Search NASA⌕ Search

SEARCH · Search NASA

Results for “Team software development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

SIDS-toADF File Mapping Manual

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The SIDS-toADF File Mapping Manual specifies the exact manner in which, under CGNS conventions, CFD data structures (the SIDS) are to be stored in (i.e., mapped onto) the file structure provided by the database manager (ADF). The result is a conforming CGNS database. Adherence to the mapping conventions guarantees uniform meaning and location of CFD data within ADF files, and thereby allows the construction of universal software to read and write the data.

McCarthy, Douglas↗

Advanced Data Format (ADF) Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial. Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its 1/0 software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The ADF is a generic database manager with minimal intrinsic capability. It was written for the purpose of storing large numerical datasets in an efficient, platform independent manner. To be effective, it must be used in conjunction with external agreements on how the data will be organized within the ADF database such defined by the SIDS. There are currently 34 user callable functions that comprise the ADF Core library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Smith, Matthew↗

NASA's Swarm Missions: The Challenge of Building Autonomous Software

The days of watching a massive manned cylinder thrust spectacularly off a platform into space might rapidly become ancient history when the National Aeronautics and Space Administration (NASA) introduces its new millenium mission class. Motivated by the need to gather more data than is possible with a single spacecraft, scientists have developed a new class of missions based on the efficiency and cooperative nature of a hive culture. The missions, aptly dubbed nanoswarm will be little more than mechanized colonies cooperating in their exploration of the solar system. Each swarm mission can have hundreds or even thousands of cooperating intelligent spacecraft that work in teams. The spacecraft must operate independently for long periods both in teams and individually, as well as have autonomic properties - self-healing, -configuring, -optimizing, and -protecting- to survive the harsh space environment. One swarm mission under concept development for 2020 to 2030 is the Autonomous Nano Technology Swarm (ANTS), in which a thousand picospacecraft, each weighing less than three pounds, will work cooperatively to explore the asteroid belt. Some spacecraft will form teams to catalog asteroid properties, such as mass, density, morphology, and chemical composition, using their respective miniature scientific instruments. Others will communicate with the data gatherers and send updates to mission elements on Earth. For software and systems development, this is uncharted territory that calls for revolutionary techniques.

Truszkowski, Walt↗

Conversion from Tree to Graph Representation of Requirements

A procedure and software to implement the procedure have been devised to enable conversion from a tree representation to a graph representation of the requirements governing the development and design of an engineering system. The need for this procedure and software and for other requirements-management tools arises as follows: In systems-engineering circles, it is well known that requirements- management capability improves the likelihood of success in the team-based development of complex systems involving multiple technological disciplines. It is especially desirable to be able to visualize (in order to identify and manage) requirements early in the system- design process, when errors can be corrected most easily and inexpensively.

Mayank, Vimal↗

Exploring the Use of a Test Automation Framework

It is known that software testers, more often than not, lack the time needed to fully test the delivered software product within the time period allotted to them. When problems in the implementation phase of a development project occur, it normally causes the software delivery date to slide. As a result, testers either need to work longer hours, or supplementary resources need to be added to the test team in order to meet aggressive test deadlines. One solution to this problem is to provide testers with a test automation framework to facilitate the development of automated test solutions.

TAF STAF Test Automation↗

System testing of a production Ada (trademark) project: The GRODY study

The use of the Ada language and design methodologies that utilize its features has a strong impact on all phases of the software development project lifecycle. At the National Aeronautics and Space Administration/Goddard Space Flight Center (NASA/GSFC), the Software Engineering Laboratory (SEL) conducted an experiment in parallel development of two flight dynamics systems in FORTRAN and Ada. The teams found some qualitative differences between the system test phases of the two projects. Although planning for system testing and conducting of tests were not generally affected by the use of Ada, the solving of problems found in system testing was generally facilitated by Ada constructs and design methodology. Most problems found in system testing were not due to difficulty with the language or methodology but to lack of experience with the application.

