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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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NASA NTRSDate not supplied

NASA’s Commercial Smallsat Data Acquisition (CSDA) Program Data System

The National Aeronautic and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program was established to identify, evaluate, and acquire data from commercial satellite companies that support and complement NASA’s Earth sciences missions and research goals. Since becoming a sustained program in 2020, CSDA has been developing a data system to provide scalable, efficient, continuous, and repeatable data management processes for all commercial data acquired by NASA. This includes providing access to commercial data to approved science investigators through NASA developed and vendor operated interfaces. As the commercial data user community and volume of data acquired by CSDA has grown, the team managing these data has adapted technologies and services to better address the data and information search, discovery, and access needs of the science user community. This presentation will provide an overview of CSDA Program data system activities including data availability, development of CSDA user interfaces, challenges in managing large-volume diverse datasets, and long-term data preservation activities to retain data for scientific reproducibility.

data management↗
NASA NTRSDate not supplied

Improving Data Discovery, Analysis, and Visualizations With Cloud-Based User Services

The Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) is one of 12 DAACs managed by the United States National Aeronautics and Space Administration (NASA) Earth Science Data and Information System (ESDIS) project [1]. GHRC and the other DAACs are designed to process, archive, document, and distribute NASA Earth-observing data, ranging from satellite missions to field campaigns [2]. A major goal of the DAACs is to enable science with these data. Science enabling can be difficult as datasets can be very large, use multiple formats, come from numerous platforms, and require three-dimensional visualization. GHRC is using its expertise with cloud-based technologies to develop open source and open science tools to empower users to explore, coincidentally visualize, and analyze multiple datasets. Being open source, the user community can develop visualizations for their own datasets. This presentation will expand on this objective and highlight the capabilities available to the international community now.

GHRC↗
NASA NTRS2011

InSAR Scientific Computing Environment

This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors. There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth's ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches. This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and new codes, abstraction and generalization of the data model for efficient manipulation of objects among modules, and well-designed module interfaces suitable for command- line execution or GUI-programming. The framework is designed to allow users contributions to promote maximum utility and sophistication of the code, creating an open-source community that could extend the framework into the indefinite future.

Rosen, Paul A.↗
NASA NTRS1993

Science & Technology Laboratory Applications Software (ELAS)

Digital image analysis system processes Landsat multispectral data, aircraft-acquired scanner data, digitized topographical data, and such ancillary data as soil types and rainfall information. Over 230 modules aid user in performing wide range of land cover analyses and manipulations.

Junkin, B. G.↗
NASA NTRS2000

Future Applications Using Return-Pulse Correlation from Imaging Laser Altimeters

The Laser Vegetation Imaging Sensor (LVIS) is an airborne, wide-swath, digitization-only laser altimeter capable of collecting full return waveforms (i.e. echoes) from laser footprints ranging in diameter from 1 to 80 m across up to a 1 km wide data swath. The return waveform can be used to enhance the accuracy of laser ranging and to provide information about the vertical structure of vegetation and topography within each laser footprint. Although extremely small laser footprints (< 1 0 cm diameter) generally return simple, impulse responses to their target surface, larger footprints typically exhibit complex returns representing the diverse vertical distributions of surfaces contained in each footprint. Only a handful of airborne and spaceborne laser altimeters record the return echo or return pulse that is reflected from the Earth's surface (i.e. NASA's LVIS, SLA, VCL, and GLAS laser altimeters). Waveforms are currently interpreted to extract a timing or ranging point or points to represent the mean ground elevation or the vertical height of vegetation. But, recent progress using pulse shape correlation techniques shows promise for a variety of science applications involving change detection of surface topography and vegetation as well as potential for improving data processing by correlating images or crossovers to solve systematic biases. We show example correlation images from LVIS and discuss instrument design implications and potential science applications.

