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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Future Satellite Observations of Solar Irradiance

Required solar irradiance measurements for climate studies include those now being made by the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM) onboard the SORCE satellite, part of the Earth Observing System fleet of NASA satellites. Equivalent or better measures of Total Solar Irradiance (TSI) and Spectral Solar Irradiance (SSI, 200 to 2000 nm) are planned for the post-2010 satellites of the National Polar-orbiting Operational Environmental Satellite System ("OESS). The design life of SORCE is 5 years, so a "Solar Irradiance Gap Filler" EOS mission is being planned for launch in the 2007 time frame, to include the same TSI and SSI measurements. Besides avoiding any gap, overlap of the data sources is also necessary for determination of possible multi-decadal trends in solar irradiance. We discuss these requirements and the impacts of data gaps, and data overlaps, that may occur in the monitoring of the critical solar radiative forcing.

Cahalan, R. F.↗
NASA NTRS2003

The MER/CIP Portal for Ground Operations

We developed the Mars Exploration Rover/Collaborative Information Portal (MER/CIP) to facilitate MER operations. MER/CIP provides a centralized, one-stop delivery platform integrating science and engineering data from several distributed heterogeneous data sources. Key issues for MER/CIP include: 1) Scheduling and schedule reminders; 2) Tracking the status of daily predicted outputs; 3) Finding and analyzing data products; 4) Collaboration; 5) Announcements; 6) Personalization.

Chan, Louise↗
NASA NTRS2008

Polar Rain Gradients and Field-Aligned Polar Cap Potentials

ACE SWEPAM measurements of solar wind field-aligned electrons have been compared with simultaneous measurements of polar rain electrons precipitating over the polar cap and detected by DMSP spacecraft. Such comparisons allow investigation of cross-polar-cap gradients in the intensity of otherwise-steady polar rain. The generally good agreement of the distribution functions, f, from the two data sources confirms that direct entry of solar electrons along open field lines is indeed the cause of polar rain. The agreement between the data sets is typically best on the side of the polar cap with most intense polar rain but the DMSP f's in less intense regions can be brought into agreement with ACE measurements by shifting all energies by a fixed amounts that range from tens to several hundred eV. In most cases these shifts are positive which implies that field-aligned potentials of these amounts exist on polar cap field lines which tend to retard the entry of electrons and produce the observed gradients. These retarding potentials undoubtedly appear in order to prevent the entry of low-energy electrons and maintain charge quasi-neutrality that would otherwise be violated since most tailward flowing magnetosheath ions are unable to follow polar rain electrons down to the polar cap. In more limited regions near the boundary of the polar cap there is sometimes evidence for field-aligned potentials of the opposite sign that accelerate polar rain electrons. A solar electron burst is also studied and it is concluded that electrons from such bursts can enter the magnetotail and precipitate in the same manner as polar rain.

Fairfield, D. H.↗
NASA NTRS2008

Polar Rain Gradients and Field-Aligned Polar Cap Potentials

ACE SWEPAM measurements of solar wind field-aligned electrons have been compared with simultaneous measurements of polar rain electrons precipitating over the polar cap and detected by DMSP spacecraft. Such comparisons allow investigation of cross-polarcap gradients in the intensity of otherwise-steady polar rain. The generally good agreement of the distribution functions, f, from the two data sources confirms that direct entry of solar electrons along open field lines is indeed the cause of polar rain. The agreement between the data sets is typically best on the side of the polar cap with most intense polar rain but the DMSP f's in less intense regions can be brought into agreement with ACE measurements by shifting all energies by a fixed amounts that range from tens to several hundred eV. In most cases these shifts are positive which implies that field-aligned potentials of these amounts exist on polar cap field lines which tend to retard the entry of electrons and produce the observed gradients. These retarding potentials undoubtedly appear in order to prevent the entry of low-energy electrons and maintain charge quasi-neutrality that would otherwise be violated since most tailward flowing magnetosheath ions are unable to follow polar rain electrons down to the polar cap. In more limited regions near the boundary of the polar cap there is sometimes evidence for field-aligned potentials of the opposite sign that accelerate polar rain electrons. A solar electron burst is also studied and it is concluded that electrons from such bursts can enter the magnetotail and precipitate in the same manner as polar rain.

