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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

A compact and low power coherent optical system for on-board spacecraft data processing.

Discussion of the design and performance of a compact low-power coherent optical data processing system suitable for spacecraft onboard applications. The system is a modification of the conventional optical data processing system in which a much more efficient solid state GaAs laser is substituted for the bulky and inferior He-Ne laser and paraboloidal mirror segments are substituted for the axially symmetric optical system of the conventional data processing system. Theoretical considerations are given to substantiate the improvement of performance aimed at in the modified system. Preliminary tests of the modified design being in progress indicate that a low power, rugged, small size optical system, capable of onboard spacecraft data processing, can be constructed by using off-axis paraboloidal mirror segments.-

Husain-Abidi, A. S.↗
DOE OSTI2024

HERO WEC V1 Upgrade - 2023 Laboratory Testing (processed data)

The following submission includes processed laboratory data from NREL's Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), in the form of MATLAB workspaces. This dataset was created using NREL's Large Amplitude Motion Platform (LAMP) and collected between August and September 2023. Included with this submission is a test log of all the processed data "HERO WEC LAMP test run log.xlsx" so that the user can easily find the data of interest. Additionally, more detailed descriptions of the type of data and how it was processed, or calculated, can be found in the document titled "Lamp Data Description.docx". The MATLAB workspaces can be visualized using the file "LAMP_Data_Viewer_Ver2.m/mlx". The user simply needs to upload the workspace of interest and run the file "LAMP_Data_Viewer_Ver2.m/mlx". Both the .m and .mlx file format has been provided depending on the user's preference. The MATLAB workspaces have been separated into zip files corresponding to either Drivetrain, Hydraulic, or Electric configuration runs representing the respective test cases that were run. The drivetrain runs were used to characterize the drivetrain only (no pump or generator). The Hydraulic runs represent the configuration when the seawater pump is installed, and the Electric runs represents the configuration when the generator is installed. The following sub-categories of data are included for each type: - DW - Deep water sine wave profile (not run in drivetrain configuration) - Heave - Heave only sine wave profile - Heave_NoRO (hydraulic configuration only) - Heave_ACC (hydraulic configuration only) - IR - Surge and heave irregular wave profile (not run in drivetrain configuration) - RW - Heave only profile created from real world encoder data (not run in drivetrain configuration) For those interested in the raw, unprocessed, data the authors have created a separate submission, linked below. This submission includes the raw TDMS files and associated files necessary to translate the data into either python or MATLAB formats. This data set has been developed by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗
NASA NTRS1980

The Seasat low rate data processing system

The development of the algorithms for data processing and distribution, the circuitry, and the performance of the Seasat low rate data processing system are reviewed. The system controls data from the radar altimeter, scatterometer, microwave radiometer, and the visible and IR radiometer for independent transmission of each instrument's readings. The downlink operates at 25 kb/sec, and a yearlong program of geophysical evaluation proceeded shortly after launch, allowing on-line engineering evaluation and alteration of the control algorithms in the system. Some data is preformatted for immediate distribution and storage in archival quality. A catalog and abstracts are provided to users allowing a RAM search from remote terminals for historical conditions. Procedures for verifying and altering the algorithms are detailed.

Brown, J. W.↗
NASA NTRS2004

Science Data Processing for the Advanced Microwave Scanning Radiometer: Earth Observing System

The National Aeronautics and Space Administration established the framework for the Science Investigator-led Processing Systems (SIPS) to enable the Earth science data products to be produced by personnel directly associated with the instrument science team and knowledgeable of the science algorithms. One of the first instantiations implemented for NASA was the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) SIPS. The AMSR-E SIPS is a decentralized, geographically distributed ground data processing system composed of two primary components located in California and Alabama. Initial science data processing is conducted at Remote Sensing Systems (RSS) in Santa Rosa, California. RSS ingests antenna temperature orbit data sets from JAXA and converts them to calibrated, resampled, geolocated brightness temperatures. The brightness temperatures are sent to the Global Hydrology and Climate Center in Huntsville, Alabama, which generates the geophysical science data products (e.g., water vapor, sea surface temperature, sea ice extent, etc.) suitable for climate research and applications usage. These science products are subsequently sent to the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado for archival and dissemination to the at-large science community. This paper describes the organization, coordination, and production techniques employed by the AMSR-E SIPS in implementing, automating and operating the distributed data processing system.

