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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Software used with the flux mapper at the solar parabolic dish test site

Software for data archiving and data display was developed for use on a Digital Equipment Corporation (DEC) PDP-11/34A minicomputer for use with the JPL-designed flux mapper. The flux mapper is a two-dimensional, high radiant energy scanning device designed to measure radiant flux energies expected at the focal point of solar parabolic dish concentrators. Interfacing to the DEC equipment was accomplished by standard RS-232C serial lines. The design of the software was dicated by design constraints of the flux-mapper controller. Early attemps at data acquisition from the flux-mapper controller were not without difficulty. Time and personnel limitations result in an alternative method of data recording at the test site with subsequent analysis accomplished at a data evaluation location at some later time. Software for plotting was also written to better visualize the flux patterns. Recommendations for future alternative development are discussed. A listing of the programs used in the anaysis is included in an appendix.

Miyazono, C.↗
NASA NTRS1986

Temporal frequency of radio emissions for the April 25, 1984 flare

The National Geophysical Data Center archives data of the solar-terrestrial environment. The USAF Radio Solar Telescope Network (RSTN) data allow performance of time series analysis to determine temporal oscillations as low as three seconds. The X13/3B flare which erupted in region 4474 (S12E43) on the 24 to 25 of April 1984, was selected. The soft X-rays, 1 to 8 A, remained above X-levels for 50 minutes and the radio emissions measured at Learmonth Solar Observatory reached a maximum of 3.15 x 10 to the 5th power SFUs at 410 MHz at 0000UT. A power spectral analysis of the fixed frequency RSTN data from Learmonth shows possible quasi-periodic fluctuations in the range two to ten seconds. Repetition rates or quasi-periodicities, in the case of the power spectral analysis, generally showed the same trends as the average solar radio flux at 245 and 8800 MHz. The quasi-periodicities at 1415 MHz showed no such trends.

Wells, G. D.↗
NASA NTRS1992

Determination and representation of electric charge distributions associated with adverse weather conditions

Algorithms are presented for determining the size and location of electric charges which model storm systems and lightning strikes. The analysis utilizes readings from a grid of ground level field mills and geometric constraints on parameters to arrive at a representative set of charges. This set is used to generate three dimensional graphical depictions of the set as well as contour maps of the ground level electrical environment over the grid. The composite, analytic and graphic package is demonstrated and evaluated using controlled input data and archived data from a storm system. The results demonstrate the packages utility as: an operational tool in appraising adverse weather conditions; a research tool in studies of topics such as storm structure, storm dynamics, and lightning; and a tool in designing and evaluating grid systems.

Rompala, John T.↗
NASA NTRS1991

A planetary version of PC-McIDAS

Viewgraphs on a planetary version of PC-McIDAS are presented. Topics covered include: McIDAS and PC-McIDAS; McIDAS hardware; real time data available; archived data available; McIDAS installed base; planetary McIDAS: and comparison of McIDAS and VICAR.

Limaye, Sanjay S.↗
NASA NTRS1993

SAO mission support software and data standards, version 1.0

This document defines the software developed by the SAO AXAF Mission Support (MS) Program and defines standards for the software development process and control of data products generated by the software. The SAO MS is tasked to develop and use software to perform a variety of functions in support of the AXAF mission. Software is developed by software engineers and scientists, and commercial off-the-shelf (COTS) software is used either directly or customized through the use of scripts to implement analysis procedures. Software controls real-time laboratory instruments, performs data archiving, displays data, and generates model predictions. Much software is used in the analysis of data to generate data products that are required by the AXAF project, for example, on-orbit mirror performance predictions or detailed characterization of the mirror reflection performance with energy.