Fairfield, D. H.↗
NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗
DOE OSTI2020

Livewire Data Platform - A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

The Livewire Data Platform is a data storage and exchange platform. It provides: a platform, allowing data sharing and discovery by linking disparate data sources to a single website via application programming interfaces (APIs); a community, building partnerships and collaboration rather than competition; a system, allowing shared data to increase in size and complexity as EEMS evolves.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Open Source Suite for Advanced Synchrophasor Analysis

The report presents the results of the development of the open-source suite of applications for synchrophasor analysis. The suite includes several software tools for oscillation analysis, power plant model validation, and frequency response analysis using synchrophasor measurements. All tools are based on the common framework and data sources. The developed tools have been used by different electrical utilities for synchrophasor analysis. The report includes several use cases based on the actual system PMU data.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

High-Resolution Regional Wave Hindcast for U.S. Pacific Island Territories

This report summarizes modeling efforts for hindcasting of wave climate within the Exclusive Economic Zone around American Samoa, Baker Island and Howland Island, Commonwealth of Northern Mariana Islands, Guam, Jarvis Island, Johnston Atoll, Palmyra Atoll and Kingman Reef, and Wake Island. The report describes the mesh development and data sources used in the process. In addition, it provides the results of a sensitivity analysis performed to determine the optimal model configuration, details the data used for model forcing, shows a detailed skill assessment, and depicts the output.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

A market-oriented database design for critical material research

Material databases are important tools to provide and store information from material research. Rising concerns about supply-chain risks to raw materials presents a need to incorporate raw-material market and end-use application data, beyond basic chemical and physical properties, into a material database. One key challenge for researchers working on critical materials is information scarcity and inconsistency. This paper introduces, as a result of a two-year project, a critical-material commodity database (CMCD) incorporated with a low-code web-based platform that allows easy access for users and simple updates for the authors. The main goal of this project was to educate material scientists on the applications having the most impact on the supply chain and current industrial specifications/markets for each application. The objective was to provide material researchers with harmonized information so that they could gain a better understanding of the market, focus their technologies on an application with a high potential for commercialization, and better contribute to supply-chain risk reduction. While the goal was met with high receptivity, several limitations stemmed from query design, distribution platform, and quality of data source. To overcome some of these limitations and expand on CMCD's potential, we are building a public webpage with an improved interface, better data organization, and higher extensibility.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0

Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Lunar targeting study: Lunar and planetary Ephemeris tapes

The Univac 1108 computer tape data formats are documented for the ephermeris tape generated by the Jet Propulsion Laboratory and the ephemeris tape used by the Quick Response Targeting Program (QRTP). Ephermeris tapes are used as the data source for the position and velocity components of those celestial bodies being considered in an integrated trajectory simulation program. The QRTP ephemeris tape has data only for lunar mission simulations. The JPL ephemeris tape has data for the moon and the nine planets. The ephemeris tapes, the data formats, the coordinate systems, and units are defined. The transformation from the mean-of-1950 coordinate system to the nearest mean Besselian year is given.

Green, W. G.↗
NASA NTRS1985

Activities of the Pilot Land Data System project

The University of Maryland's Remote Sensing Systems Laboratory submitted to NASA/Goddard an interim progress report on the work being conducted within its Pilot Land Data System IPLDS project. The Remote Sensing Systems Laboratory addressed the following tasks: (1) identify data types and data sources needed to describe the selected test sites in collaboration with Goddard's Hydrological Sciences Branch; (2) define the procedures necessary to access/acquire this data; (3) conduct meetings with the PLDS Systems Engineering Group to identify functional specification priorities for PLDS development; (4) assemble documentation on historical remotely sensed imagery and transfer of such information to the PLDS Data Management Group; (5) collect data identified by Goodard's Hydrological Sciences Branch for data set inventory in PLD; (6) develop a Workstation-PLDS system interface over high speed lines, (7) develop and test through a Phase 1 demonstration of a micro workstation to access PLDS; and (8) establish interdepartmental agreement of development of computer link for electronic access of water resources data from USGS.

Sircar, J. K.↗
NASA NTRS1993

Algorithms for high-speed universal noiseless coding

This paper provides the basic algorithmic definitions and performance characterizations for a high-performance adaptive noiseless (lossless) 'coding module' which is currently under separate developments as single-chip microelectronic circuits at two NASA centers. Laboratory tests of one of these implementations recently demonstrated coding rates of up to 900 Mbits/s. Operation of a companion 'decoding module' can operate at up to half the coder's rate. The functionality provided by these modules should be applicable to most of NASA's science data. The hardware modules incorporate a powerful adaptive noiseless coder for 'standard form' data sources (i.e., sources whose symbols can be represented by uncorrelated nonnegative integers where the smaller integers are more likely than the larger ones). Performance close to data entries can be expected over a 'dynamic range' of from 1.5 to 12-15 bits/sample (depending on the implementation). This is accomplished by adaptively choosing the best of many Huffman equivalent codes to use on each block of 1-16 samples. Because of the extreme simplicity of these codes no table lookups are actually required in an implementation, thus leading to the expected very high data rate capabilities already noted.

