestus, and transitioning or time-evolving cloud characteristics. The data sets from these cameras include information on the clouds' horizontal dimensions, elevations, and depths, while also enabling potential products for cloud initiation and dissipation rates, and vertical velocities. Stereo cameras simultaneously inform on cloud life cycle stage and spatial properties such as cloud fractional coverage, which should provide complementary information for ARM users when combined with TRACER cloud radars, lidar, and/or other profiling sensors. Moreover, camera products offer large-eddy simulation (LES),-scale-appropriate cloud coverage, depth, and spatial variability estimates, while opening additional avenues to challenge difficult process questions on cloud updrafts/entrainment and their covariability with environmental controls such as wind shear and humidity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

International land Model Benchmarking (ILAMB) Package v002.00

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Macromolecular crystallography with a large format CMOS detector

Recent advances in CMOS technology have allowed the production of large surface area detectors suitable for macromolecular crystallography experiments [1]. The Molecular Biology Consortium (MBC) Beamline 4.2.2 at the Advanced Light Source in Berkeley, CA, has installed a 2952 x 2820 mm RDI CMOS-8M detector with funds from NIH grant S10OD012073. The detector has a 20nsec dead pixel time and performs well with shutterless data collection strategies. The sensor obtains sharp point response and minimal optical distortion by use of a thin fiber-optic plate between the phosphor and sensor module. Shutterless data collections produce high-quality redundant datasets that can be obtained in minutes. The fine-sliced data are suitable for processing in standard crystallographic software packages (XDS, HKL2000, D*TREK, MOSFLM). Faster collection times relative to the previous CCD detector have resulted in a record number of datasets collected in a calendar year and de novo phasing experiments have resulted in publications in both Science and Nature [2,3]. The faster collections are due to a combination of the decreased overhead requirements of shutterless collections combined with exposure times that have decreased by over a factor of 2 for images with comparable signal to noise of the NOIR-1 detector. The overall increased productivity has allowed the development of new beamline capabilities and data collection strategies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗
DOE OSTI2016

Evaluation of layered zinc hydroxide nitrate and zinc/nickel double hydroxide salts in the removal of chromate ions from solutions

Layered zinc hydroxide nitrate (ZnHN) and Zn/Ni layered double hydroxide salts were synthesized and used to remove chromate ions from solutions at pH 8.0. The materials were characterized by many instrumental techniques before and after chromate ion removal. ZnHN decomposed after contact with the chromate solution, whereas the layered structure of Zn/Ni hydroxide nitrate (Zn/NiHN) and Zn/Ni hydroxide acetate (Zn/NiHA) remained their layers intact after the topotactic anionic exchange reaction, only changing the basal distances. ZnHN, Zn/NiHN, and Zn/NiHA removed 210.1, 144.8, and 170.1 mg of CrO{sub 4}{sup 2−}/g of material, respectively. Although the removal values obtained for Zn/NiHN and Zn/NiHA were smaller than the values predicted for the ideal formulas of the solids (194.3 and 192.4 mg of CrO{sub 4}{sup 2−}/g of material, respectively), the measured capacities were higher than the values achieved with many materials reported in the literature. Kinetic experiments showed the removal reaction was fast. To facilitate the solid/liquid separation process after chromium removal, Zn/Ni layered double hydroxide salts with magnetic supports were also synthesized, and their ability to remove chromate was evaluated. - Highlights: • Zinc hydroxide nitrate and Zn/Ni hydroxide nitrate or acetate were synthesized. • The interlayer anions were replaced by chromate anions at pH=8.0. • Only Zn/Ni hydroxide nitrate or acetate have the structure preserved after exchange. • Fast exchange reaction and high capacity of chromate removal were observed. • Magnetic materials were obtained to facilitate the solids removal the from solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

EXSCLAIM!: Harnessing materials science literature for self-labeled microscopy datasets

This work introduces the EXSCLAIM! toolkit for the automatic extraction, separation, and caption-based natural language annotation of images from scientific literature. EXSCLAIM! is used to show how rule-based natural language processing and image recognition can be leveraged to construct an electron microscopy data set containing thousands of keyword-annotated nanostructure images. Moreover, it is demonstrated how a combination of statistical topic modeling and semantic word similarity comparisons can be used to increase the number and variety of keyword annotations on top of the standard annotations from EXSCLAIM! With large-scale imaging datasets constructed from scientific literature, users are well positioned to train neural networks for classification and recognition tasks specific to microscopy-tasks often otherwise inhibited by a lack of sufficient annotated training data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Semi-empirical simulation of in-motion radiation detection systems