Blair, J. Bryan↗
NASA NTRS2020

NASA ESDS Citizen Science Data Working Group

This document provides guidelines for legal, policy, and ethical issues; standards for citizen science data collection and management; information on ensuring usability of citizen science data and communication regarding its use; and best practices for long-term archival of citizen science data.Section1 contains a detailed discussion of policy, ethical, and legal considerations influencing citizen science data collection. Section 2 considers standards for documentation, including documentation of instrumentation, procedures, and the data itself. It concludes with a discussion of how citizen science data should be attributed. Section 3 provides guidance about how to ensure citizen science data are collected and stored in a useable way. It also considers how NASA and data producers should notify the scientific community, including citizen scientists and the public, about citizen science datasets and the scientific conclusions reached using them. Finally, Section 4 provides detailed information regarding what should be archived from projects using a citizen science approach, including data and code. It provides guidance about archive location, process, and timeframe, as well as information about data access and distribution services provided by NASA that may be relevant to data producers working with citizen scientists.

Citizen Science↗
NASA NTRS1999

Computing with Beowulf

Parallel computers built out of mass-market parts are cost-effectively performing data processing and simulation tasks. The Supercomputing (now known as "SC") series of conferences celebrated its 10th anniversary last November. While vendors have come and gone, the dominant paradigm for tackling big problems still is a shared-resource, commercial supercomputer. Growing numbers of users needing a cheaper or dedicated-access alternative are building their own supercomputers out of mass-market parts. Such machines are generally called Beowulf-class systems after the 11th century epic. This modern-day Beowulf story began in 1994 at NASA's Goddard Space Flight Center. A laboratory for the Earth and space sciences, computing managers there threw down a gauntlet to develop a $50,000 gigaFLOPS workstation for processing satellite data sets. Soon, Thomas Sterling and Don Becker were working on the Beowulf concept at the University Space Research Association (USRA)-run Center of Excellence in Space Data and Information Sciences (CESDIS). Beowulf clusters mix three primary ingredients: commodity personal computers or workstations, low-cost Ethernet networks, and the open-source Linux operating system. One of the larger Beowulfs is Goddard's Highly-parallel Integrated Virtual Environment, or HIVE for short.

Cohen, Jarrett↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Building a framework to genetically characterize “feather spots” and understand demographic impacts of solar energy sites on migratory bird populations

The lack of data on the impact of utility-scale solar facilities on avian species and populations adds to the cost of siting and operation. As much as 32 percent of the avian biological material (feathers and carcasses) recovered from solar facilities remain unidentified, because they often take the form of “feather spots”. Feather spots are remains of impacted animals that can be separated into two broad categories: 1) those remains that may be visually identified to a species, or 2) those that cannot be visually identified to a species due to degradation from the environment and/or scavenger activity (listed as “unknown”). Even when feather spots can be identified to species, they cannot be visually assigned to particular breeding populations. In some cases, it is unknown whether multiple feather spots represent single or multiple individuals. This project’s objectives were to: 1. Use a developed, genetic-based technique to identify and determine the species, population of origin, and number of individuals found in feather spots recovered from solar facilities. 2. Implement collected data and resulting analyses to develop a publicly accessible web-based decision-making tool that can be used by the solar industry, regulators and other stakeholders to inform siting, mitigation, and conservation management efforts. 3. Establish a not-for-profit fee-for-service center at UCLA to ensure collection and identification of feather spots continue after the project period of performance. During the Project Period, we proposed to establish a pipeline for collecting, transporting, and storing of avian biological material collected at solar facilities and the collection and identification of feather spots to species and individual. We proposed the development of a genetic-based framework that would recover viable DNA from feather spots, amplify this DNA (i.e., make millions of copies of the original DNA), and use it to match the resulting sequences to a national database of known species of birds. The result would be the identification of feathers spots that were previously unidentified, and the incorporation of these samples into a larger database that included all samples recovered from solar facilities. The resulting report (below) details the result of this work and its alignment with proposed activities. We proposed the use of the data collected to assess the comparative risk to specific species or populations of species from solar facilities. For some species, we have already identified genomic markers of specific breeding populations and developed “genoscapes,” maps of unique genetic variation across the full breeding range of a species. We used these (previously and newly developed) genoscapes to probabilistically link a feather spot to the specific breeding populations from which it originated (assignment probabilities range from 75%-100% depending on species and population groups). For those species without genoscapes, we developed a vulnerability and susceptibility estimate that determines the relative local and regional risk to populations that are in geographic proximity to solar facilities, using citizen science data (Breeding Bird Survey (BBS) and eBird). These two feather spot processing pipelines (see Figure 1 below) provide quantitative estimates as to the numbers of individuals from a given population of origin that are affected by solar facilities, and ultimately can reduce costs to the consumer by reducing the industry costs associated with mitigation and siting strategies for future solar energy development.