Hsieh, P.↗
NASA NTRS1999

Monitoring and Correcting Autonomic Function Aboard Mir: NASA Technology Used in Space and on Earth to Facilitate Adaptation

The broad objective of the research was to study individual characteristics of human adaptation to long duration spaceflight and possibilities of their correction using autonomic conditioning. The changes in autonomic state during adaptation to microgravity can have profound effects on the operational efficiency of crewmembers and may result in debilitating biomedical symptoms. Ground-based and inflight experiment results showed that certain responses of autonomic nervous system were correlated with, or consistently preceded, reports of performance decrements or the symptoms. Autogenic-Feedback-Training Exercise (AFTE) is a physiological conditioning method that has been used to train people to voluntary control several of their own physiological responses. The specific objectives were: 1) To study human autonomic nervous system (ANS) responses to sustained exposure to microgravity; 2) To study human behavior/performance changes related to physiology; 3) To evaluate the effectiveness of preflight autonomic conditioning (AFTE) for facilitating adaptation to space and readaptation to Earth; and 4) To archive these data for the NASA Life Sciences Data Archive and thereby make this information available to the international scientific community.

Cowings, P.↗
NASA NTRS2004

Inductive System Health Monitoring

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

Iverson, David L.↗
NASA NTRS2004

ViDI: Virtual Diagnostics Interface: The Future of Wind Tunnel Testing - Volume 1

The quality of data acquired in a given test facility ultimately resides within the fidelity and implementation of the instrumentation systems. Over the last decade, the emergence of robust optical techniques has vastly expanded the envelope of measurement possibilities. At the same time the capabilities for data processing, data archiving and data visualization required to extract the highest level of knowledge from these global, on and off body measurement techniques have equally expanded. Yet today, while the instrumentation has matured to the production stage, an optimized solution for gaining knowledge from the gigabytes of data acquired per test (or even per test point) is lacking. A technological void has to be filled in order to possess a mechanism for near-real time knowledge extraction during wind tunnel experiments. Under these auspices, the Virtual Diagnostics Interface, or ViDI, was developed.

Fleming, Gary A.↗
NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗
NASA NTRSDate not supplied

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗
NASA NTRS1993

Compression through decomposition into browse and residual images

Economical archival and retrieval of image data is becoming increasingly important considering the unprecedented data volumes expected from the Earth Observing System (EOS) instruments. For cost effective browsing the image data (possibly from remote site), and retrieving the original image data from the data archive, we suggest an integrated image browse and data archive system employing incremental transmission. We produce our browse image data with the JPEG/DCT lossy compression approach. Image residual data is then obtained by taking the pixel by pixel differences between the original data and the browse image data. We then code the residual data with a form of variable length coding called diagonal coding. In our experiments, the JPEG/DCT is used at different quality factors (Q) to generate the browse and residual data. The algorithm has been tested on band 4 of two Thematic mapper (TM) data sets. The best overall compression ratios (of about 1.7) were obtained when a quality factor of Q=50 was used to produce browse data at a compression ratio of 10 to 11. At this quality factor the browse image data has virtually no visible distortions for the images tested.

Novik, Dmitry A.↗
NASA NTRS1999

GENESIS: GPS Environmental and Earth Science Information System

This presentation reviews the GPS ENvironmental and Earth Science Information System (GENESIS). The objectives of GENESIS are outlined (1) Data Archiving, searching and distribution for science data products derived from Space borne TurboRogue Space Receivers for GPS science and other ground based GPS receivers, (2) Data browsing using integrated visualization tools, (3) Interactive web/java-based data search and retrieval, (4) Data subscription service, (5) Data migration from existing GPS archived data, (6) On-line help and documentation, and (7) participation in the WP-ESIP federation. The presentation reviews the products and services of Genesis, and the technology behind the system.

