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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

TASK3 Laboratory Experiments Data

Laboratory Experiments Data of TASK3 of DOE project DE- FE0031686. Each signal has its own excel file. 150 signals are sent through the rock sample per each load configuration. There were approximately 50 to 150 load combinations tested during the experiments. Experiments were repeated after changing the polarity direction of the transducers. Signals of these repeats are in separate folders called "Reverse". There are three formations tested from the Michigan Core and four formations tested from the FutureGen site. The "Code" folder contains the Python code developed to analyze the signals. Large Dataset, please contact EDXSupport@netl.doe.gov

core↗
DOE OSTI2021

Cinema:Snap: Real-time tools for analysis of dynamic diamond anvil cell experiment data

We report we developed tools and a workflow for real-time analysis of data from dynamic diamond anvil cell experiments performed at user light sources. These tools allow users to determine the phases of matter observed during the compression of materials in order to make decisions during an experiment to improve the quality of experimental results and maximize the use of scarce experimental facility time. The tools fill a gap in dynamic compression data analysis tools that are real-time, are flexible to the needs of high-pressure scientists, connect to automated processing of results, can be easily incorporated into workflows with existing tools and data formats, and support remote experimental data analysis workflows. Specific analytics developed include novel automated two-peak analysis for overlapping peaks and multiple phases, coordinated views of pressure and temperature values, full-compression contour plots, and configurable views of integrated x-ray diffraction. We present an experimental use case to show how the tools produce real-time analytics that help the scientists revise parameters for the next compression

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Expert‐in‐the‐loop design of integral nuclear data experiments

Abstract Nuclear data are fundamental inputs to radiation transport codes used for reactor design and criticality safety. The design of experiments to reduce nuclear data uncertainty has been a challenge for many years, but advances in the sensitivity calculations of radiation transport codes within the last two decades have made optimal experimental design possible. The design of integral nuclear experiments poses numerous challenges not emphasized in classical optimal design, in particular, constrained design spaces (in both a statistical and engineering sense), severely under‐determined systems, and optimality uncertainty. We present a design pipeline to optimize critical experiments that uses constrained Bayesian optimization within an iterative expert‐in‐the‐loop framework. We show a successfully completed experiment campaign designed with this framework that involved two critical configurations and multiple measurements that targeted compensating errors in 239 Pu nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1995

Magnetic Field Experiment Data Analysis System

The Johns Hopkins University Applied Physics Laboratory (JHU/APL) Magnetic Field Experiment Data Analysis System (MFEDAS) has been developed to process and analyze satellite magnetic field experiment data from the TRIAD, MAGSAT, AMPTE/CCE, Viking, Polar BEAR, DMSP, HILAT, UARS, and Freja satellites. The MFEDAS provides extensive data management and analysis capabilities. The system is based on standard data structures and a standard user interface. The MFEDAS has two major elements: (1) a set of satellite unique telemetry processing programs for uniform and rapid conversion of the raw data to a standard format and (2) the program Magplot which has file handling, data analysis, and data display sections. This system is an example of software reuse, allowing new data sets and software extensions to be added in a cost effective and timely manner. Future additions to the system will include the addition of standard format file import routines, modification of the display routines to use a commercial graphics package based on X-Window protocols, and a generic utility for telemetry data access and conversion.

Holland, D. B.↗
NASA NTRSDate not supplied

Linear Mixed-Effects Models for Human-in-the-Loop Tracking Experiment Data

Linear mixed-effects models provide several benefits over more traditional statistical inference tests that are particularly useful for most human-in-the-loop tracking experiment data. However, surprisingly, mixed models are virtually not used for the analysis of tracking experiment data. This paper uses of linear mixed-effects models to analyze combined tracking data from two previous human-in-the-loop roll tracking experiments that compared control behavior metrics collected in both a research aircraft and a motion-base simulator. In the experiments, pilots' behavior under 10 different motion configurations with varying motion filter gains and break frequencies was evaluated and compared to that in the real aircraft. The linear mixed-effects model analysis on the combined dataset confirmed the main statistical outcomes of the individual experiments. The main benefits of mixed models for this type of data were demonstrated by successfully combining data from two experiments that used different experimental conditions and of which one had an additional apparatus and the other a missing participant. Finally, the mixed-model analysis was able to explicitly test for scientifically relevant statistical differences in the dependent measures between the aircraft and simulator, as well as both experiments.

manual control↗
DOE OSTI2022

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis to Support Risk Model Parameter Estimations

This set of slides has been prepared for a talk at the INL AI/ML Symposium held on September 8, 2022. Presentation outline: Background - Nuclear power plant operating experience data sources • Research focus and motivation - Analyzing free-text operating experience data: present and future • Research method - Input - Methodological steps - Output • Conclusions and next steps

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

Reduction procedures for accurate analysis of MSX surveillance experiment data

Technical challenges of the Midcourse Space Experiment (MSX) science instruments require careful characterization and calibration of these sensors for analysis of surveillance experiment data. Procedures for reduction of Resident Space Object (RSO) detections will be presented which include refinement and calibration of the metric and radiometric (and photometric) data and calculation of a precise MSX ephemeris. Examples will be given which support the reduction, and these are taken from ground-test data similar in characteristics to the MSX sensors and from the IRAS satellite RSO detections. Examples to demonstrate the calculation of a precise ephemeris will be provided from satellites in similar orbits which are equipped with S-band transponders.

