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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Caltech/JPL Conference on Image Processing Technology, Data Sources and Software for Commercial and Scientific Applications

Recent advances in image processing and new applications are presented to the user community to stimulate the development and transfer of this technology to industrial and commercial applications. The Proceedings contains 37 papers and abstracts, including many illustrations (some in color) and provides a single reference source for the user community regarding the ordering and obtaining of NASA-developed image-processing software and science data.

Redmann, G. H.↗
NASA NTRS2019

Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data

Earth Science satellite missions provide a unique opportunity for scientists to visualize complex and multifaceted observations projected geospatially across maps of the Earth. While visualization tools can help scientists comprehend, analyze, and share data, visualizing Level-2 Earth Sciences data poses its own specific set of challenges. Since the geospatial information in Level-2 data files is stored as independent variables, the plotting process involves matching dimensional information from latitude and longitude with a desired variable. Variables are stored in different ways across various Earth Science data file formats, which complicates the process of extracting data and plotting variables from a given file without requiring extensive user input and prerequisite familiarity with the file type variable structure. In coordination with NASA’s Goddard Earth Sciences Data Information Services Center (GES DISC), the team developed a Level-2 Earth Science data visualization tool that aims to address some of the complexities associated with plotting Level-2 data. This tool offers command-line and user interface support for file and variable selection to accommodate varying use cases and degrees of user familiarity with the structure of a given file. The visualization tool is written in Python 3 and utilizes a modular approach to facilitate continued expansion and reuse. In addressing some common complications involved in plotting Level-2 Earth Sciences data, the tool aims to help to link the process of analysis more directly with data acquisition and visualization, bringing analysis closer to data across levels of processing.

Li, Angela W.↗
NASA NTRS2012

The Kepler End-to-End Data Pipeline: From Photons to Far Away Worlds

The Kepler mission is described in overview and the Kepler technique for discovering exoplanets is discussed. The design and implementation of the Kepler spacecraft, tracing the data path from photons entering the telescope aperture through raw observation data transmitted to the ground operations team is described. The technical challenges of operating a large aperture photometer with an unprecedented 95 million pixel detector are addressed as well as the onboard technique for processing and reducing the large volume of data produced by the Kepler photometer. The technique and challenge of day-to-day mission operations that result in a very high percentage of time on target is discussed. This includes the day to day process for monitoring and managing the health of the spacecraft, the annual process for maintaining sun on the solar arrays while still keeping the telescope pointed at the fixed science target, the process for safely but rapidly returning to science operations after a spacecraft initiated safing event and the long term anomaly resolution process.The ground data processing pipeline, from the point that science data is received on the ground to the presentation of preliminary planetary candidates and supporting data to the science team for further evaluation is discussed. Ground management, control, exchange and storage of Kepler's large and growing data set is discussed as well as the process and techniques for removing noise sources and applying calibrations to intermediate data products.

data archiving↗
NASA NTRS2014

Prototype and Metrics for Data Processing Chain Components of IPM

This presentation lays out the evolution of the Intelligent Payload Module (IPM) vision given that the HyspIRI mission has been delayed. It shows that there has been a focus on airborne vehcile and unmanned aerial systems to further develop the IPM functionality. This of course does not preclude use of the IPM for space missions but provides alternate paths to continue the concept of improved onboard processing for low latency users of science data products.

Onboard Processing↗
DOE OSTI2026

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗
NASA NTRS1988

Artificial intelligence in a mission operations and satellite test environment

A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

Busse, Carl↗
NASA NTRS1990

Small business innovation research. Abstracts of 1988 phase 1 awards

Non-proprietary proposal abstracts of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA are presented. Projects in the fields of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robots, computer sciences, information systems, data processing, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered.

Source record↗
NASA NTRS1999

Earth Orbiter 1 (EO-1): Wideband Advanced Recorder and Processor (WARP)

An overview of the Earth Orbitor 1 (EO1) Wideband Advanced Recorder and Processor (WARP) is presented in viewgraph form. The WARP is a spacecraft component that receives, stores, and processes high rate science data and its associated ancillary data from multispectral detectors, hyperspectral detectors, and an atmospheric corrector, and then transmits the data via an X-band or S-band transmitter to the ground station. The WARP project goals are: (1) Pathfinder for next generation LANDSAT mission; (2) Flight prove architectures and technologies; and (3) Identify future technology needs.

Smith, Terry↗
NASA NTRS2003

A Distributed Simulation Software System for Multi-Spacecraft Missions

The paper will provide an overview of the web-based distributed simulation software system developed for end-to-end, multi-spacecraft mission design, analysis, and test at the NASA Goddard Space Flight Center (GSFC). This software system was developed for an internal research and development (IR&D) activity at GSFC called the Distributed Space Systems (DSS) Distributed Synthesis Environment (DSE). The long-term goal of the DSS-DSE is to integrate existing GSFC stand-alone test beds, models, and simulation systems to create a "hands on", end-to-end simulation environment for mission design, trade studies and simulations. The short-term goal of the DSE was therefore to develop the system architecture, and then to prototype the core software simulation capability based on a distributed computing approach, with demonstrations of some key capabilities by the end of Fiscal Year 2002 (FY02). To achieve the DSS-DSE IR&D objective, the team adopted a reference model and mission upon which FY02 capabilities were developed. The software was prototyped according to the reference model, and demonstrations were conducted for the reference mission to validate interfaces, concepts, etc. The reference model, illustrated in Fig. 1, included both space and ground elements, with functional capabilities such as spacecraft dynamics and control, science data collection, space-to-space and space-to-ground communications, mission operations, science operations, and data processing, archival and distribution addressed.