Seigle, Jeffrey↗

Automated Flight Dynamics Product Generation for the EOS AM-1 Spacecraft

As part of NASA's Earth Science Enterprise, the Earth Observing System (EOS) AM-1 spacecraft is designed to monitor long-term, global, environmental changes. Because of the complexity of the AM-1 spacecraft, the mission operations center requires more than 80 distinct flight dynamics products (reports). To create these products, the AM-1 Flight Dynamics Team (FDT) will use a combination of modified commercial software packages (e.g., Analytical Graphic's Satellite ToolKit) and NASA-developed software applications. While providing the most cost-effective solution to meeting the mission requirements, the integration of these software applications raises several operational concerns: (1) Routine product generation requires knowledge of multiple applications executing on variety of hardware platforms. (2) Generating products is a highly interactive process requiring a user to interact with each application multiple times to generate each product. (3) Routine product generation requires several hours to complete. (4) User interaction with each application introduces the potential for errors, since users are required to manually enter filenames and input parameters as well as run applications in the correct sequence. Generating products requires some level of flight dynamics expertise to determine the appropriate inputs and sequencing. To address these issues, the FDT developed an automation software tool called AutoProducts, which runs on a single hardware platform and provides all necessary coordination and communication among the various flight dynamics software applications. AutoProducts, autonomously retrieves necessary files, sequences and executes applications with correct input parameters, and deliver the final flight dynamics products to the appropriate customers. Although AutoProducts will normally generate pre-programmed sets of routine products, its graphical interface allows for easy configuration of customized and one-of-a-kind products. Additionally, AutoProducts has been designed as a mission-independent tool, and can be easily reconfigured to support other missions or incorporate new flight dynamics software packages. After the AM-1 launch, AutoProducts will run automatically at pre-determined time intervals . The AutoProducts tool reduces many of the concerns associated with the flight dynamics product generation. Although AutoProducts required a significant effort to develop because of the complexity of the interfaces involved, its use will provide significant cost savings through reduced operator time and maximum product reliability. In addition, user satisfaction is significantly improved and flight dynamics experts have more time to perform valuable analysis work. This paper will describe the evolution of the AutoProducts tool, highlighting the cost savings and customer satisfaction resulting from its development. It will also provide details about the tool including its graphical interface and operational capabilities.

Matusow, Carla↗

Prototype Common Bus Spacecraft: Hover Test Implementation and Results

In order to develop the capability to evaluate control system technologies, NASA Ames Research Center (Ames) began a test program to build a Hover Test Vehicle (HTV) - a ground-based simulated flight vehicle. The HTV would integrate simulated propulsion, avionics, and sensors into a simulated flight structure, and fly that test vehicle in terrestrial conditions intended to simulate a flight environment, in particular for attitude control. The ultimate purpose of the effort at Ames is to determine whether the low-cost hardware and flight software techniques are viable for future low cost missions. To enable these engineering goals, the project sought to develop a team, processes and procedures capable of developing, building and operating a fully functioning vehicle including propulsion, GN&C, structure, power and diagnostic sub-systems, through the development of the simulated vehicle.

Hine, Butler Preston↗

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, slated to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task; allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with high-performance optimizers written by the University of Alabama, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav suite image deployment process is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile without unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

optimization↗

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, expected to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary & operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task, allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with high-performance optimizers written by researchers at the University of Alabama, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav software suite itself is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile – thus avoiding unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

Containerization↗

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, expected to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary & operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task, allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with University of Alabama’s high-performance optimizer, ASSET, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav software suite itself is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile – thus avoiding unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

solar cruiser↗

Using MCC Facility Metrics to Size, Inform, and Troubleshoot

The Mission Control Center (MCC) underwent a major architecture update that has been used for Mission Operations since 2016. The MCC Performance team has collected system performance and usage metrics to improve the configuration, troubleshoot incidents, and help size the system to accommodate future programs. The data is collected through MCC custom software and custom scripts to extract data from our Commercial Off The Shelf (COTS) tools. This data has enabled MCC to support more activities concurrently, help our operations and development teams to respond to issues more quickly, and make our directorate informed buyers to meet new requirements when developing project plans for the upcoming Fiscal Year.

Data Science↗

Nasa's Ant-Inspired Swarmie Robots

As humans push further beyond the grasp of earth, robotic missions in advance of human missions will play an increasingly important role. These robotic systems will find and retrieve valuable resources as part of an in-situ resource utilization (ISRU) strategy. They will need to be highly autonomous while maintaining high task performance levels. NASA Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots to be used as a ground-based research platform for ISRU missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in a previously unmapped environment and return those resources to a central site. This talk will guide the audience through the Swarmie robot project from its conception by students in a New Mexico research lab to its robot trials in an outdoor parking lot at NASA. The software technologies and techniques used on the project will be discussed, as well as various challenges and solutions that were encountered by the development team along the way.

