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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Edward Lawrence Powers, Jr. December 30, 1915 - August 1, 2005; In Memorium: "It is only needed to say that he was a man ahead of his time, a man who led radiation research in all that he did." Michael G. Simic, Ph.D., D.Sc.; August, 2005

Larry Powers was a man of commitment: to roots, family, science, and large appetites. He grew up in Charleston, South Carolina, during the Great Depression that defined his remarkable work ethic and value for contribution. He graduated from the municipal College of Charleston in 1938 with majors in biology, chemistry, and mathematics. That same year, he married his wife Elly of Charleston, with whom he had seven daughters by the early years of his eras of discovery in 1959. He was awarded an Honorary Doctor of Letters from the College of Charleston in 1974, and retired there with Elly in 1987 as a Professor in Residence. Having obtained his Ph.D. from Johns Hopkins University in genetics and protozoology (1941), and having begun his professional career at the University of Notre Dame (Instructor and Assistant Professor, 1941-1945), Larry was often heard to comment on traditions of excellence in education and football, with adamant priority given to the first but without allowance for failure in the second.

Richmond, Robert C.↗
NASA NTRS2017

New Understanding of Hubble Space Telescope Gyro Current Increase Led to a Method to Save a Failing Gyro

Throughout the history of the Hubble Space Telescope (HST) program, gyro current increases have been observed to occur, oftentimes leading to gyro failure. The explanation was that debris from the surfaces of the gas bearings, with only 50 millionths on an inch clearance, resulted in rotor restriction, which increased friction, torque, and current. However, the rotor restriction theory never could account for the fact that a restart of the gyro would restore the current back to nominal. An effort was made to understand this puzzling gyro behavior after two HST gyros exhibited increased current within the same week in November 2015. A review board was created to resolve these anomalies and generate operational procedures to potentially extend gyro life.

Mechanism↗
NASA NTRS2014

Accurately Measuring the Color of the Ocean on Earth and from Space: Uncertainties Revisited and A Report from the Community-Led Spectral Absorption Workshop to Update and Revise the NASA Inherent Optical Properties Protocol

The color of the ocean (apparent optical properties or AOPs) is determined by the spectral scattering and absorption of light by its dissolved and particulate constituents.The absorption and scattering properties of the water column are the so-called inherent optical properties.

protocol↗
NASA NTRS2018

The InSAR Scientific Computing Environment 3.0: A Flexible Framework for NISAR Operational and User-Led Science Processing

The InSAR Scientific Computing Environment (ISCE) was first developed under the NASA Advanced Information Systems Technology as a flexible, extensible object-oriented framework for Interferometric Synthetic Aperture Radar (InSAR) processing. The ISCE framework uses Python 3 at the workflow level, controlling modules of compiled code for functional processing, and managing inputs, outputs, and other flow control services. The currently released version, called ISCE 2.1, is distributed to the research community through the Western North America InSAR Consortium under a research license. The ISCE team is working on the next generation of the code in order to prepare for the NASAISRO SAR (NISAR) mission operational processing. Innovations in this code include augmentation or conversion of the custom Python framework elements in ISCE with the Pyre framework, new workflows for interferometric and polarimetric stack processing, a more intuitive and graphically based user interface, and flow control for hybrid computing environments including CPU/GPU clusters, logging and error tracking facilities, and new more efficient computational modules that exploit graphical processor units (GPUs) when available. The ISCE 3.0 framework is designed to work in an operational environment as well as on a single user’s laptop or compute cluster, with services to discover capabilities and scale computations accordingly.

Buckley, Sean M.↗
NASA NTRS2022

Megafires in a Warming World: What Wildfire Risk Factors Led to California’s Largest Recorded Wildfire

Massive wildfires and extreme fire behavior are becoming more frequent across the westernUnited States, creating a need to better understand how megafire behavior will evolve in our warmingworld. Here, the fire spread model Prometheus is used to simulate the initial explosive growth ofthe 2020 August Complex, which occurred in northern California (CA) mixed conifer forests. Hightemperatures, low relative humidity, and daytime southerly winds were all highly correlated withextreme rates of modeled spread. Fine fuels reached very dry levels, which accelerated simulationgrowth and heightened fire heat release (HR). Model sensitivity tests indicate that fire growth andHR are most sensitive to aridity and fuel moisture content. Despite the impressive early observedgrowth of the fire, shifting the simulation ignition to a very dry September 2020 heatwave predicted a>50% increase in growth and HR, as well as increased nighttime fire activity. Detailed model analysesof how extreme fire behavior develops can help fire personnel prepare for problematic ignitions.

Kevin Varga↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗
NASA NTRSDate not supplied

Information Systems for Crew-Led Operations Beyond Low-Earth Orbit

On past and present human space missions, the management of vehicle health and status has primarily been executed from Earth. Missions such as Apollo, Space Shuttle, and ISS have relied on a safety net of ground-based experts with access to real-time telemetry data, broad and deep systems expertise, and powerful analytical and computing capabilities. The ground team monitors and manages the vehicle’s health in real-time and responds quickly to critical situations and malfunctions. Ground operators also provide real-time oversight and verbal guidance to flight crew members, especially during complex procedure execution and high-risk activities like extra-vehicular activities. However, this operational paradigm, in place for 60 years, will not transfer to long duration exploration missions beyond low Earth orbit (LEO). Lunar and deep-space crewed missions will encounter delayed communications that prohibit real-time operational and medical support. Additionally, there will be infrequent resupply and a diminished capacity to evacuate or rescue crew members. A small crew must operate independently, managing the vehicle’s state, responding to time-critical events, and executing complex procedures, all without the safety net of real-time support.

data representation↗