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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Mission leverage education: NSU/NASA innovative undergraduate model

The BEST Lab (Center for Excellence in Science Education), the Center for Materials Research (CMR), and the Chemistry, Mathematics, Physics, and Computer Science (CS) Departments at Norfolk State University (NSU) joined forces to implement MiLEN(2) IUM - an innovative approach tu integrate current and emerging research into the undergraduate curricula and train students on NASA-related fields. An Earth Observing System (EOS) mission was simulated where students are educated and trained in many aspects of Remote Sensing: detector physics and spectroscopy; signal processing; data conditioning, analysis, visualization; and atmospheric science. This model and its continued impact is expected to significantly enhance the quality of the Mathematics, Science, Engineering and Technology (MSET or SMET) educational experience and to inspire students from historically underrepresented groups to pursue careers in NASA-related fields. MiLEN(2) IUM will be applicable to other higher education institutions that are willing to make the commitment to this endeavor in terms of faculty interest and space.

Chaudhury, S. Raj↗
NASA NTRS2000

VCL Laser Altimeter Surface Return Expected Geolocation Performance

The Vegetation Canopy Lidar (VCL) mission, expected to launch in the spring of 2002, will carry a unique Multi-Beam Laser Altimeter (MBLA) instrument designed to observe vegetative canopy structure for a nominal mission duration of 2 years. The VCL MBLA is a three-beam instrument where each laser is capable of producing returns with 30-m along-track spacing and 25-m-diameter footprints. Identifying the precise location of the point on the Earth's surface from which the laser energy reflects is a critical issue in the validation and application of the data. The resultant geolocation accuracy is dependent on the performance of many components of the VCL system including: laser pulse round trip travel time observation to surface, navigation tracking data, attitude determination system data, timing, laser pointing and body orientation stability, knowledge of instrument and navigation tracking point positions, media and geophysical corrections. Additionally, it is critical to calibrate on-orbit instrument parameters including pointing and range corrections. The geolocation and calibration methodology and algorithms will be summarized. A detailed geolocation error analysis identifying the contributions from each system component, along with the resultant expected geolocation accuracy, will be presented. A brief discussion of the operational geolocation process will also be presented. Science and data validation implications from geolocation performance will be summarized.

Luthcke, S. B.↗
NASA NTRS2015

Classifying Floating Potential Measurement Unit Data Products as Science Data

We are Co-Investigators for the Floating Potential Measurement Unit (FPMU) on the International Space Station (ISS) and members of the FPMU operations and data analysis team. We are providing this memo for the purpose of classifying raw and processed FPMU data products and ancillary data as NASA science data with unrestricted, public availability in order to best support science uses of the data.

Coffey, Victoria↗
NASA NTRS2018

Systems and Methods for Advanced Rapid Imaging and Analysis for Earthquakes

Many embodiments provide a hybrid data processing system (HySDS) of an end-to-end geodetic imaging data system enabling near-real-time science, assessment, response, and rapid recovery. The HySDS may be an operation data processing system that integrates data from many different geodetic data sources and/or sensors, including interferometric synthetic aperture radar (InSAR), GPS, pixel tracking, seismology, and/or modeling, and processes the data to generate actionable high quality science data products. The HySDS may provide for an automated imaging and analysis capabilities that is able to handle the imminent increases in raw data from new and existing geodetic monitoring sensor systems.

Owen, Susan Ethel↗
DOE OSTI2024

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗
NASA NTRS2006

LDCM Grid Prototype (LGP)

The LGP successfully demonstrated that grid technology could be used to create a collaboration among research scientists, their science development machines, and distributed data to create a science production system in a nationally distributed environment. Grid technology provides a low cost and effective method of enabling production of science products by the science community. To demonstrate this, the LGP partnered with NASA GSFC scientists and used their existing science algorithms to generate virtual Landsat-like data products using distributed data resources. LGP created 48 output composite scenes with 4 input scenes each for a total of 192 scienes processed in parallel. The demonstration took 12 hours, which beat the requirement by almost 50 percent, well within the LDCM requirement to process 250 scenes per day. The LGP project also showed the successful use of workflow tools to automate the processing. Investing in this technology has led to funding for a ROSES ACCESS proposal. The proposal intends to enable an expert science user to produce products from a number of similar distributed instrument data sets using the Land Cover Change Community-based Processing and Analysis System (LC-ComPS) Toolbox. The LC-ComPS Toolbox is a collection of science algorithms that enable the generation of data with ground resolution on the order of Landsat-class instruments.