biologically inspired robots↗

GeoLab: A Geological Workstation for Future Missions

The GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance theThe GeoLab glovebox was, until November 2012, fully integrated into NASA's Deep Space Habitat (DSH) Analog Testbed. The conceptual design for GeoLab came from several sources, including current research instruments (Microgravity Science Glovebox) used on the International Space Station, existing Astromaterials Curation Laboratory hardware and clean room procedures, and mission scenarios developed for earlier programs. GeoLab allowed NASA scientists to test science operations related to contained sample examination during simulated exploration missions. The team demonstrated science operations that enhance the early scientific returns from future missions and ensure that the best samples are selected for Earth return. The facility was also designed to foster the development of instrument technology. Since 2009, when GeoLab design and construction began, the GeoLab team [a group of scientists from the Astromaterials Acquisition and Curation Office within the Astromaterials Research and Exploration Science (ARES) Directorate at JSC] has progressively developed and reconfigured the GeoLab hardware and software interfaces and developed test objectives, which were to 1) determine requirements and strategies for sample handling and prioritization for geological operations on other planetary surfaces, 2) assess the scientific contribution of selective in-situ sample characterization for mission planning, operations, and sample prioritization, 3) evaluate analytical instruments and tools for providing efficient and meaningful data in advance of sample return and 4) identify science operations that leverage human presence with robotic tools. In the first year of tests (2010), GeoLab examined basic glovebox operations performed by one and two crewmembers and science operations performed by a remote science team. The 2010 tests also examined the efficacy of basic sample characterization [descriptions, microscopic imagery, X-ray fluorescence (XRF) analyses] and feedback to the science team. In year 2 (2011), the GeoLab team tested enhanced software and interfaces for the crew and science team (including Web-based and mobile device displays) and demonstrated laboratory configurability with a new diagnostic instrument (the Multispectral Microscopic Imager from the JPL and Arizona State University). In year 3 (2012), the GeoLab team installed and tested a robotic sample manipulator and evaluated robotic-human interfaces for science operations.

Evans, Cynthia↗

X-29A flight control system performance during flight test

An account is given of flight control system performance results for the X-29A forward-swept wing 'Advanced Technology Demonstrator' fighter aircraft, with attention to its software and hardware components' achievement of the requisite levels of system stability and desirable aircraft handling qualities. The Automatic Camber Control Logic is found to be well integrated with the stability loop of the aircraft. A number of flight test support software programs developed by NASA facilitated monitoring of the X-29A's stability in real time, and allowed the test team to clear the envelope with confidence.

Chin, J.↗

Using ACIS on the Chandra X-ray Observatory as a Particle Radiation Monitor II

The Advanced CCD Imaging Spectrometer is an instrument on the Chandra X-ray Observatory. CCDs are vulnerable to radiation damage, particularly by soft protons in the radiation belts and solar storms. The Chandra team has implemented procedures to protect ACIS during high-radiation events including autonomous protection triggered by an on-board radiation monitor. Elevated temperatures have reduced the effectiveness of the on-board monitor. The ACIS team has developed an algorithm which uses data from the CCDs themselves to detect periods of high radiation and a flight software patch to apply this algorithm is currently active on-board the instrument. In this paper, we explore the ACIS response to particle radiation through comparisons to a number of external measures of the radiation environment. We hope to better understand the efficiency of the algorithm as a function of the flux and spectrum of the particles and the time-profile of the radiation event.

Grant, C. E.↗

MPS Editor - An Integrated Sequencing Environment

In today's operations environment, the teams are smaller and need to be more efficient while still ensuring the safety and success of the mission. In addition, teams often begin working on a mission in its early development phases and continue on the team through actual operations. For these reasons the operations teams want to be presented with a software environment that integrates multiple needed software applications as well as providing them with context sensitive editing support for entering commands and sequences of commands. At Jet Propulsion Laboratory, the Multi-Mission Planning and Sequencing (MPS) Editor provided by the Multi-Mission Ground Systems and Services (MGSS) supports those operational needs.

Streiffert, Barbara A.↗

Surface Operations Simulator and Scheduler (SOSS) Presentation

NASA - KAIA (Korea Agency for Infrastructure Technology Advancement) - KARI (Korea Aerospace Research Institute) collaboration surface air traffic management research has been ongoing since May 2015. In the first year collaboration, NASA's SOSS software has been transferred to KAIA and KARI teams to provide fast time simulation capability. Incheon International Airport model has been developed for SOSS.

surface traffic management↗