Goodman, H. Michael↗
NASA NTRS1987

Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development

Spacelab Data Processing Facility (SLDPF) expert system prototypes have been developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. SLDPF functions include the capturing, quality monitoring, processing, accounting, and forwarding of mission data to various user facilities. Prototypes for the two SLDPF functional elements, the Spacelab Output Processing System and the Spacelab Input Processing Element, are described. The prototypes have produced beneficial results including an increase in analyst productivity, a decrease in the burden of tedious analyses, the consistent evaluation of data, and the providing of concise historical records.

Kelly, Angelita C.↗
NASA NTRS1987

Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development

Spacelab Data Processing Facility (SLDPF) expert system prototypes were developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. The SLDPF functions include the capturing, quality monitoring, processing, accounting, and forwarding of mission data to various user facilities. Prototypes for the two SLDPF functional elements, the Spacelab Output Processing System and the Spacelab Input Processing Element, are described. The prototypes have produced beneficial results including an increase in analyst productivity, a decrease in the burden of tedious analyses, the consistent evaluation of data, and the providing of concise historical records.

Kelly, Angelita C.↗
NASA NTRS1980

Data processing system for the Sneg-2MP experiment

The data processing system for scientific experiments on stations of the "Prognoz" type provides for the processing sequence to be broken down into a number of consecutive stages: preliminary processing, primary processing, secondary processing. The tasks of each data processing stage are examined for an experiment designed to study gamma flashes of galactic origin and solar flares lasting from several minutes to seconds in the 20 kev to 1000 kev energy range.

Gavrilova, Y. A.↗
NASA NTRS1984

Technology for the product and process data base

The computerized product and process data base is increasingly recognized to be the cornerstone component of an overall system aimed at the integrated automation of the industrial processes of a given company or enterprise. The technology needed to support these more effective computer integrated design and manufacturing methods, especially the concept of 3-D computer-sensible product definitions rather than engineering drawings, is not fully available and rationalized. Progress is being made, however, in bridging this technology gap with concentration on the modeling of sophisticated information and data structures, high-performance interactive user interfaces and comprehensive tools for managing the resulting computerized product definition and process data base.

Barnes, R. D.↗
NASA NTRS1973

Evolution of the satellite telemetry data processing facility at the Goddard Space Flight Center.

Data from scientific and application satellites managed by the NASA Goddard Space Flight Center are acquired through the world-wide Spacecraft Tracking and Data Network (STDN). These data are forwarded to a central telemetry data processing facility whose primary objective is the timely provision of the data to users in a form suitable for their analysis. In a successful evolution, a satellite data processing facility must adapt to changing support requirements while operationally supporting active spacecraft. Advances in the technology of data transmission, data storage systems, and file management make it feasible to implement a third-generation system which will be able to satisfy experimenter requirements for the next ten years.

Keipert, F. A.↗
NASA NTRSDate not supplied

Performance Analysis and Data Processing for the Mars Sample Recovery Helicopter in the Jet Propulsion Laboratory 25-ft Space Simulator

On April 19, 2021, Ingenuity became the first helicopter to fly on Mars at Jezero Crater, completing a total of 72 flights by the end of its mission. The success of Ingenuity resulted in various research efforts to further explore Mars via vertical flight, including two optimized Ingenuity-sized helicopters proposed to retrieve samples for the 2028 Mars Sample Return mission. To aid in the design process for the two proposed Sample Retrieval Helicopters, both heritage and optimized, increased diameter rotors were tested at the NASA Jet Propulsion Laboratory in the 25-ft Space Simulator. Three test campaigns were performed using the Ingenuity rotors and optimized Sample Retrieval Helicopter (SRH) rotors for several rotor speeds, densities, configurations, and collectives to identify performance limitations. These three test campaigns included the Ingenuity Engineering Design Model 1 (EDM-1) with and without a cruciform box, Transonic Rotor Test (TRT) rig, and SRH Dual Rotor Test (DRT). Experimental setup, test matrix, data processing, data quality, and performance results for EDM-1, TRT, and DRT campaigns are presented and discussed. Experimental results from the test campaigns will aid in future experimental methods and validation efforts for planetary rotorcraft exploration.