Rice, Robert F.↗
NASA NTRS2008

A New Bond Albedo for Performing Orbital Debris Brightness to Size Transformations

We have developed a technique for estimating the intrinsic size distribution of orbital debris objects via optical measurements alone. The process is predicated on the empirically observed power-law size distribution of debris (as indicated by radar RCS measurements) and the log-normal probability distribution of optical albedos as ascertained from phase (Lambertian) and range-corrected telescopic brightness measurements. Since the observed distribution of optical brightness is the product integral of the size distribution of the parent [debris] population with the albedo probability distribution, it is a straightforward matter to transform a given distribution of optical brightness back to a size distribution by the appropriate choice of a single albedo value. This is true because the integration of a powerlaw with a log-normal distribution (Fredholm Integral of the First Kind) yields a Gaussian-blurred power-law distribution with identical power-law exponent. Application of a single albedo to this distribution recovers a simple power-law [in size] which is linearly offset from the original distribution by a constant whose value depends on the choice of the albedo. Significantly, there exists a unique Bond albedo which, when applied to an observed brightness distribution, yields zero offset and therefore recovers the original size distribution. For physically realistic powerlaws of negative slope, the proper choice of albedo recovers the parent size distribution by compensating for the observational bias caused by the large number of small objects that appear anomalously large (bright) - and thereby skew the small population upward by rising above the detection threshold - and the lower number of large objects that appear anomalously small (dim). Based on this comprehensive analysis, a value of 0.13 should be applied to all orbital debris albedo-based brightness-to-size transformations regardless of data source. Its prima fascia genesis, derived and constructed from the current RCS to size conversion methodology (SiBAM Size-Based Estimation Model) and optical data reduction standards, assures consistency in application with the prior canonical value of 0.1. Herein we present the empirical and mathematical arguments for this approach and by example apply it to a comprehensive set of photometric data acquired via NASA's Liquid Mirror Telescopes during the 2000-2001 observing season.

Mulrooney, Mark K.↗
NASA NTRSDate not supplied

Application of Lidar-Radar Combined Data Products during the IMPACTS 2020 Field Campaign

The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) is a three-year field campaign investigating the formation and lifecycle of banded, precipitation structures within intense wintertime cyclones impacting the highly-populated northeast United States. Unlike previous campaigns in the region, IMPACTS mission scientists have access to and coordinate the NASA ER-2 and P-3 aircraft to collect observations from both a remote sensing and in-situ perspective, respectively. For IMPACTS, the ER-2 aircraft was equipped with lidar (CPL), radar (CRS, HIWRAP, EXRAD), microwave radiometer (CoSMIR, AMPR) instruments, each with their own unique capabilities and limitations. Our on-going work effort aims to develop IMPACTS lidar and radar merged data products, which can be used to supplement the raw data sources, tease out additional aspects of the mechanisms underpinning wintertime cyclones, and enhance our understanding of microphysical properties in sensor overlap regions. Preliminary merged data products combine CPL lidar with any one of the NASA High Altitude Radar (HAR) radar products (CRS, HIWRAP, EXRAD) and represent these data as both normalized values and translated to reflectivity signal (dB). Continuing work will further refine our merged data product algorithm to provide additional information on hydrometeor species identification, ice crystal habit, and ice-water content, which will help IMPACTS achieve its mission goal of improving microphysical properties retrievals from both airborne and spaceborne platforms.

Stephen D. Nicholls↗
NASA NTRSDate not supplied

Air Quality Analysis with Sensors, Satellites, and Models

Poor air quality is a major global public health concern, which is only projected to get worse in coming years. A comprehensive understanding of current and potential future air quality and its key drivers spanning from local to global scales is needed to tackle this important problem. This presentation will outline the sources of information that we use to understand air quality, including ground-based measurements, satellites, and models. After giving an overview of these data sources and outlining their strengths and limitations, we will take a look at how they can be used together to give us a better picture of air quality locally and globally.

Carl Malings↗
DOE OSTI2024

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗
DOE OSTI2025

Electricity Baseline 2022

The Electricity Baseline (2022) is a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data and was created using the ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0). The Python package used the "ELCI_2022" model configuration to set the facility and generation data sources and years that were used to create this life cycle inventory, which were taken from publicly accessible datasets and automatically curated into a local data store. An archive of the data stores used in this model is available online: https://doi.org/10.18141/2569193. This model is presented in GreenDelta's openLCA schema v2 JSON-LD format (https://greendelta.github.io/olca-schema/).

Electricity; LCA; data inventory↗