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At least 1,153 records · Page 64

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

L. Prinzel↗

The Adaptable and Resilient Safety System: The Human Factor in Future In-Time Aviation Safety Management Systems

In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.

Aviation Safety↗

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Knowledge-based vision for space station object motion detection, recognition, and tracking

Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

Symosek, P.↗

Earth Science Data Analytics: Bridging Tools and Techniques with the Co-Analysis of Large, Heterogeneous Datasets

The continuum of ever-evolving data management systems affords great opportunities to the enhancement of knowledge and facilitation of science research. To take advantage of these opportunities, it is essential to understand and develop methods that enable data relationships to be examined and the information to be manipulated. This presentation describes the efforts of the Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster to understand, define, and facilitate the implementation of ESDA to advance science research. As a result of the void of Earth science data analytics publication material, the cluster has defined ESDA along with 10 goals to set the framework for a common understanding of tools and techniques that are available and still needed to support ESDA.

science data analysis↗

Complications of Metadata Curation for NASA Airborne and Field Campaigns, Platforms, and Instruments

The Airborne Data Management Group (ADMG) curates metadata that describe NASA's airborne and field campaigns, platforms and instruments. This activity is vital to building a useful inventory of sub-orbital Earth science data that improves data discovery and access. During the curation process, many metadata issues were identified that required improvement to campaign and data product metadata. In some cases, locating the needed metadata to add to the inventory was a simple process. For other cases, the information was hard to find. In addition, identifying accurate investigation instrument details to add to the inventory was especially complicated because of the variety of definitions used in the Earth science community for the same concepts. One example of this is the concept of instruments' spatial and temporal resolution. The spatial resolution is one of the more difficult elements to curate given the variations in meaning across various disciplines. Clarified definitions are needed to enable consistency of information across campaigns and instruments. In this presentation, we introduce results from a survey of scientists from various fields in which we asked for definitions of spatial and temporal resolution. Our survey results highlight the importance of creating more universally acceptable definitions for certain metadata elements. By curating sub-orbital field campaign and instrument metadata, ADMG is enabling more efficient discovery and access to NASA observations by allowing science data users to search for certain clearly defined criteria and metadata values.

Ashlyn Shirey↗

Blast from the Past: ASDC Curation for NASA Suborbital Legacy Missions to Promote Data Discovery and Accessibility

NASA has an extensive history of conducting suborbital field campaigns to further advances in atmospheric sciences. Beginning with the Chemical Instrument Test and Evaluation (CITE) conducted in 1983-1984, NASA has completed many suborbital campaigns over the past three decades. Since the early 2010s, suborbital missions are typically assigned to a NASA Distributed Active Archive Center (DAAC) prior to the mission for long-term archival and distribution. Efforts are being made by NASA’s Earth Science Data and Information System (ESDIS) Project and the Airborne Data Management Group (ADMG) to assign legacy missions to DAACs for permanent archival and distribution, so that these valuable datasets remain to be available to the scientific community. NASA’s Atmospheric Science Data Center (ASDC) has been named the assigned DAAC for nearly 20 atmospheric composition legacy missions, including missions conducted as part of the Global Tropospheric Experiment (GTE) and expects to be named the assigned DAAC for more of these missions over the next few years. The primary goal of the ASDC is to provide access to the datasets as they are currently formatted to the broad user community and enhance their findability and accessibility. However, data reporting standards have evolved significantly since 1983 and the datasets span a wide variety of file formats, including text, Ames, GTE, and ICARTT (International Consortium for Atmospheric Research on Transport and Transformation), and the amount of metadata and relevant information included in the files also varies greatly and can not be readily extracted without subject matter knowledge. This has caused challenges for the ASDC’s suborbital metadata extraction pipeline in ensuring that accurate and necessary metadata is being provided for the missions by all the ASDC’s existing search mechanisms. To make the data more findable and accessible, the ASDC has begun researching ways to further enhance the datasets, including distributing value-added products (i.e. consistent file format such as ICARTT or netCDF), adding standard names from the ESDIS Standards Coordination Office (ESCO)-approved Atmospheric Composition Variable Standard Names Convention (ACVSNC), and creating outreach materials such as ArcGIS StoryMaps, User Guides, and Micro Articles, providing overviews of the missions and what type of data was collected during the missions. These efforts also help support NASA’s Open-Source Science by enhancing the FAIRness of the legacy data products. This presentation will review the ASDC’s ongoing efforts, progress made, and future plans for legacy missions.