14 SOLAR ENERGY↗
NASA NTRS2011

Collaboration Portals for NASA's Airborne Field Campaigns

The University of Alabama in Huntsville (UAH), in collaboration with the Global Hydrology Resource Center, a NASA Earth Science Data Center, has provided information management for a number of NASA Airborne Field campaigns, both hurricane science investigations and satellite instrument validation. Effective field campaign management requires communication and coordination tools, including utilities for personnel to upload and share flight plans, weather forecasts, a variety of mission reports, preliminary science data, and personal photos. Beginning with the Genesis and Rapid Intensification Processes (GRIP) hurricane field campaign in 2010, we have provided these capabilities via a Drupal-based collaboration portal. This portal was reused and modified for the Midlatitude Continental Convective Clouds Experiment (MC3E), part of the Global Precipitation Measurement mission ground validation program. An end goal of these development efforts is the creation of a Drupal profile for field campaign management. This presentation will discuss experiences with Drupal in developing and using these collaboration portals. Topics will include Drupal modules used, advantages and disadvantages of working with Drupal in this context, and how the science teams used the portals in comparison with other communication and collaboration tools.

Conover, Helen↗
NASA NTRS2016

PLANT: Polarimetric-Interferometric Lab and Analysis Tools for Ecosystem and Land-Cover Science and Applications

PLANT (Polarimetric-interferometric Lab and Analysis Tools) is a new collection of software tools developed at the Jet Propulsion Laboratory to support processing and analysis of Synthetic Aperture Radar (SAR) data for ecosystem and land-cover/land-use change science and applications. PLANT inherits code components from the Interferometric Scientific Computing Environment (ISCE) to generate highresolution, coregistered polarimetric-interferometric SLC stacks from Level-0/1 data for a variety of airborne and spaceborne sensors. The goal is to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g.,maps of above-ground biomass and forest disturbance). In this paper we introduce the capabilities of PLANT and report first results obtained with the tools developed up to date.

Lavalle, Marco↗
DOE OSTI2024

Co-design for Particle Applications at Exascale

Co-design across the Exascale Computing Project (ECP) has been critical for both enabling science applications and bringing disparate communities together. Developing and porting applications to the various high-performance computing (HPC) architectures on pre-exascale and exascale computers has been quite challenging due to the diversity of hardware features and software stacks. The Co-design Center for Particle Applications (CoPA) has developed and enhanced the Cabana and PROGRESS/BML libraries to facilitate the creation of new particle applications, make existing particle applications exascale capable, and allow teams to explore new capabilities. Particle methods from atomistic, mesoscale, continuum, through cosmological scales have been built with Cabana, along with new possibilities for application coupling. Similarly, the PROGRESS/BML library has enabled quantum particle applications with linear algebra solvers to use advanced hardware. Across these CoPA-developed libraries, the co-design abstraction layer combines performance portability with math library support to facilitate separation of concerns and directly support science runs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1966

Science subsystem

Instrumentation of science subsystem of Mariner- Mars 1964 mission - data collection instruments and data processing

SPACECRAFT INSTRUMENTATION↗
NASA NTRS1973

The deep space network, volume 13

The objectives, functions, and organization of the Deep Space Network are summarized. The deep space instrumentation facility, the ground communications facility, and the network control system are described. Other areas reported include: Helios Mission support, DSN support of the Mariner Mars 1971 extended mission, Mariner Venus/Mercury 1973 mission support, Viking mission support, radio science, tracking and ground-based navigation, network control and data processing, and deep space stations.