Burns, Richard↗
NASA NTRS2003

An Internet Protocol-Based Software System for Real-Time, Closed-Loop, Multi-Spacecraft Mission Simulation Applications

The paper will provide an overview of the web-based distributed simulation software system developed for end-to-end, multi-spacecraft mission design, analysis, and test at the NASA Goddard Space Flight Center (GSFC). This software system was developed for an internal research and development (IR&D) activity at GSFC called the Distributed Space Systems (DSS) Distributed Synthesis Environment (DSE). The long-term goal of the DSS-DSE is to integrate existing GSFC stand-alone test beds, models, and simulation systems to create a "hands on", end-to-end simulation environment for mission design, trade studies and simulations. The short-term goal of the DSE was therefore to develop the system architecture, and then to prototype the core software simulation capability based on a distributed computing approach, with demonstrations of some key capabilities by the end of Fiscal Year 2002 (FY02). To achieve the DSS-DSE IR&D objective, the team adopted a reference model and mission upon which FY02 capabilities were developed. The software was prototyped according to the reference model, and demonstrations were conducted for the reference mission to validate interfaces, concepts, etc. The reference model, illustrated in Fig. 1, included both space and ground elements, with functional capabilities such as spacecraft dynamics and control, science data collection, space-to-space and space-to-ground communications, mission operations, science operations, and data processing, archival and distribution addressed.

Davis, George↗
NASA NTRS2008

Lights Out Operations of a Space, Ground, Sensorweb

We have been operating an autonomous, integrated sensorweb linking numerous space and ground sensors in 24/7 operations since 2004. This sensorweb includes elements of space data acquisition (MODIS, GOES, and EO-1), space asset retasking (EO-1), integration of data acquired from ground sensor networks with on-demand ground processing of data into science products. These assets are being integrated using web service standards from the Open Geospatial Consortium. Future plans include extension to fixed and mobile surface and subsurface sea assets as part of the NSF's ORION Program.

Chien, Steve↗
NASA NTRS2023

PACE Technical Report Series, Volume 11: The PACE Postlaunch Airborne eXperiment (PACE-PAX)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission is NASA's latest and greatest effort to study the ocean-atmosphere system and build upon the legacy of previous satellite missions that have revolutionized our understanding of our home planet. By using advanced radiometric and polarimetric instruments to measure ocean color and key atmospheric variables, PACE aims to provide new insights into the complex interactions between the ocean, atmosphere, and biosphere. This information will be critical for improving our ability to model and predict changes in the Earth's climate, as well as to manage and conserve our planet's valuable natural resources. Performance assessments and science data product validation is a critical process for any Earth Science space-borne mission, as it involves assessing and verifying the quality of the data products generated by the mission while it is in orbit, as well as assigning uncertainties to these retrievals. More specifically, validation efforts are essential for assessing the accuracy of instrument data and the derived science products across varied spatial and temporal scales and ensuring their reliability and consistency with the mission's scientific goals and objectives. The overall plan for validation of PACE data is described in “PACE Science Data Product Validation Plan” (see, e.g., https://pace.gsfc.nasa.gov), and among range of post-launch activities, it describes the need and requirements for a post-launch airborne field campaign in support of PACE validation. This volume outlines the plans and requirements of the PACE Postlaunch Airborne eXperiment (PACE-PAX). The main goal of PACE-PAX is to gather validation and assessment data for the PACE mission, using a variety of airborne and ground-based assets. These assets will be coordinated to obtain complementary measurements of key ocean and atmospheric variables, such as ocean color, aerosols, and clouds. By collecting data from multiple sources, PACE-PAX will help to validate and refine the data products generated by the PACE mission, as well as to identify any potential errors or biases in the measurements. This will be essential for ensuring the accuracy and reliability of the PACE data products, and for maximizing the scientific value of the mission.

Kirk D Knobelspiesse↗
NASA NTRS1992

Multi-frequency multi-polarization processing for spaceborne SAR

The Shuttle Imaging Radar-C (SIR-C) is the third in a series of space shuttle based synthetic aperture radars (SAR) sponsored by the National Aeronautics and Space Administration (NASA). The SIR-C ground data processing system is to process the playbacked SAR signal data into a variety of data products for distribution to the science community. An overview of the end-to-end ground data processing system with emphasis on the unique characteristics involved in the system design is presented. Included in the discussion are science requirements, radar system specifications, input data format specifications, system operations design, data products design, processing algorithm design, hardware architecture design, and software design.

