Search NASA⌕ Search

SEARCH · Search NASA

Results for “knowledge systems”

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 271 records · Page 15

Spacelab Life Sciences-1 electrical diagnostics expert system

The Spacelab Life Sciences-1 (SLS-1) Electrical Diagnostic (SLED) expert system is a continuous real time knowledge-based system to monitor and diagnose electrical system problems in the Spacelab. After fault isolation, the SLED system provides corrective procedures and advice to the ground-based console operator. The SLED system updates its knowledge about the status of Spacelab every 3 seconds. The system supports multiprocessing of malfunctions and allows multiple failures to be handled simultaneously. Information which is readily available via a mouse click includes: general information about the system and each component, the electrical schematics, the recovery procedures of each malfunction, and an explanation of the diagnosis.

Kao, Cheng Y.↗

LOX Expert System

The LOX Expert System is a computer program which uses artificial intelligence (AI) techniques to diagnose instrumentation problems in the shuttle liquid oxygen fueling system. The KNOBS knowledge-based system is being modified for application to this problem. System functionality and fault isolation methods are described.

Scarl, E. A.↗

CARDS: A blueprint and environment for domain-specific software reuse

CARDS (Central Archive for Reusable Defense Software) exploits advances in domain analysis and domain modeling to identify, specify, develop, archive, retrieve, understand, and reuse domain-specific software components. An important element of CARDS is to provide visibility into the domain model artifacts produced by, and services provided by, commercial computer-aided software engineering (CASE) technology. The use of commercial CASE technology is important to provide rich, robust support for the varied roles involved in a reuse process. We refer to this kind of use of knowledge representation systems as supporting 'knowledge-based integration.'

Wallnau, Kurt C.↗

Intelligent systems technology infrastructure for integrated systems

Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.

Lum, Henry, Jr.↗

EVA and telerobot interaction

We are about to enter into a new era - that of astronauts working hand in hand with telerobots in space. This has been done to some degree with astronauts and the Space Station Shuttle's Remote Manipulator Arm. However, for the Space Station Freedom, not only will astronauts be working with the RMS type system but also with smaller, more dexterous systems such as the Flight Telerobotic Servicer (FTS). Because EVA time is a premium resource, the most effective use of the astronauts and the telerobot will be required. There may be some tasks for which it is most efficient to have both the EVA astronaut and the telerobot working together. This type of close integration has not occurred before and brings up many issues. Most of these issues are related to technology: communication must be infallible, new control systems and devices may be required, enhanced telerobot safety systems may be necessary. IVA operations may also be affected by the combined EVA telerobot tasks. There is also the issue of how the EVA astronaut and the telerobot work on separate tasks but at the same time. For both situations, research and development of at least some new technology is required; enhanced communication both by voice and data, sophisticated collision detection systems, more responsive controls and displays. These new systems or system enhancements may require knowledge base systems for their operation. Some of the important issues, types of tasks, the FTS capabilities, the technology that is needed to address those issues, and the possible impact on Space Station Freedom are reviewed.

Willshire, Kelli F.↗

Dan Goldin Presentation: Pathway to the Future

In the "Path to the Future" presentation held at NASA's Langley Center on March 31, 1999, NASA's Administrator Daniel S. Goldin outlined the future direction and strategies of NASA in relation to the general space exploration enterprise. NASA's Vision, Future System Characteristics, Evolutions of Engineering, and Revolutionary Changes are the four main topics of the presentation. In part one, the Administrator talks in detail about NASA's vision in relation to the NASA Strategic Activities that are Space Science, Earth Science, Human Exploration, and Aeronautics & Space Transportation. Topics discussed in this section include: space science for the 21st century, flying in mars atmosphere (mars plane), exploring new worlds, interplanetary internets, earth observation and measurements, distributed information-system-in-the-sky, science enabling understanding and application, space station, microgravity, science and exploration strategies, human mars mission, advance space transportation program, general aviation revitalization, and reusable launch vehicles. In part two, he briefly talks about the future system characteristics. He discusses major system characteristics like resiliencey, self-sufficiency, high distribution, ultra-efficiency, and autonomy and the necessity to overcome any distance, time, and extreme environment barriers. Part three of Mr. Goldin's talk deals with engineering evolution, mainly evolution in the Computer Aided Design (CAD)/Computer Aided Engineering (CAE) systems. These systems include computer aided drafting, computerized solid models, virtual product development (VPD) systems, networked VPD systems, and knowledge enriched networked VPD systems. In part four, the last part, the Administrator talks about the need for revolutionary changes in communication and networking areas of a system. According to the administrator, the four major areas that need cultural changes in the creativity process are human-centered computing, an infrastructure for distributed collaboration, rapid synthesis and simulation tools, and life-cycle integration and validation. Mr. Goldin concludes his presentation with the following maxim "Collaborate, Integrate, Innovate or Stagnate and Evaporate." He also answers some questions after the presentation.

Source record↗

A Survey of Knowledge Management Research & Development at NASA Ames Research Center

This chapter catalogs knowledge management research and development activities at NASA Ames Research Center as of April 2002. A general categorization scheme for knowledge management systems is first introduced. This categorization scheme divides knowledge management capabilities into five broad categories: knowledge capture, knowledge preservation, knowledge augmentation, knowledge dissemination, and knowledge infrastructure. Each of nearly 30 knowledge management systems developed at Ames is then classified according to this system. Finally, a capsule description of each system is presented along with information on deployment status, funding sources, contact information, and both published and internet-based references.

Keller, Richard M.↗

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Agricultural systems↗

Development of an Expert System for Representing Procedural Knowledge

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Georgeff, Michael P.↗

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

An Information Architecture facilitates the understanding and, hence, harnessing of the human system risk-related data supply chain which enhances the ability to securely collect, integrate, and share data assets that improve human system research and operations. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as a data supply chain), the Human Research Program (HRP) and Space Life Science Directorate (SLSD) are building an information architecture plan to leverage their existing, and often shared, IT infrastructure.

Buquo, Lynn E.↗

A primitive-based 3D object recognition system

An intermediate-level knowledge-based system for decomposing segmented data into three-dimensional primitives was developed to create an approximate three-dimensional description of the real world scene from a single two-dimensional perspective view. A knowledge-based approach was also developed for high-level primitive-based matching of three-dimensional objects. Both the intermediate-level decomposition and the high-level interpretation are based on the structural and relational matching; moreover, they are implemented in a frame-based environment.

Dhawan, Atam P.↗

Beyond knowledge capture: creating useful work-centric systems

Once you have successfully captured knowledge, the challenge then becomes one of creating an affective way to use that knowledge. Two high knowledge content systems developed at the Jet Propulsion Laboratory are presented as examples of work-centric systems, where the primary value to the user is in the content.

knowledge management environment knowledge capture↗

JD 7: The Sun and the Heliosphere as an Integrated System

As knowledge of the Sun and the heliosphere grows, it is becoming not only possible but preferable to view the global structure, the interaction with the local interstellar medium, and changes over a solar cycle as the behavior of an integrated system. This consideration motivated Joint Discussion 7, which was meant both to summarize the state of art at the time of IAU XXVand to solicit interest in this kind of approach. The Joint Discussion was arranged in four sections, two on processes that, beginning from the Sun s interior, model and shape the heliosphere (From the Transition Region to the Corona and beyond and From the Sun to the interstellar Medium), one on elemental abundances and particles in the corona and the heliosphere (Energetic Particles, