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NASA NTRS2011

Towards an Improved High Resolution Global Long-Term Solar Resource Database

This paper presents an overview of an ongoing project to develop and deliver a solar mapping processing system to the National Renewable Energy Laboratory (NREL) using the data sets that are planned for production at the National Climatic Data Center (NCDC). NCDC will be producing a long-term radiance and cloud property data set covering the globe every three hours at an approximate resolution of 10 x 10 km. NASA, the originators of the Surface meteorology and Solar Energy web portal are collaborating with SUNY-Albany to develop the production system and solar algorithms. The initial result will be a global long-term solar resource data set spanning over 25 years. The ultimate goal of the project is to also deliver this data set and production system to NREL for continual production. The project will also assess the impact of providing these new data to several NREL solar decision support tools.

Stackhouse, Paul W.↗

NASA NTRS2008

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Hong, Yang↗

NASA NTRS1999

Application of CFD to Explain Anomalous Stall Behavior of the SSME Flowmeter

Anomalous behavior manifested in the apparent SSME fuel flowmeter constant which relates the rotor speed to the engine flowrate has been shown to be the result of wakes of the upstream hexagonal web flow straightener periodically stalling the rotor blades, thereby changing the lift on the blades and the rotation speed of the rotor. Moreover, an unsteady, two-dimensional computational fluid dynamics model of the flowmeter has shown this wake-induced stall disappearing as the straightener-rotor distance is doubled, in accord with the existing SSME flowmeter database for the previous "egg crate" flowmeter. These observations have led to a new flowmeter design which has been shown in three-dimensional CFD computations (consistent with both the previous two-dimensional analyses and with existing correlations for airfoil stall) to be much less susceptible to stalling instabilities.

Ascoli, E.↗

NASA NTRS1997

CINTEX: International Interoperability Extensions to EOSDIS

A large part of the research under this cooperative agreement involved working with representatives of the DLR, NASDA, EDC, and NOAA-SAA data centers to propose a set of enhancements and additions to the EOSDIS Version 0 Information Management System (V0 IMS) Client/Server Message Protocol. Helen Conover of ITSL led this effort to provide for an additional geographic search specification (WRS Path/Row), data set- and data center-specific search criteria, search by granule ID, specification of data granule subsetting requests, data set-based ordering, and the addition of URLs to result messages. The V0 IMS Server Cookbook is an evolving document, providing resources and information to data centers setting up a VO IMS Server. Under this Cooperative Agreement, Helen Conover revised, reorganized, and expanded this document, and converted it to HTML. Ms. Conover has also worked extensively with the IRE RAS data center, CPSSI, in Russia. She served as the primary IMS contact for IRE-CPSSI and as IRE-CPSSI's liaison to other members of IMS and Web Gateway (WG) development teams. Her documentation of IMS problems in the IRE environment (Sun servers and low network bandwidth) led to a general restructuring of the V0 IMS Client message polling system. to the benefit of all IMS participants. In addition to the IMS server software and documentation. which are generally available to CINTEX sites, Ms. Conover also provided database design documentation and consulting, order tracking software, and hands-on testing and debug assistance to IRE. In the final pre-operational phase of IRE-CPSSI development, she also supplied information on configuration management, including ideas and processes in place at the Global Hydrology Resource Center (GHRC), an EOSDIS data center operated by ITSL.

Graves, Sara J.↗

NASA NTRSDate not supplied

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

NASA NTRS2007

AIRSAR Web-Based Data Processing

The AIRSAR automated, Web-based data processing and distribution system is an integrated, end-to-end synthetic aperture radar (SAR) processing system. Designed to function under limited resources and rigorous demands, AIRSAR eliminates operational errors and provides for paperless archiving. Also, it provides a yearly tune-up of the processor on flight missions, as well as quality assurance with new radar modes and anomalous data compensation. The software fully integrates a Web-based SAR data-user request subsystem, a data processing system to automatically generate co-registered multi-frequency images from both polarimetric and interferometric data collection modes in 80/40/20 MHz bandwidth, an automated verification quality assurance subsystem, and an automatic data distribution system for use in the remote-sensor community. Features include Survey Automation Processing in which the software can automatically generate a quick-look image from an entire 90-GB SAR raw data 32-MB/s tape overnight without operator intervention. Also, the software allows product ordering and distribution via a Web-based user request system. To make AIRSAR more user friendly, it has been designed to let users search by entering the desired mission flight line (Missions Searching), or to search for any mission flight line by entering the desired latitude and longitude (Map Searching). For precision image automation processing, the software generates the products according to each data processing request stored in the database via a Queue management system. Users are able to have automatic generation of coregistered multi-frequency images as the software generates polarimetric and/or interferometric SAR data processing in ground and/or slant projection according to user processing requests for one of the 12 radar modes.

