Project development plan for launch instrumentation
Launch instrumentation development plan - instrumentation systems and services, reliability and quality assurance, procurement, funding, manpower, and management plan
GROUND SUPPORT EQUIPMENT↗
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Flight test experience with the F-8 digital fly-by-wire system
Flight test results of the F-8 digital fly-by-wire (DFBW) control system are presented and the implications for application to active control technology (ACT) are discussed. The F-8 DFBW system has several of the attributes of proposed ACT systems, so the flight test experience is helpful in assessing the capabilities of those systems. Topics of discussion include the predicted and actual flight performance of the control system, assessments of aircraft flying qualities and other piloting factors, software management and control, and operational experience.
Szalai, K. J.↗
Flight test experience with the F-8 digital fly-by-wire system
Flight test results of the F-8 digital fly by wire control system are presented and the implications for application to active control technology are discussed. The F-8 DFBW system has several of the attributes of proposed ACT systems, so the flight test experience is helpful in assessing the capabilities of those systems. Topics of discussion include the predicted and actual flight performance of the control system, assessments of aircraft flying qualities and other piloting factors, software management and control, and operational experience.
Szalai, K. J.↗
Annual Report to the NASA Administrator by the Aerospace Safety Advisory Panel on the Space Shuttle Program. Part 2: Summary of Information Developed in the Panel's Fact-Finding Activities
The panel focused its attention on those areas that are considered most significant for flight success and safety. Elements required for the Approach and Landing Test Program, the Orbital Flight Test Program, and those management systems and their implementation which directly affect safety, reliability, and quality control, were investigated. Ground facilities and the training programs for the ground and flight crews were studied. Of special interest was the orbiter thermal protection subsystems.
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IEEE/AIAA/NASA Digital Avionics Systems Conference, 9th, Virginia Beach, VA, Oct. 15-18, 1990, Proceedings
The present conference on digital avionics discusses vehicle-management systems, spacecraft avionics, special vehicle avionics, communication/navigation/identification systems, software qualification and quality assurance, launch-vehicle avionics, Ada applications, sensor and signal processing, general aviation avionics, automated software development, design-for-testability techniques, and avionics-software engineering. Also discussed are optical technology and systems, modular avionics, fault-tolerant avionics, commercial avionics, space systems, data buses, crew-station technology, embedded processors and operating systems, AI and expert systems, data links, and pilot/vehicle interfaces.
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Third International Symposium on Space Mission Operations and Ground Data Systems, part 2
Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The symposium papers focus on improvements in the efficiency, effectiveness, and quality of data acquisition, ground systems, and mission operations. New technology, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations. This volume covers expert systems, systems development tools and approaches, and systems engineering issues.
Rash, James L.↗
Demonstrating Autonomous Mission Operations Onboard the International Space Station
The NASA Autonomous Mission Operations (AMO) project conducted an experiment to turn over operation and management of selected International Space Station (ISS) sys- tems to the on-board crew. ISS crews managed two different spacecraft systems: the Total Organic Carbon Analyzer (TOCA), a water quality analyzer, and Station Support Com- puters (SSC) laptops, which are non-critical crew computer systems. These systems were selected because they are representative of systems a future crew may need to operate au- tonomously during a deep space mission. The crew autonomously operated these systems, taking on mission operations functions traditionally performed by support teams on the ground, using new software tools that provide decision support algorithms for planning, monitoring and fault management, hardware schematics, system briefs, and data displays that are normally unavailable to the crew. The experiment lasted seven months, during which ISS crews managed TOCA and SSCs on 22 occasions. The AMO software processed data from TOCA and SSCs continuously during this seven month period. The combined performance of the software and crew achieved a 88 success rate on managing TOCA activity, the system for which ground-truth was available.
Autonomous Mission Operations↗
Third International Symposium on Space Mission Operations and Ground Data Systems, part 1
Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The papers focus on improvements in the efficiency, effectiveness, productivity, and quality of data acquisition, ground systems, and mission operations. New technology, techniques, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations.
Rash, James L.↗
Information System Life-Cycle And Documentation Standards (SMAP DIDS)
Although not computer program, SMAP DIDS written to provide systematic, NASA-wide structure for documenting information system development projects. Each DID (data item description) outlines document required for top-quality software development. When combined with management, assurance, and life cycle standards, Standards protect all parties who participate in design and operation of new information system.
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Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine
High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.
Carl Malings↗
Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine
High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.
Carl Malings↗
Data management study, volume 5. Appendix E - Contractor data package quality assurance /QA/ Final report
Manufacturing verification tests for quality assurance and control data management on Voyager spacecraft
DATA HANDLING SYSTEM↗
Formal Methods Specification and Verification Guidebook for Software and Computer Systems: Planning and Technology Insertion - Volume 1
The Formal Methods Specification and Verification Guidebook for Software and Computer Systems describes a set of techniques called Formal Methods (FM), and outlines their use in the specification and verification of computer systems and software. Development of increasingly complex systems has created a need for improved specification and verification techniques. NASA's Safety and Mission Quality Office has supported the investigation of techniques such as FM, which are now an accepted method for enhancing the quality of aerospace applications. The guidebook provides information for managers and practitioners who are interested in integrating FM into an existing systems development process. Information includes technical and administrative considerations that must be addressed when establishing the use of FM on a specific project. The guidebook is intended to aid decision makers in the successful application of FM to the development of high-quality systems at reasonable cost. This is the first volume of a planned two-volume set. The current volume focuses on administrative and planning considerations for the successful application of FM.
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Performance Evaluation of a Data Validation System
Online data validation is a performance-enhancing component of modern control and health management systems. It is essential that performance of the data validation system be verified prior to its use in a control and health management system. A new Data Qualification and Validation (DQV) Test-bed application was developed to provide a systematic test environment for this performance verification. The DQV Test-bed was used to evaluate a model-based data validation package known as the Data Quality Validation Studio (DQVS). DQVS was employed as the primary data validation component of a rocket engine health management (EHM) system developed under NASA's NGLT (Next Generation Launch Technology) program. In this paper, the DQVS and DQV Test-bed software applications are described, and the DQV Test-bed verification procedure for this EHM system application is presented. Test-bed results are summarized and implications for EHM system performance improvements are discussed.
Wong, Edmond↗
Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs
The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.
Carl Malings↗
Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs
The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.
Nathan R. Pavlovic↗
Software Products
MAST is a decision support system to help in the management of dairy herds. Data is collected on dairy herds around the country and processed at regional centers. One center is Cornell University, where Dr. Lawrence Jones and his team developed MAST. The system draws conclusions from the data and summarizes it graphically. CLIPS, which is embedded in MAST, gives the system the ability to make decisions without user interaction. With this technique, dairy managers can identify herd problems quickly, resulting in improved animal health and higher milk quality. CLIPS (C Language Integrated Production System) was developed by NASA's Johnson Space Center. It is a shell for developing expert systems designed to permit research, development and delivery on conventional computers.
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Conceptual design and evaluation of selected Space Station concepts, volume 2
The partially closed cycle environmental control and Life Support Subsystems is examined. Components of the system include air pressure control, heat control, water management, air and water quality monitors, fire detection and suppression, personnel escape, and EVA support subsystems.
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