Hajj, George↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Synthetic Streamflow Datasets to Support Emulation of Water Allocations via LSTM

This archive is the data companion to the bonney_et-al_2026_erc metarepo which generates synthetic data, trains an LSTM model, and generates performance metrics on the trained model. While the generation of the synthetic data is fully reprodicible, it is a computationally expensive process. This data archive contains the synthetic datasets needed for training and testing an LSTM model and reproduction of figures and tables. In addition, supplemenatary data products generating and visualizing results is also included, such as geospatial data for the basin. Contents There are two high level directories: `WRAP_archive/` and `repo_data/`. The `WRAP_archive` directory contains compressed intermediate dataproducts from the dataset generation workflow (marked as "I_Dataset_Generation" in the metarepo). These data products are not required by any scripts in the metarepo, but they are archived as they are expensive to generate and may have useful information for other analyses. The `repo_data` directory contains the necessary data for reproducing the workflow in the metarepo and should be decompressed and moved into the top level of the metarepo. Additional details are provided in README.md.

drought↗
NASA NTRS2000

The SHADOZ Data Base: History, Archive Web Guide, and Sample Climatologies

SHADOZ (Southern Hemisphere Additional Ozonesonde) is a project to augment and archive ozonesonde data from ten tropical and subtropical ozone stations. Started in 1998 by NASA's Goddard Space Flight Center and other US and international co-investigators, SHADOZ is an important tool for tropospheric ozone research in the equatorial region. The rationale for SHADOZ is to: (1) validate and improve remote sensing techniques (e.g., the Total Ozone Mapping Spectrometer (TOMS) satellite) for estimating tropical ozone, (2) contribute to climatology and trend analyses of tropical ozone and (3) provide research topics to scientists and educate students, especially in participating countries. SHADOZ is envisioned as a data service to the global scientific community by providing a central public archive location via the internet: http://code9l6.gsfc.nasa.gov/Data_services/shadoz. While the SHADOZ website maintains a standard data format for the archive, it also informs the data users on the differing stations' preparation techniques and data treatment. The presentation navigates through the SHADOZ website to access each station's sounding data and summarize each station's characteristics. Since the start of the project in 1998, the SHADOZ archive has accumulated over 600 ozonesonde profiles and received over 30,000 outside data requests. Data also includes launches from various SHADOZ supported field campaigns, such as, the Indian Ocean Experiment (INDOEX), Sounding of Ozone and Water in the Equatorial Region (SOWER) and Aerosols99 Atlantic Cruise. Using data from the archive, sample climatologies and profiles from selected stations and campaigns will be shown.

White, J. C.↗
DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
NASA NTRS2005

Public Outreach and Archiving of Data from the High Resolution Stereo Camera Onboard Mars Express: 2004 The First Year

During the first year of operation, corresponding to the calendar year 2004, the HRSC imaging experiment onboard ESA's Mars Express mission recorded 23 Gigabyte of 8-bit compressed raw data. After processing, the amount of data increased to more than 344 Gigabyte of decompressed and radiometrically calibrated scientifically useable image products. Every six months these HRSC Level 2 data are fed into ESA's Planetary Science Archive (PSA) that sends all data also to the Planetary Data System (PDS) to ensure easy availability to the interested user. On their respective web portals, the European Space Agency published in cooperation with the Principal Investigator-Group at Freie Universitat Berlin and the German Space Agency (DLR) almost 40 sets of high-level image scenes and movies for PR needs that have been electronically visited many hundred thousand times.

Koehler, U.↗
NASA NTRS2017

Community Exoplanet Follow-up Program

During the Kepler mission, our team provided the community with the highest resolution images available anywhere of exoplanet host stars. Using speckle interferometry on the 3.5-m WIYN, and 8-m Gemini telescopes, thousands of observations have been obtained reaching the diffraction limit of the telescope. From these public data available at the NASA Exoplanet Archive, numerous publications have resulted and many scientific results have been obtained for exoplanets including the fact that high-resolution imaging is critical to fully characterize the planet host stars and the planets themselves (e.g., planet radius and incident flux). Exoplanet host star observations have also occurred (and continue) for K2 mission candidates with archival data available as well. Observational programs for TESS candidates, WFIRST program stars, and Zodiacal light candidates are currently on-going. Availability to propose or obtain such observations are possible through 1) collaboration with our team, 2) successfully proposing to WIYN or GEMINI for telescope time, or 3) using publically available archival data. This poster will highlight the observational program, how time is allocated and how our queue observational program works, and new features and observational modes that are available now.

Exoplanet↗