Chu, Anhua↗

NASA NTRS1999

MOD Tool (Microwave Optics Design Tool)

The Jet Propulsion Laboratory (JPL) is currently designing and building a number of instruments that operate in the microwave and millimeter-wave bands. These include MIRO (Microwave Instrument for the Rosetta Orbiter), MLS (Microwave Limb Sounder), and IMAS (Integrated Multispectral Atmospheric Sounder). These instruments must be designed and built to meet key design criteria (e.g., beamwidth, gain, pointing) obtained from the scientific goals for the instrument. These criteria are frequently functions of the operating environment (both thermal and mechanical). To design and build instruments which meet these criteria, it is essential to be able to model the instrument in its environments. Currently, a number of modeling tools exist. Commonly used tools at JPL include: FEMAP (meshing), NASTRAN (structural modeling), TRASYS and SINDA (thermal modeling), MACOS/IMOS (optical modeling), and POPO (physical optics modeling). Each of these tools is used by an analyst, who models the instrument in one discipline. The analyst then provides the results of this modeling to another analyst, who continues the overall modeling in another discipline. There is a large reengineering task in place at JPL to automate and speed-up the structural and thermal modeling disciplines, which does not include MOD Tool. The focus of MOD Tool (and of this paper) is in the fields unique to microwave and millimeter-wave instrument design. These include initial design and analysis of the instrument without thermal or structural loads, the automation of the transfer of this design to a high-end CAD tool, and the analysis of the structurally deformed instrument (due to structural and/or thermal loads). MOD Tool is a distributed tool, with a database of design information residing on a server, physical optics analysis being performed on a variety of supercomputer platforms, and a graphical user interface (GUI) residing on the user's desktop computer. The MOD Tool client is being developed using Tcl/Tk, which allows the user to work on a choice of platforms (PC, Mac, or Unix) after downloading the Tcl/Tk binary, which is readily available on the web. The MOD Tool server is written using Expect, and it resides on a Sun workstation. Client/server communications are performed over a socket, where upon a connection from a client to the server, the server spawns a child which is be dedicated to communicating with that client. The server communicates with other machines, such as supercomputers using Expect with the username and password being provided by the user on the client.

Katz, Daniel S.↗

NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗

NASA NTRSDate not supplied

New Ways of Facilitating Improved Data Discovery and Access for NASA's Suborbital Earth Science Observations

NASA conducts field research in various Earth Science disciplines utilizing airborne and other non-satellite platforms to acquire in situ and remotely sensed observations indicative of physical processes across a range of scales. Field efforts are key in the development and validation of instruments and satellite algorithm refinements. The heterogeneous data, with a range of file formats, scales, and acquisition methods, support research in several science areas. NASA’s archive process assigns data products to discipline-oriented Distributed Active Archive Centers (DAACs) for stewardship. Over time, individual DAACs have developed tools for data browsing and serving disparate user bases. As science becomes more interdisciplinary, researchers need to incorporate observations from multiple campaigns, and multiple DAACs, into their work. Motivated in part by this shifting paradigm of needs, the Catalog of Archived Suborbital Earth Science Investigations (CASEI) was created. CASEI provides a single starting point to browse, search, and discover airborne and field data. Contextual metadata are organized and inter-linked allowing intuitive, integrated exploration across all NASA DAACs. Campaign science objectives, platform and instrument configurations, geographical details, geophysical concepts, and more are tracked in CASEI’s database, facilitating multi-parameter search, browse, and discovery of relevant data products. Researchers are able to directly access associated data products, via DOI links, regardless of the DAAC where they reside. Significant events, key time periods of high science interest within the longer-duration campaign effort, are also indicated and allow for a more efficient identification of critical data subsets. This presentation describes CASEI’s development, intensive metadata curation process, and demonstrates the web interface experience. Initial content metrics and plans for continued maintenance will also be discussed.