Curlander, John C.↗
NASA NTRSDate not supplied

Lunar Gateway Charging and Effects on Low-Energy Electron Measurements

The Electron Electrostatic Analyzer (EEA) is part of the HERMES instrument suite on Lunar Gateway and is designed to measure electrons in the energy range from 1 eV to 18 keV. Electrons in this range can be deflected or blocked from entering a detector by electric fields from a charged spacecraft platform, so many heliophysics missions (MMS, Cluster, etc.) use active potential control to minimize stray electric fields which would corrupt low-energy plasma measurements. Gateway, however, does not have such capabilities so the surface charging effects will influence the electron data. Further, some elements of Gateway partially block the instrument’s field of view to space. The effects of the Gateway platform on the low-energy electron population must be understood to maximize the accuracy of the EEA data. To investigate the electrostatic environment near Gateway and its effects on the EEA measurements, we use Nascap-2K to model the expected charging of Gateway under representative solar wind, magnetosheathic, and magnetospheric conditions. Next, we use the potential and electric field outputs from Nascap-2K along with in-house particle tracing codes to investigate how low-energy electrons are perturbed, blocked, or deflected by the spacecraft. We discuss how these perturbations impact the plasma moments computed from the EEA data and possible approaches for correcting the charging effects including application of advanced methods such as neural networks. In addition to electrons from the space environment being influenced by the electrostatic environment around Gateway, photoelectrons generated on Gateway surfaces will also be measured by EEA. We are investigating how knowledge of the potentials of various Gateway surfaces can be extracted from these measured photoelectrons using advanced numerical modeling and analysis. Such information would be valuable for validating charging models and planning mission operations around the platform. Finally, we discuss how the specific workflow developed for Gateway can be extended to a generalized process that is applicable to other future missions. As the space industry prepares for human exploration beyond low-Earth orbit, the need to obtain accurate space weather data from rideshare science payloads is critical. Our process for removing platform effects from the science data serves as a pathfinder for leveraging advanced simulations to maximize science returns and ensure the safety and success of future crewed missions.

Miles Bengtson↗
NASA NTRS2001

Earth Science System of the Future: Observing, Processing, and Delivering Data Products Directly to Users

Advancement of our predictive capabilities will require new scientific knowledge, improvement of our modeling capabilities, and new observation strategies to generate the complex data sets needed by coupled modeling networks. New observation strategies must support remote sensing from a variety of vantage points and will include "sensorwebs" of small satellites in low Earth orbit, large aperture sensors in Geostationary orbits, and sentinel satellites at L1 and L2 to provide day/night views of the entire globe. Onboard data processing and high speed computing and communications will enable near real-time tailoring and delivery of information products (i.e., predictions) directly to users.

Crisp, David↗
NASA NTRS1993

Mission operations update for the restructured Earth Observing System (EOS) mission

The National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS) will provide a comprehensive long term set of observations of the Earth to the Earth science research community. The data will aid in determining global changes caused both naturally and through human interaction. Understanding man's impact on the global environment will allow sound policy decisions to be made to protect our future. EOS is a major component of the Mission to Planet Earth program, which is NASA's contribution to the U.S. Global Change Research Program. EOS consists of numerous instruments on multiple spacecraft and a distributed ground system. The EOS Data and Information System (EOSDIS) is the major ground system developed to support EOS. The EOSDIS will provide EOS spacecraft command and control, data processing, product generation, and data archival and distribution services for EOS spacecraft. Data from EOS instruments on other Earth science missions (e.g., Tropical Rainfall Measuring Mission (TRMM)) will also be processed, distributed, and archived in EOSDIS. The U.S. and various International Partners (IP) (e.g., the European Space Agency (ESA), the Ministry of International Trade and Industry (MITI) of Japan, and the Canadian Space Agency (CSA)) participate in and contribute to the international EOS program. The EOSDIS will also archive processed data from other designated NASA Earth science missions (e.g., UARS) that are under the broad umbrella of Mission to Planet Earth.

Kelly, Angelita Castro↗
NASA NTRS2007

Processing AIRS Scientific Data Through Level 2

The Atmospheric Infrared Spectrometer (AIRS) Science Processing System (SPS) is a collection of computer programs, denoted product generation executives (PGEs), for processing the readings of the AIRS suite of infrared and microwave instruments orbiting the Earth aboard NASA s Aqua spacecraft. AIRS SPS at an earlier stage of development was described in "Initial Processing of Infrared Spectral Data' (NPO-35243), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 39. To recapitulate: Starting from level 0 (representing raw AIRS data), the PGEs and their data products are denoted by alphanumeric labels (1A, 1B, and 2) that signify the successive stages of processing. The cited prior article described processing through level 1B (the level-2 PGEs were not yet operational). The level-2 PGEs, which are now operational, receive packages of level-1B geolocated radiance data products and produce such geolocated geophysical atmospheric data products such as temperature and humidity profiles. The process of computing these geophysical data products is denoted "retrieval" and is quite complex. The main steps of the process are denoted microwave-only retrieval, cloud detection and cloud clearing, regression, full retrieval, and rapid transmittance algorithm.

Oliphant, Robert↗