Megan Buzanowicz↗

White paper on science operations

Major changes are taking place in the way astronomy gets done. There are continuing advances in observational capabilities across the frequency spectrum, involving both ground-based and space-based facilities. There is also very rapid evolution of relevant computing and data management technologies. However, although the new technologies are filtering in to the astronomy community, and astronomers are looking at their computing needs in new ways, there is little coordination or coherent policy. Furthermore, although there is great awareness of the evolving technologies in the arena of operations, much of the existing operations infrastructure is ill-suited to take advantage of them. Astronomy, especially space astronomy, has often been at the cutting edge of computer use in data reduction and image analysis, but has been somewhat removed from advanced applications in operations, which have tended to be implemented by industry rather than by the end-user scientists. The purpose of this paper is threefold. First, we briefly review the background and general status of astronomy-related computing. Second, we make recommendations in three areas: data analysis; operations (directed primarily to NASA-related activities); and issues of management and policy, believing that these must be addressed to enable technological progress and to proceed through the next decade. Finally, we recommend specific NASA-related work as part of the Astrotech-21 plans, to enable better science operations in the operations of the Great Observatories and in the lunar outpost era.

Schreier, Ethan J.↗

The Planetary Data System - A Case Study in the Development and Management of Meta-Data for a Scientific Digital Library

The Planetary Data System (PDS) is an active science data archive managed by scientists for NASA's planetary science community. With the advent of the World Wide Web the majority of the archive has been placed on-line as a science digital libraty for access by scientists, the educational community, and the general public.

Data System Meta-data scientific digital library↗

How to Flatten the Earth?

Since the passage of the Geospatial Data Act (GDA) in 2018, federal agencies, including the Department of Energy (DOE), have been working to ensure compliance and outline guidance for the geospatial datasets and affiliated products publicly released from their agencies. At DOE this sparked work to develop a geospatial data management strategy and implementation plan; both of which spotlighted the need for the agency to set preferred guidance for the agency to use to inform the release of any public facing geospatial data and products. One of the immediate needs was set around establishing preferred guidance for coordinate systems, given the foundational role they play in all geospatial data, as they help reference data to the earth. DOE’s Geospatial Information Officer (GIO) and the Geospatial Sciences Steering Committee (GSSC) worked together to summarize best practices and current DOE uses to outline recommendations for coordinate systems to use for public geospatial data and products. This poster summarizes the role of coordinate systems, trends in coordinate system use from across the Department that were used to set preferred guidance for the Department to consider when releasing public-facing geospatial data and products.

Bauer, Jennifer↗

NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training

The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user fs decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.

Fuell, Kevin K.↗

The payload connection - Approaches to onboard data processing for scientific systems on the Space Shuttle

The integration of payload instruments into the Command and Data Management Subsystem (CDMS) of the Space Shuttle Spacelab is discussed. Specific emphasis is on the distributed (self-contained processor) vs centralized (Spacelab Computer) approach to science payload utilization of these control and data handling capabilities. An overview of the Spacelab CDMS is first given. A synopsis of the integration process for Spacelab Missions 1, 2, and 3 is discussed. Three different hardware approaches to payload command and data handling are then categorized from which Spacelab implementations to date are derived. The different types of Spacelab Mission 3 payload CDMS hardware and software being used are discussed, including examples of microprocessors and data acquisition systems. Preliminary costs for Spacelab application software vs other flight software approaches are compared. A standard RAU interface that would permit a range of ECOS services to be provided, yet be implemented as a mass-produceable unit for incorporation into payloads, is proposed, in keeping with the trend toward simplifying the integration effort, standardizing CDMS interfaces, and ultimately lowering cost.

Konkel, C. R.↗

Automated extraction of metadata from remotely sensed satellite imagery

The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.

Cromp, Robert F.↗

LARCRIM user's guide, version 1.0

LARCRIM is a relational database management system (RDBMS) which performs the conventional duties of an RDBMS with the added feature that it can store attributes which consist of arrays or matrices. This makes it particularly valuable for scientific data management. It is accessible as a stand-alone system and through an application program interface. The stand-alone system may be executed in two modes: menu or command. The menu mode prompts the user for the input required to create, update, and/or query the database. The command mode requires the direct input of LARCRIM commands. Although LARCRIM is an update of an old database family, its performance on modern computers is quite satisfactory. LARCRIM is written in FORTRAN 77 and runs under the UNIX operating system. Versions have been released for the following computers: SUN (3 & 4), Convex, IRIS, Hewlett-Packard, CRAY 2 & Y-MP.