Weinstein, Beth↗
NASA NTRS2006

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

This viewgraph presentation reviews the architectural description of the Mission Data Processing and Control System (MPCS). MPCS is an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is designed with these factors (1) Enabling plug and play architecture (2) MPCS has strong inheritance from GDS components that have been developed for other Flight Projects (MER, MRO, DAWN, MSAP), and are currently being used in operations and ATLO, and (3) MPCS components are Java-based, platform independent, and are designed to consume and produce XML-formatted data

Mission Data Processing and Control System (MPCS)↗
NASA NTRS2019

Developing a Machine-Learning-Based Processing Framework for Twitter and Other Crowdsourced Data

Crowdsourced data streams such as Twitter and other social media are important sources of real-time and historical global information for Earth science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we have been exploring the Twitter data stream for its potential in augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. To realize this potential, we need to increase the information density and enhance the quality of filtered precipitation tweets. We have implemented various components of a machine learning (ML)-based processing infrastructure for crowdsourced data that outputs, in this instance, useful and usable information derived from precipitation tweets. We have test enriched the Twitter stream with higher quality active tweets from those knowingly contributing to our effort and from existing crowdsourced programs (e.g., mPING, CoCoRaHS). We have experimented with various algorithms for processing tweets, including Naà ve Bayes, Convolutional Neural Network (CNN), Hierarchical Attention Network (HAN), and semi-supervised learning (with tri-training). Our current work focuses on (1) automated review of Earth science-related publications to determine relationships between discipline research needs and ML algorithms; (2) investigating Sequential Generative Adversarial Network (SeqGAN) for processing precipitation tweets for anomaly detection; and (3) managing crowdsourced data in a way that is compatible with existing NASA satellite data archives and using the data for ML applications. Key results include (1) network visualization of NLP-processed publications in various Earth science disciplines; (2) difference between GPM-linked, generated tweets and collected actual tweets that is small for GPM-determined light to moderate rain cases and high for GPM-determined heavy rain cases; and (3) identification of MongoDB for storing raw tweets and Zarr format for gridded tweets (compatible with GPM data). Our results have taken us a step closer to an operational ML-based tweet processing infrastructure and have already demonstrated that tweet-derived precipitation information is potentially useful for validation of Earth science satellite data.

Teng, William↗
NASA NTRSDate not supplied

Recent Progress at the International Laser Ranging Service (ILRS)

The International Laser Ranging Service (ILRS) is experiencing significant growth. New stations are being built and brought into operation, expanding the spatial and temporal coverage of the Satellite Laser Ranging (SLR) observations. Some of these stations are multi-technique Core Sites that allow us to exploit the combined strengths of different geodetic space techniques. New satellites are strengthening the ILRS contribution to the International Terrestrial Reference Frame (ITRF), and expanding the spectrum of satellite applications supported by the ILRS. New analysis, modeling, and data processing techniques continue to improve the science products. New campaigns are continuing to expand SLR applications into relativity and the study of non-gravitational forces. The ILRS is currently participating in the Galileo for Science campaign (G4S_2.0 project), funded by the Italian Space Agency (ASI), which aims to perform a set of measurements in the field of gravitation with the Galileo satellites, taking advantage of the accuracy of the on-board atomic clocks and, in particular, of GSAT0201and GSAT0202 by exploiting their relatively high eccentricity (~0.16). New activities underway in Lunar Laser Ranging (LLR), with the imminent launch and deployment of the upcoming Next Generation Lunar Retroreflector - 1 (NGLR-1) to the lunar surface. Some new satellites supported by the ILRS are now exploring means of capturing Space Debris, while some ILRS stations run local laser ranging projects to track space debris, contributing to the maintenance of various data catalogs. Time transfer experiments are also expanding the application of laser ranging, linking two fully characterized optical clocks at different locations with SLR (Einstein Synchronization) providing measurements of height differences, demonstrating the feasibility of a physical height system. Two-way and one-way transponders activity has been underway since the LASSO experiment in the 1990’s. More experiments are underway or planned. Applications include time and frequency transfer and clock synchronization between ground and space, interplanetary laser ranging, and fundamental physics. This presentation will give an update on ILRS activities and the impact that these activities have had and will have on ILRS data products.