metadata↗

NASA NTRS2003

Enhancing and Archiving the APS Catalog of the POSS I

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

Humphreys, Roberta M.↗

NASA NTRS2006

A Predictive Approach to Eliminating Errors in Software Code

NASA s Metrics Data Program Data Repository is a database that stores problem, product, and metrics data. The primary goal of this data repository is to provide project data to the software community. In doing so, the Metrics Data Program collects artifacts from a large NASA dataset, generates metrics on the artifacts, and then generates reports that are made available to the public at no cost. The data that are made available to general users have been sanitized and authorized for publication through the Metrics Data Program Web site by officials representing the projects from which the data originated. The data repository is operated by NASA s Independent Verification and Validation (IV&V) Facility, which is located in Fairmont, West Virginia, a high-tech hub for emerging innovation in the Mountain State. The IV&V Facility was founded in 1993, under the NASA Office of Safety and Mission Assurance, as a direct result of recommendations made by the National Research Council and the Report of the Presidential Commission on the Space Shuttle Challenger Accident. Today, under the direction of Goddard Space Flight Center, the IV&V Facility continues its mission to provide the highest achievable levels of safety and cost-effectiveness for mission-critical software. By extending its data to public users, the facility has helped improve the safety, reliability, and quality of complex software systems throughout private industry and other government agencies. Integrated Software Metrics, Inc., is one of the organizations that has benefited from studying the metrics data. As a result, the company has evolved into a leading developer of innovative software-error prediction tools that help organizations deliver better software, on time and on budget.

Source record↗

NASA NTRS2016

Flight Awareness Collaboration Tool Development

NASA is developing the Flight Awareness Collaboration Tool (FACT) to support airline and airport operations during winter storms. The goal is to reduce flight delays and cancellations due to winter weather. FACT concentrates relevant information from the Internet and FAA databases on one screen for easy access. It provides collaboration tools for those managing the winter weather event including the airline operations center, airport authority (runway treatment), the Federal Aviation Administration air traffic control tower, and de-icing operators. Prediction tools are being added to improve FACT capabilities including one that anticipates changes in airport departure rates from weather forecasts. We have formed two user teams from affected airports to guide the design and evaluate the web-based prototype. Future work includes adding more automated capabilities and conducting a simulation to evaluate FACT in a realistic environment.

Mogford, Richard↗

NASA NTRS2019

Flight Awareness Collaboration Tool Development

Mogford, Richard↗

NASA NTRS1996

Software Project Management and Measurement on the World-Wide-Web (WWW)

We briefly describe a system for forms-based, work-flow management that helps members of a software development team overcome geographical barriers to collaboration. Our system, called the Web Integrated Software Environment (WISE), is implemented as a World-Wide-Web service that allows for management and measurement of software development projects based on dynamic analysis of change activity in the workflow. WISE tracks issues in a software development process, provides informal communication between the users with different roles, supports to-do lists, and helps in software process improvement. WISE minimizes the time devoted to metrics collection and analysis by providing implicit delivery of messages between users based on the content of project documents. The use of a database in WISE is hidden from the users who view WISE as maintaining a personal 'to-do list' of tasks related to the many projects on which they may play different roles.

Callahan, John↗

NASA NTRS2010

Description of a Website Resource for Turbulence Modeling Verification and Validation

The activities of the Turbulence Model Benchmarking Working Group - which is a subcommittee of the American Institute of Aeronautics and Astronautics (AIAA) Fluid Dynamics Technical Committee - are described. The group s main purpose is to establish a web-based repository for Reynolds-averaged Navier-Stokes turbulence model documentation, including verification and validation cases. This turbulence modeling resource has been established based on feedback from a survey on what is needed to achieve consistency and repeatability in turbulence model implementation and usage, and to document and disseminate information on new turbulence models or improvements to existing models. The various components of the website are described in detail: description of turbulence models, turbulence model readiness rating system, verification cases, validation cases, validation databases, and turbulence manufactured solutions. An outline of future plans of the working group is also provided.