Davis, John S.↗

Retrieving Atmospheric Temperature and Moisture Profiles from NPP CRIS/ATMS Sensors Using Crimss EDR Algorithm

The Joint Polar Satellite System (JPSS) is a U.S. National Oceanic and Atmospheric Administration (NOAA) mission in collaboration with the U.S. National Aeronautical Space Administration (NASA) and international partners. The NPP Cross-track Infrared Microwave Sounding Suite (CrIMSS) consists of the infrared (IR) Crosstrack Infrared Sounder (CrIS) and the microwave (MW) Advanced Technology Microwave Sounder (ATMS). The CrIS instrument is hyperspectral interferometer, which measures high spectral and spatial resolution upwelling infrared radiances. The ATMS is a 22-channel radiometer similar to Advanced Microwave Sounding Units (AMSU) A and B. It measures top of atmosphere MW upwelling radiation and provides capability of sounding below clouds. The CrIMSS Environmental Data Record (EDR) algorithm provides three EDRs, namely the atmospheric vertical temperature, moisture and pressure profiles (AVTP, AVMP and AVPP, respectively), with the lower tropospheric AVTP and the AVMP being JPSS Key Performance Parameters (KPPs). The operational CrIMSS EDR an algorithm was originally designed to run on large IBM computers with dedicated data management subsystem (DMS). We have ported the operational code to simple Linux systems by replacing DMS with appropriate interfaces. We also changed the interface of the operational code so that we can read data from both the CrIMSS science code and the operational code and be able to compare lookup tables, parameter files, and output results. The detail of the CrIMSS EDR algorithm is described in reference [1]. We will present results of testing the CrIMSS EDR operational algorithm using proxy data generated from the Infrared Atmospheric Sounding Interferometer (IASI) satellite data and from the NPP CrIS/ATMS data.

Liu, X.↗

Spinoff 2011

Topics include: Bioreactors Drive Advances in Tissue Engineering; Tooling Techniques Enhance Medical Imaging; Ventilator Technologies Sustain Critically Injured Patients; Protein Innovations Advance Drug Treatments, Skin Care; Mass Analyzers Facilitate Research on Addiction; Frameworks Coordinate Scientific Data Management; Cameras Improve Navigation for Pilots, Drivers; Integrated Design Tools Reduce Risk, Cost; Advisory Systems Save Time, Fuel for Airlines; Modeling Programs Increase Aircraft Design Safety; Fly-by-Wire Systems Enable Safer, More Efficient Flight; Modified Fittings Enhance Industrial Safety; Simulation Tools Model Icing for Aircraft Design; Information Systems Coordinate Emergency Management; Imaging Systems Provide Maps for U.S. Soldiers; High-Pressure Systems Suppress Fires in Seconds; Alloy-Enhanced Fans Maintain Fresh Air in Tunnels; Control Algorithms Charge Batteries Faster; Software Programs Derive Measurements from Photographs; Retrofits Convert Gas Vehicles into Hybrids; NASA Missions Inspire Online Video Games; Monitors Track Vital Signs for Fitness and Safety; Thermal Components Boost Performance of HVAC Systems; World Wind Tools Reveal Environmental Change; Analyzers Measure Greenhouse Gasses, Airborne Pollutants; Remediation Technologies Eliminate Contaminants; Receivers Gather Data for Climate, Weather Prediction; Coating Processes Boost Performance of Solar Cells; Analyzers Provide Water Security in Space and on Earth; Catalyst Substrates Remove Contaminants, Produce Fuel; Rocket Engine Innovations Advance Clean Energy; Technologies Render Views of Earth for Virtual Navigation; Content Platforms Meet Data Storage, Retrieval Needs; Tools Ensure Reliability of Critical Software; Electronic Handbooks Simplify Process Management; Software Innovations Speed Scientific Computing; Controller Chips Preserve Microprocessor Function; Nanotube Production Devices Expand Research Capabilities; Custom Machines Advance Composite Manufacturing; Polyimide Foams Offer Superior Insulation; Beam Steering Devices Reduce Payload Weight; Models Support Energy-Saving Microwave Technologies; Materials Advance Chemical Propulsion Technology; and High-Temperature Coatings Offer Energy Savings.

Source record↗

Architecture of a large object-oriented database for remotely sensed data

Attention is given to the proposed Intelligent Information Fusion System (IIFS) within the framework of the Intelligent Data Management project at NASA-Goddard. IIFS is to use connectionist architectures to extract high-level attributes from incoming sensor images, and then send those characterizations and their associated ephemeris and ancillary image data to a large object-oriented database which will serve as the master catalog of sensor data. Important issues facing this project include the choice of rapid-access data structures (RADSs) for cataloging images by their high-level characterization, the implementation of efficient spatial data structures for cataloging images by their scene location, the automated population of such a database from a continuous stream of incoming ephemeris and ancillary data, and the translation and optimization of natural-language database queries so that RADSs are employed when appropriate.

Dorfman, Erik↗