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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An R shiny graphical user interface for highprecision mass spectrometric data analysis

• There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2, IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

LABONE, ELIZABETH↗
DOE OSTI2025

CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States

The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Advanced data science toolkit for non-data scientists – A user guide

Emerging modern data analytics attracts much attention in materials research and shows great potential for enabling data-driven design. Data populated from the high-throughput CALPHAD approach enables researchers to better understand underlying mechanisms and to facilitate novel hypotheses generation, but the increasing volume of data makes the analysis extremely challenging. Here in this paper, we introduce an easy-to-use, versatile, and open-source data analytics frontend, ASCENDS (Advanced data SCiENce toolkit for Non-Data Scientists), designed with the intent of accelerating data-driven materials research and development. The toolkit is also of value beyond materials science as it can analyze the correlation between input features and target values, train machine learning models, and make predictions from the trained surrogate models of any scientific dataset. Various algorithms implemented in ASCENDS allow users performing quantified correlation analyses and supervised machine learning to explore any datasets of interest without extensive computing and data science background. The detailed usage of ASCENDS is introduced with an example of experimental high-temperature alloy data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

High event rate analysis technique for the dual-axis duo-lateral position-sensitive silicon detectors of FAUST

The dual-axis duo-lateral (DADL) position-sensitive silicon detector was developed to obtain precise position and energy information for detected charged particles. The Forward Array Using Silicon Technology (FAUST) is currently equipped with 68 DADL detectors backed by CsI(Tl) scintillators for the study of charged particle correlations in heavy-ion collisions where precise position and energy information is essential. When conventional signal processing electronics were used for the DADL detectors, a position dependence of the measured energy as well as distortions in the calculated particle positions were observed. In previous work, waveforms from the detector after preamplification were studied to better understand the features that give rise to these distortions; therein, a waveform analysis technique was developed to improve the energy resolution and linearity in position reconstruction. However, the reading and writing of waveforms for an entire detector array limits data collection rates and adds significant burden in data storage and analysis speed. In this work, the integrators of a Struck SIS3316 ADC were utilized to process 228 Th source data to develop and optimize a new analysis method that captures the benefits of the waveform analysis technique while circumventing the waveform writing requirement. This integrator method – capable of 59 keV (FWHM) energy resolution – was used in the collection of 35 MeV/nucleon 28 Si + 12 C collision data using FAUST to investigate exotic decays of highly excited highly deformed nuclei. In this data, a position resolution of 0.4 mm (FWHM) was obtained for 25 MeV α-particles; for α-particles near this energy that originate from 8 Be ground state decays, a 8 Be ground state width of 30 keV (FWHM) was obtained. The impact of the energy-dependent DADL position resolution emergent from electronic noise on the quality of excited state measurement was modeled and compared to the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

E-Area Low Level Waste Generator Inventory Uncertainty Estimation

This report describes the method used to estimate the uncertainty and bias in the low-level waste inventory, as reported by Waste Generators, for waste disposed in the E-Area Low-Level Waste Facility at SRS. The waste cut uncertainty and bias is summed to calculate the current total uncertainty and bias in each disposal unit in the E-Area Low-Level Waste Facility. This information is used to estimate the future uncertainty and bias when all disposal units are closed. For most waste cuts, there are two areas of inventory uncertainty and bias: in the isotopic characterization of the waste stream and in the measurement of total waste cut activity. Waste stream characterization is accomplished through a combination of process knowledge and analytical measurements. This characterization is documented by a technical baseline that describes the relative quantity of each isotope present in the waste stream. The total activity of each individual waste cut is usually measured directly or is calculated through a ratio of activity per weight or activity per volume. The waste cut total activity is multiplied by the waste stream isotopic fraction to calculate the total isotopic activity present in the waste cut. The waste cut uncertainty and bias is calculated by analyzing the uncertainties and biases in the waste stream characterization and waste cut measurements and adding the uncertainties in quadrature and multiplying the reported isotopic activities by the bias factors. The current isotopic inventory, uncertainty, and bias of a disposal unit is the sum of the currently disposed individual waste cut isotopic activities, uncertainties, and biases. The future uncertainty and bias is estimated based on the average “worst-case” (largest) uncertainties and biases of currently closed and operational disposal units. This report details the method, data sources, and calculation techniques used to calculate these values. It also presents some of the difficulties in working with the reported data and gives examples of the calculations and analysis. The software used to carryout the analysis is included and the location of the complete individual analyses is given. After discussion with waste generators, examination of multiple waste characterization documents, and a review of SRS Manual 1S, the reported ELLWF radionuclide activities are clearly conservative and likely represent reasonable upper bounds for the true activities. However, quantifying the bias and uncertainty in each waste cut requires detailed analysis of the documentation for each waste cut measurement and waste stream characterization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Panorama 360 (Final Report)

This is the final technical report for the DOE-funded Panorama 360 project. Panorama 360 provided a resource for the collection, analysis, and sharing of performance data about end-to-end scientific workflows executing on DOE facilities. The work focused on workflows that include experimental data generation at DOE facilities. The main activities of Panorama 360 include the development of: 1. A distributed repository that stores different types of workflow execution data (e.g., point and time series performance traces at fine- and coarse-grained levels); 2. A set of open-source data capture, curation, and publishing tools fully integrated with a state-of-the-art workflow management system that automates data ingestion to the repository and enables users to discover, query, and process data from the repository; 3. A set of analysis algorithms and machine learning based tools to perform analysis and characterization of the gathered data, which can be used to detect anomalous performance or system faults; and 4. Best practices and recommendations for workflow evaluation, analysis, execution, and architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Panorama 360 (Final Report)