Lunar Laser Ranging↗
NASA NTRSDate not supplied

Satellite Instrument Calibration

Satellite remote sensing is an integral part of global earth observation. Satellite remote sensing data enable us to observe the whole globe at a reasonably high frequency. To maintain the accuracy of satellite remote sensing data, it is critical to continuously perform instrument calibration throughout the lifetime of the mission. This presentation describes the common characteristics of earth observing satellite sensors, the calibration processes and potential issues, the implication on science data, and how we understand the globe.

calibration↗
DOE OSTI2026

CMIP7 Data Request: atmosphere priorities and opportunities

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data unlocking key research avenues in atmospheric science and provides justification for the resources needed to produce this data. Topics within the CMIP7 Atmosphere Theme centre around processes and feedbacks in atmospheric science such as clouds, aerosols and atmospheric chemistry, atmospheric circulation, temperature variability and extremes, radiative forcings, and Earth system model evaluation. These topics are summarised in this paper as scientific “opportunities” which will be realised through CMIP7 experiments and Earth system model outputs. These opportunities were submitted by a thematic group of atmospheric science community representatives combined with an extended consultation process. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making, including supporting the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). As an author group, we also reflect on the process used to collate this data request and make recommendations to future CMIP governance on implementing a consultation on this scale in the future.

58 GEOSCIENCES↗
NASA NTRS2012

Communicating by Doppler: Detecting Spacecraft Dynamics During Critical Maneuvers

Communicating information from spacecraft in deep space utilizes sophisticated techniques of modulations onto a microwave signal carrier. Under most conditions, there is a high success rate of sending commands to the spacecraft and receiving science data acquired by on-board instruments along with health and status information. There are conditions, however, where the signal dynamics are too high and/or the received signal-to-noise ratio is below the receiver threshold. Under these conditions, often by design and sometimes as a result of planned or unplanned critical maneuvers, events (e.g., orbit insertion or descent and landing), safe mode, etc., it becomes highly critical but exceedingly challenging to receive information about the health and dynamical behavior of the spacecraft. The Deep Space Network, being a world-class instrument for Radio Science research, developed openloop receivers, called the Radio Science Receiver, designed to capture the raw incoming electromagnetic signals and associated noise for Radio Science experiments; post data capture digital signal processing extracts the signal carrier for scientific analysis. This receiver provides a high level of configuration flexibility and can be optimized for the various types of experiments. In addition to its scientific utility, it proved to be useful, and in some cases critical, for the support of missions during specific scenarios were the link budget is below the threshold of the tracking receiver to maintain lock or the frequency dynamics are faster than the limits of the tracking receiver. In these cases, the signal carrier is often detected only in the open-loop receiver to provide information on the specific behavior of the spacecraft from the carrier dynamics. This paper describes the utility of the system to support mission-critical events for the three cases of Cassini's Saturn orbit insertion, Huygens Titan landing, and Mars rovers landing.

radio science↗
NASA NTRS1994

Multimission Telemetry Visualization (MTV) system: A mission applications project from JPL's Multimedia Communications Laboratory

This paper describes the Multimission Telemetry Visualization (MTV) data acquisition/distribution system. MTV was developed by JPL's Multimedia Communications Laboratory (MCL) and designed to process and display digital, real-time, science and engineering data from JPL's Mission Control Center. The MTV system can be accessed using UNIX workstations and PC's over common datacom and telecom networks from worldwide locations. It is designed to lower data distribution costs while increasing data analysis functionality by integrating low-cost, off-the-shelf desktop hardware and software. MTV is expected to significantly lower the cost of real-time data display, processing, distribution, and allow for greater spacecraft safety and mission data access.