Rumsey, Christopher L.↗

NASA NTRS2019

The Arctic-Boreal vulnerability experiment model benchmarking system

NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) integrates field and airborne data into modeling and synthesis activities for understanding Arctic and Boreal ecosystem dynamics. The ABoVE Benchmarking System (ABS) is an operational software package to evaluate terrestrial biosphere models against key indicators of Arctic and Boreal ecosystem dynamics, i.e.: carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance. The ABS utilizes satellite remote sensing data, airborne data, and field data from ABoVE as well as collaborating research networks in the region, e.g.: the Permafrost Carbon Network, the International Soil Carbon Network, the Northern Circumpolar Soil Carbon Database, AmeriFlux sites, the Moderate Resolution Imaging Spectroradiometer, the Orbiting Carbon Observatory 2, and the Soil Moisture Active Passive mission. The ABS is designed to be interactive for researchers interested in having their models accurately represent observations of key Arctic indicators: a user submits model results to the system, the system evaluates the model results against a set of Arctic-Boreal benchmarks outlined in the ABoVE Concise Experiment Plan, and the user then receives a quantitative scoring of model strengths and deficiencies through a web interface. This interactivity allows model developers to iteratively improve their model for the Arctic-Boreal Region by evaluating results from successive model versions. We show here, for illustration, the improvement of the Lund–Potsdam–Jena-Wald Schnee und Landschaft (LPJwsl) version model through the ABoVE ABS as a new permafrost module is coupled to the existing model framework. The ABS will continue to incorporate new benchmarks that address indicators of Arctic-Boreal ecosystem dynamics as they become available.

ABoVE↗

NASA NTRS2011

Ruby on Rails Applications

Ruby on Rails is an open source web application framework for the Ruby programming language. The first application I built was a web application to manage and authenticate other applications. One of the main requirements for this application was a single sign-on service. This allowed authentication to be built in one location and be implemented in many different applications. For example, users would be able to login using their existing credentials, and be able to access other NASA applications without authenticating again. The second application I worked on was an internal qualification plan app. Previously, the viewing of employee qualifications was managed through Excel spread sheets. I built a database driven application to streamline the process of managing qualifications. Employees would be able to login securely to view, edit and update their personal qualifications.

Hochstadt, Jake↗

NASA NTRS2013

The NASA Fireball Network

In the summer of 2008, the NASA Meteoroid Environments Office (MEO) began to establish a video fireball network, based on the following objectives: (1) determine the speed distribution of cm size meteoroids, (2) determine the major sources of cm size meteoroids (showers/sporadic sources), (3) characterize meteor showers (numbers, magnitudes, trajectories, orbits), (4) determine the size at which showers dominate the meteor flux, (5) discriminate between re-entering space debris and meteors, and 6) locate meteorite falls. In order to achieve the above with the limited resources available to the MEO, it was necessary that the network function almost fully autonomously, with very little required from humans in the areas of upkeep or analysis. With this in mind, the camera design and, most importantly, the ASGARD meteor detection software were adopted from the University of Western Ontario's Southern Ontario Meteor Network (SOMN), as NASA has a cooperative agreement with Western's Meteor Physics Group. 15 cameras have been built, and the network now consists of 8 operational cameras, with at least 4 more slated for deployment in calendar year 2013. The goal is to have 15 systems, distributed in two or more groups east of automatic analysis; every morning, this server also automatically generates an email and a web page (http://fireballs.ndc.nasa.gov) containing an automated analysis of the previous night's events. This analysis provides the following for each meteor: UTC date and time, speed, start and end locations (longitude, latitude, altitude), radiant, shower identification, light curve (meteor absolute magnitude as a function of time), photometric mass, orbital elements, and Tisserand parameter. Radiant/orbital plots and various histograms (number versus speed, time, etc) are also produced. After more than four years of operation, over 5,000 multi-station fireballs have been observed, 3 of which potentially dropped meteorites. A database containing data on all these events, including the videos and calibration information, has been developed and is being modified to include data from the SOMN and other camera networks.

Cooke, William J.↗