This final technical report from the lead institution, USC grant #DE-SC0012636, serves as the final technical report for collaborative institution UNC-CH grant #DE-SC0012390. The goal was to develop a repository and associated capabilities for data collection, ingestion, and analysis for a broad class of DOE applications that span experimental and simulation science workflows. In particular, this work focuses on workflows that include experimental data generation at DOE facilities. The main activities of Panorama 360 include the development of: (1) A distributed repository that stores different types of workflow execution data (e.g., point and time series performance traces at fine- and coarse-grained levels); (2) A set of open-source data capture, curation, and publishing tools fully integrated with a state-of-the-art workflow management system that automates data ingestion to the repository and enables users to discover, query, and process data from the repository; (3) A set of analysis algorithms and machine learning based tools to perform analysis and characterization of the gathered data, which can be used to detect anomalous performance or system faults; and (4) Best practices and recommendations for workflow evaluation, analysis, execution, and architectures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

Natural Resource Information System. Volume 1: Overall description

A prototype computer-based Natural Resource Information System was designed which could store, process, and display data of maximum usefulness to land management decision making. The system includes graphic input and display, the use of remote sensing as a data source, and it is useful at multiple management levels. A survey established current decision making processes and functions, information requirements, and data collection and processing procedures. The applications of remote sensing data and processing requirements were established. Processing software was constructed and a data base established using high-altitude imagery and map coverage of selected areas of SE Arizona. Finally a demonstration of system processing functions was conducted utilizing material from the data base.

Source record↗
NASA NTRS1972

Third and fourth moments of vertical two-point differences of turbulent velocity fluctuations in the atmospheric boundary layer.

Results of recent measurements of the distribution function of wind shear and the associated third and fourth standardized moments. Emphasis is placed on the vertical variation of the longitudinal component of turbulence, i.e., the component of turbulence along the mean wind vector. The data source consists of 11 sets of longitudinal turbulent velocity fluctuation time histories digitized at 0.2-sec intervals with approximately 18,000 data points per history.

Fichtl, G. H.↗
NASA NTRS1974

Regional environmental analysis and management: New techniques for current problems

Advances in data acquisition and processing procedures for regional environmental analysis are discussed. Automated and semi-automated techniques employing Earth Resources Technology Satellite data and conventional data sources are presented. Experiences are summarized. The ERTS computer compatible tapes provide a very complete and flexible record of earth resources data and represent a viable medium to enhance regional environmental analysis research.

Honea, R. B.↗
NASA NTRS1999

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Bosilovich, Michael G.↗
NASA NTRS1996

JPL/NASA/IEEE Test Effectiveness Workshop

(none given)From OBJECTIVES: Specific objectives of the working group are to support the innovation, development, evaluation and implementation of test methods, metrics and tools based on failure engineering/physics and/or root cause evaluations. Data sources systems and tools shall be developed and implemented that: 1) provide improved preventions, controls, analyses and tests (PACT) & field failure data collection, 2) facilities data analysis, archiving, retrieval, failure physics and/or root cause evaluations and 3) enable new and existing technology suitability evaluations to be performed.

effectiveness concurrent engineering metrics test ↗
NASA NTRS2010

ISS Plasma Environment: Status of CCMC Products for ISS Mission Ops

ISS Program currently using FPMU Ne, Te in-situ measurements to support operations and anomaly investigations. Working to acquire alternative data sources if FPMU is not available. Work is progressing on CCMC tools for low Earth orbit ionosphere characterization. Validation against FPMU data required before model output can be used for ISS operational support. MSFC plans to continue comparing CTIP output during FPMU campaigns. Results to date have been useful in identifying ionospheric origins of high latitude charging environments.

Minow, Joseph↗
NASA NTRS2012

The InSAR Scientific Computing Environment

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

geodetic imaging↗
NASA NTRS2015

Data Applicability of Heritage and New Hardware For Launch Vehicle Reliability Models

Bayesian reliability requires the development of a prior distribution to represent degree of belief about the value of a parameter (such as a component's failure rate) before system specific data become available from testing or operations. Generic failure data are often provided in reliability databases as point estimates (mean or median). A component's failure rate is considered a random variable where all possible values are represented by a probability distribution. The applicability of the generic data source is a significant source of uncertainty that affects the spread of the distribution. This presentation discusses heuristic guidelines for quantifying uncertainty due to generic data applicability when developing prior distributions mainly from reliability predictions.

Al Hassan, Mohammad↗
NASA NTRS2016

Open Source Next Generation Visualization Software for Interplanetary Missions

Mission control is evolving quickly, driven by the requirements of new missions, and enabled by modern computing capabilities. Distributed operations, access to data anywhere, data visualization for spacecraft analysis that spans multiple data sources, flexible reconfiguration to support multiple missions, and operator use cases, are driving the need for new capabilities. NASA's Advanced Multi-Mission Operations System (AMMOS), Ames Research Center (ARC) and the Jet Propulsion Laboratory (JPL) are collaborating to build a new generation of mission operations software for visualization, to enable mission control anywhere, on the desktop, tablet and phone. The software is built on an open source platform that is open for contributions (http://nasa.github.io/openmct).

software engineering↗
NASA NTRS2016

Characterize Aerosols from MODIS MISR OMI MERRA-2: Dynamic Image Browse Perspective

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed a new visualization service (NASA Level 2 Data Quality Visualization, DQViz)supporting various visualization and data accessing capabilities from satellite Level 2(MODISMISROMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

data quality↗