Koeberlein, Ernest, III↗
NASA NTRS2016

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

AIRS↗
NASA NTRS2016

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗
NASA NTRS2011

Generic, Extensible, Configurable Push-Pull Framework for Large-Scale Science Missions

The push-pull framework was developed in hopes that an infrastructure would be created that could literally connect to any given remote site, and (given a set of restrictions) download files from that remote site based on those restrictions. The Cataloging and Archiving Service (CAS) has recently been re-architected and re-factored in its canonical services, including file management, workflow management, and resource management. Additionally, a generic CAS Crawling Framework was built based on motivation from Apache s open-source search engine project called Nutch. Nutch is an Apache effort to provide search engine services (akin to Google), including crawling, parsing, content analysis, and indexing. It has produced several stable software releases, and is currently used in production services at companies such as Yahoo, and at NASA's Planetary Data System. The CAS Crawling Framework supports many of the Nutch Crawler's generic services, including metadata extraction, crawling, and ingestion. However, one service that was not ported over from Nutch is a generic protocol layer service that allows the Nutch crawler to obtain content using protocol plug-ins that download content using implementations of remote protocols, such as HTTP, FTP, WinNT file system, HTTPS, etc. Such a generic protocol layer would greatly aid in the CAS Crawling Framework, as the layer would allow the framework to generically obtain content (i.e., data products) from remote sites using protocols such as FTP and others. Augmented with this capability, the Orbiting Carbon Observatory (OCO) and NPP (NPOESS Preparatory Project) Sounder PEATE (Product Evaluation and Analysis Tools Elements) would be provided with an infrastructure to support generic FTP-based pull access to remote data products, obviating the need for any specialized software outside of the context of their existing process control systems. This extensible configurable framework was created in Java, and allows the use of different underlying communication middleware (at present, both XMLRPC, and RMI). In addition, the framework is entirely suitable in a multi-mission environment and is supporting both NPP Sounder PEATE and the OCO Mission. Both systems involve tasks such as high-throughput job processing, terabyte-scale data management, and science computing facilities. NPP Sounder PEATE is already using the push-pull framework to accept hundreds of gigabytes of IASI (infrared atmospheric sounding interferometer) data, and is in preparation to accept CRIMS (Cross-track Infrared Microwave Sounding Suite) data. OCO will leverage the framework to download MODIS, CloudSat, and other ancillary data products for use in the high-performance Level 2 Science Algorithm. The National Cancer Institute is also evaluating the framework for use in sharing and disseminating cancer research data through its Early Detection Research Network (EDRN).

Foster, Brian M.↗
NASA NTRS2014

GPM Data Products, Their Availability, and Production Status

On February 28, 2014, Japan Standard Time, the Global Precipitation Measurement (GPM) mission was launched in a picture-perfect launch activity. On March 4, 2014, the GPM Microwave Imager (GMI) was put into science observation mode. The Dual-Frequency Radar (DPR) was put in science observation mode on March 8, 2014. The Precipitation Processing System (PPS) produced products immediately upon receiving the data. Both regular science products and Near-realtime (NRT) products were produced. These were made immediately available to a group of early adopters. In mid-June 2014, GMI level-1 brightness temperature products were made publicly available. In mid-July 2014, GMI and partner-radiometer precipitation retrievals were made public. GMI public availability was several months ahead of the planned release. The DPR products became publicly available on the planned release date of September 2, 2014. Data continues to be available to any user desiring it.

Data Products↗
NASA NTRS2010

Pixel-Level Calibration in the Kepler Science Operations Center Pipeline

We present an overview of the pixel-level calibration of flight data from the Kepler Mission performed within the Kepler Science Operations Center Science Processing Pipeline. This article describes the calibration (CAL) module, which operates on original spacecraft data to remove instrument effects and other artifacts that pollute the data. Traditional CCD data reduction is performed (removal of instrument/detector effects such as bias and dark current), in addition to pixel-level calibration (correcting for cosmic rays and variations in pixel sensitivity), Kepler-specific corrections (removing smear signals which result from the lack of a shutter on the photometer and correcting for distortions induced by the readout electronics), and additional operations that are needed due to the complexity and large volume of flight data. CAL operates on long (~30 min) and short (~1 min) sampled data, as well as full-frame images, and produces calibrated pixel flux time series, uncertainties, and other metrics that are used in subsequent Pipeline modules. The raw and calibrated data are also archived in the Multi-mission Archive at Space Telescope at the Space Telescope Science Institute for use by the astronomical community.

Calibration↗