Gaposchkin, E. Mike↗
NASA NTRS1976

Onboard experiment data support facility. Task 2 report: Definition of onboard processing requirements

The onboard experiment data support facility (OEDSF) will provide data processing support to various experiment payloads on board the space shuttle. The OEDSF study will define the conceptual design and generate specifications for an OEDSF which will meet the following objectives: (1) provide a cost-effective approach to end-to-end processing requirements, (2) service multiple disciplines (3) satisfy user needs, (4) reduce the amount and improve the quality of data collected, stored and processed, and (5) embody growth capacity.

Source record↗
DOE OSTI2026

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

Combined Release and Radiation Effects Satellite (CRRES) experiments data collection, analysis, and publication

The Combined Release and Radiation Effects Satellite (CRRES) program experiments data collection, analysis, and publication activities are described. These activities were associated with both the satellite chemical release and a planned Puerto Rico sounding rocket campaign. To coordinate these activities, a working group meeting was organized and conducted.

Long, Terry N.↗
DOE OSTI2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing

Fusion energy experiments and simulations provide critical information needed to plan future fusion reactors. As next-generation devices like ITER move toward long-pulse experiments, analyses, including AI and ML, should be performed in a wide range of time and computing constraints, from near-real-time constraints, between-shot analysis, and to campaign-wide long-term analysis. However, the data volume, velocity, and variety make it extremely challenging for analyses using only local computational resources. Researchers need the ability to compose and execute workflows spanning edge resources to large-scale high-performance computing facilities.We present Delta, a system to address data analysis challenges, including AI/ML, in fusion science, by leveraging the ADIOS I/O library and middleware, to support executing science workflows over the wide area network for near-real-time streaming. We discuss the data federation challenges in performing remote workflows, focusing on on-going research work in (1) managing, reducing, and streaming data to minimize I/O and data movement overheads, (2) decompressing and reorganizing data for analysis, and (3) executing workflows for automated data analysis. We introduce examples for deep-learning based data analysis for the fusion domain and demonstrate how we use Delta to construct end-to-end workflows for a fusion device in Korea, connecting a remote DOE facility in the USA. The capability demonstrated by this project is the basis for improving the state of the art for near-real-time data federation amongst remote facilities.

Choi, Jong Youl↗
NASA NTRS2014

Physical Science Informatics: Providing Open Science Access to Microheater Array Boiling Experiment Data

The Physical Science Informatics (PSI) system is the next step in this an effort to make NASA sponsored flight data available to the scientific and engineering community, along with the general public. The experimental data, from six overall disciplines, Combustion Science, Fluid Physics, Complex Fluids, Fundamental Physics, and Materials Science, will present some unique challenges. Besides data in textual or numerical format, large portions of both the raw and analyzed data for many of these experiments are digital images and video, requiring large data storage requirements. In addition, the accessible data will include experiment design and engineering data (including applicable drawings), any analytical or numerical models, publications, reports, and patents, and any commercial products developed as a result of the research. This objective of paper includes the following: Present the preliminary layout (Figure 2) of MABE data within the PSI database. Obtain feedback on the layout. Present the procedure to obtain access to this database.

nucleate boiling↗
NASA NTRS1975

Onboard experiment data support facility, task 1 report

The conceptual design and specifications are developed for an onboard experiment data support facility (OEDSF) to provide end to end processing of data from various payloads on board space shuttles. Classical data processing requirements are defined and modeled. Onboard processing requirements are analyzed. Specifications are included for an onboard processor.

Source record↗
NASA NTRS1972

An investigation of geometry and noise corrections to San Marco-C neutral atmospheric composition experiment data

The problem of the calculation of ambient densities from San Marco-C neutral atmospheric composition experiment data is considered. A brief description is given of the data measurement method, followed by a description of both the theoretical and experimental data curves. Geometry, electrometer distortions, and noise effects are then studied in terms of their effects on the ideal data form. From these considerations two data reduction methods are evolved. The first is an iterative integration technique that exploits the symmetry of the experimental data about the minimum angle of attack. For the analysis of geometry effects, a second method using interval averaging was developed and studied.

Curtis, S. A.↗
DOE OSTI2023

The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE's magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (~71%) SNe Ia, 339 (~23%) SNe II, and 96 (~6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Results of software error-data experiments

In order to evaluate existing software reliability models and proposed modeling approaches, a search was conducted for data on the software failure process. This search revealed that the data necessary for this evaluation were not available. As a result, a research effort was initiated by NASA to generate data on which to base the development of credible methods for assessing the reliability of software targeted for flight-crucial applications. Two sets of software error-data experiments were conducted by different research groups. The results of the experiments were consistent: errors caused by different faults in a program occurred at widely varying rates; program failure rates exhibited a log-linear trend with respect to the number of faults corrected; some faults were found to interact in either concealing or revealing ways; and contiguous regions of the input space which cause a program to generate errors, called error crystals, were found and characterized for some faults. Collectively, these experiments have produced information on software failure which must be accounted for in software reliability modeling approaches.

Finelli, George B.↗