Source record↗
NASA NTRS1975

Apollo-Soyuz test project

Experiments proposed for the Apollo-Soyuz space mission are discussed. Data focus of space processing and manufacturing, earth surveys, and life sciences. Special efforts were made to test the compatibility of the rendezvous and docking systems for manned spacecraft. Mission planning programs, personnel training, and spacecraft modifications for both spacecraft are included.

Source record↗
NASA NTRS1984

Introduction to Long-Duration Exposure Facility

A description of the structure and uses of the Long Duration Exposure Facility (LDEF) is given. The LDEF was designed to provide a large number of economical opportunities for science and technology experiments that require modest electrical power and data processing while in space and which benefit from postflight laboratory investigations with the retrieved experiment hardware. Like the Shuttle, the LDEF is reusable, and repeat missions are planned, each with a new complement of experiments. The LDEF is essentially a free-flying cylindrical structure. The experiments on LDEF are totally self-contained in trays mounted on the exterior of the structure. LDEF can accommodate 86 experiment trays, 72 around the circumference and 14 on the two ends. The LDEF is delivered to Earth orbit by the Shuttle. In orbit, the Shuttle remote manipulator system removes the LDEF from the Shuttle payload bay and places it in a gravity-gradient-stabilized attitude. After an extended period in orbit, which is set by experiment requirements, the LDEF is retrieved on a subsequent Shuttle flight.

Kinard, W. H.↗
NASA NTRS1999

High Data Rate Instrument Study

The High Data Rate Instrument Study was a joint effort between the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC). The objectives were to assess the characteristics of future high data rate Earth observing science instruments and then to assess the feasibility of developing data processing systems and communications systems required to meet those data rates. Instruments and technology were assessed for technology readiness dates of 2000, 2003, and 2006. The highest data rate instruments are hyperspectral and synthetic aperture radar instruments which are capable of generating 3.2 Gigabits per second (Gbps) and 1.3 Gbps, respectively, with a technology readiness date of 2003. These instruments would require storage of 16.2 Terebits (Tb) of information (RF communications case of two orbits of data) or 40.5 Tb of information (optical communications case of five orbits of data) with a technology readiness date of 2003. Onboard storage capability in 2003 is estimated at 4 Tb; therefore, all the data created cannot be stored without processing or compression. Of the 4 Tb of stored data, RF communications can only send about one third of the data to the ground, while optical communications is estimated at 6.4 Tb across all three technology readiness dates of 2000, 2003, and 2006 which were used in the study. The study includes analysis of the onboard processing and communications technologies at these three dates and potential systems to meet the high data rate requirements. In the 2003 case, 7.8% of the data can be stored and downlinked by RF communications while 10% of the data can be stored and downlinked with optical communications. The study conclusion is that only 1 to 10% of the data generated by high data rate instruments will be sent to the ground from now through 2006 unless revolutionary changes in spacecraft design and operations such as intelligent data extraction are developed.

Schober, Wayne↗
NASA NTRS2004

Wavefront Sensing using a Multi-Object Spectrograph (NIRSpec)

An analysis is presented that illustrates how the JWST fine-phasing process can be carried out using NIRSpec data collected at the science focal plane. The analysis is based on a multi-plane diffraction model which properly accounts for the microshutter diffractive element placed at the first relay position of the spectrograph. Wavefront sensing results are presented based on both simulated as well as real data collected from the NASA Goddard Microshutter Testbed.

Dean, Bruce↗