The Replicative Assessment of Spectroscopic Equipment (RASE) is an open-source software that uses experimental data as the basis to simulate the response of commercial radiation detectors to sources in various situations, particularly in the context of nuclear security and safeguards applications. Dynamic RASE introduces the capability to simulate scenarios where sources and detector are in relative motion. Position-dependent experimentally acquired gamma spectra are ingested by Dynamic RASE to build maps that describe the detector response over all space. These response maps are used to replicate the time-dependent energy spectra collected as sources move on a path near the detector. Here, a Gaussian process is used to build each map, incorporating a novel kernel adapted to the special case of radiation detection. The approach has been validated against experimental data acquired using a NaI-based detector for 137 Cs and 54 Mn sources. The capability to create accurate simulations using either long-dwell static measurements or dynamic pass-by measurements as source data has been demonstrated. Quantitative relative performance, benefits, and shortcomings are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗
DOE OSTI2015

MO-DE-BRA-03: TOPAS-edu: A Window Into the Stochastic World Through the TOPAS Tool for Particle Simulation

Purpose: The stochastic nature of the subatomic world presents a challenge for physics education. Even experienced physicists can be amazed at the varied behavior of electrons, x-rays, protons, neutrons, ions and the any short-lived particles that make up the overall behavior of our accelerators, brachytherapy sources and medical imaging systems. The all-particle Monte Carlo particle transport tool, TOPAS Tool for Particle Simulation, originally developed for proton therapy research, has been repurposed into a physics teaching tool, TOPAS-edu. Methods: TOPAS-edu students set up simulated particle sources, collimators, scatterers, imagers and scoring setups by writing simple ASCII files (in the TOPAS Parameter Control System format). Students visualize geometry setups and particle trajectories in a variety of modes from OpenGL graphics to VRML 3D viewers to gif and PostScript image files. Results written to simple comma separated values files are imported by the student into their preferred data analysis tool. Students can vary random seeds or adjust parameters of physics processes to better understand the stochastic nature of subatomic physics. Results: TOPAS-edu has been successfully deployed as the centerpiece of a physics course for master’s students at Queen’s University Belfast. Tutorials developed there takes students through a step by step course on the basics of particle transport and interaction, scattering, Bremsstrahlung, etc. At each step in the course, students build simulated experimental setups and then analyze the simulated results. Lessons build one upon another so that a student might end up with a full simulation of a medical accelerator, a water-phantom or an imager. Conclusion: TOPAS-edu was well received by students. A second application of TOPAS-edu is currently in development at Zurich University of Applied Sciences, Switzerland. It is our eventual goal to make TOPAS-edu available free of charge to any non-profit organization, along with associated tutorial materials developed by the TOPAS-edu community. Work supported in part by the U.S. Department of Energy under contract number DE-AC02-76SF00515. B. Villagomez-Bernabe is supported by CONACyT (Mexican Council for Science and Technology) project 231844.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Data from: “Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats”

This dataset contains supplementary information for a manuscript describing the ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) data repository's community data and metadata reporting formats. The purpose of creating the ESS-DIVE reporting formats was to provide guidelines for formatting some of the diverse data types that can be found in the ESS-DIVE repository. The 6 teams of community partners who developed the reporting formats included scientists and engineers from across the Department of Energy National Lab network. Additionally, during the development process, 247 individuals representing 128 institutions provided input on the formats. The primary files in this dataset are 10 data and metadata crosswalk for ESS-DIVE’s reporting formats (all files ending in _crosswalk.csv). The crosswalks compare elements used in each of the reporting formats to other related standards and data resources (e.g., repositories, datasets, data systems). This dataset also contains additional files recommended by ESS-DIVE’s file-level metadata reporting format. Each data file has an associated dictionary (files ending in _dd.csv) which provide a brief description of each standard or data resource consulted in the data reporting format development process. The flmd.csv file describes each file contained within the dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

FTICR-MS data

Soils along a salinity gradient from a coastal forested floodplain (Beaver Creek in Western Washington) were analyzed for their organic compound signatures using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR). This contains 12T FTICR reports of water and chloroform fraction of soils, processed data using FREDA, data filtering steps in FREDA, data used to generate van Krevelen plots, and code for analyzing FTICR data and performing statistics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Predicting material microstructure evolution via data-driven machine learning

The recent rapid rise in data-driven practices in the materials science domain has led to the development of efficient, generalizable, and accurate approaches for several applications, including: material property prediction, mining (micro)structure- property and (micro)structure-processing relationships, and characterization of material microstructures. Central to the materials science domain is linking microstructure to properties and performance, and critical to building such linkages is understanding how microstructures evolve as a function of environmental exposure or processing conditions (e.g., time, temperature, applied stress or strain, irradiation). This preview article summarizes recent work on the development of recurrent neural networks for predicting spatio-temporal microstructure evolution detailed by Yang et al in their manuscript entitled 'Self-supervised Learning and Prediction of Microstructure Evolution with Recurrent Neural Networks'.

machine learning (ML), materials characterization↗