Data Processing↗
NASA NTRS1992

Science data processing in the Mission to Planet Earth era

The data-processing systems developed to support NASA's Mission to Planet Earth (MPE) are described in an overview of the system architectures. The MPE program is discussed in terms of flight segments and data types to examine the required elements of the information systems. The data-processing segments are described for the Atmospheric Laboratory for Applications and Science, the Tropical Rainfall Measuring Mission, the Earth Observing System, and the Geostationary Earth Observatory. The data and information systems for the separate segments provide some redundant processing services. Distributed active archive centers are employed for each segment composed of three subelements: (1) a product-generation system, (2) a data archive and distribution system, and (3) an information management system. The data processing design for the MPE is expected to facilitate the understanding of the entire earth system on a global scale.

Goodman, H. M.↗
NASA NTRS1988

Radar-Data-Processing System

Report describes radar data system at NASA Western Aeronautical Test Range. System provides real-time and recorded data about flightpaths of research aircraft and Space Shuttle. Called RADATS, processes data from three radars simultaneously; interacts with system operator; enhances data by introducing corrections and smoothing; controls range, azimuth, and elevation of radars; and automatically calibrates itself before and after missions. Software classified into three kinds of programs: utility, real-time, and calibration. Equipment exhibited exceptional reliability. Software matured to become virtually trouble-free.

Anderson, Karl F.↗
NASA NTRS2011

The New Web-Based Hera Data Processing System at the HEASARC

The HEASARC at NASA/GSFC has provide an on-line astronomical data processing system called Hera for several years. Hera provides a complete data processing environment, including installed software packages, local data storage, and the CPU resources needed to process the user's data. The original design of Hera, however, has 2 requirements that has limited it's usefulness for some users, namely, that 1) the user must download and install a small helper program on their own computer before using Hera, and 2) Hera requires that several computer ports/sockets be allowed to communicate through any local firewalls on the users machine. Both of these restrictions can be problematic for some users, therefore we are now migrating Hera into a purely Web based environment which only requires a standard Web browser. The first release of Web Hera is now publicly available at http://heasarc.gsfc.nasa.gov/webheara/. It currently provides a standard graphical interface for running hundreds of different data processing programs that are available in the HEASARC's ftools software package. Over the next year we to add more features to Web Hera, including an interactive command line interface, and more display and line capabilities.

Pence, W.↗
NASA NTRSDate not supplied

Earth Science Data Processing With Nextflow

Earth science data processing tasks present many challenges. These tasks often process large input datasets and require scores of CPU-hours to generate results. All but the simplest tasks will be decomposed into a series of computational or data manipulation steps, also known as a scientific workflow. In order to reduce the burden of orchestrating and running the dependent processing steps, a workflow execution engine is required. This poster describes the lessons learned by the CLARREO Pathfinder (CPF) team while developing multiple scientific workflows and utilizing the open-source Nextflow engine to execute them in a cloud computing environment. The Nextflow engine is designed with the following stated goals: first, the engine does not dictate how individual steps in the task are implemented (i.e. it is language and interface agnostic); second, the engine supports easy configuration and modularity at the workflow level so that others can easily execute our workflows to reproduce results; lastly, the engine eases development by transparently scaling execution from local to remote environments. Nextflow was developed for the bioinformatics domain but is a good fit for other scientific workflows where the overall task is well-described by a dataflow diagram. The CPF team has developed Nextflow pipelines (i.e. scientific workflows) to simulate CLARREO radiance, generate large look-up tables for inter-calibration algorithms, and generate L4 intercalibration data products. These pipelines consume from single-digits to hundreds of thousands of CPU-hours. In the development and evolution of these pipelines we have discovered many design patterns, pitfalls, and solutions to common problems. Our goal is to demonstrate important aspects of how to design, implement, run, and ultimately share Nextflow pipelines in the domain of Earth science.

Aron D Bartle↗
NASA NTRS1986

A radar data processing and enhancement system

This report describes the space position data processing system of the NASA Western Aeronautical Test Range. The system is installed at the Dryden Flight Research Facility of NASA Ames Research Center. This operational radar data system (RADATS) provides simultaneous data processing for multiple data inputs and tracking and antenna pointing outputs while performing real-time monitoring, control, and data enhancement functions. Experience in support of the space shuttle and aeronautical flight research missions is described, as well as the automated calibration and configuration functions of the system.

Anderson, K. F.↗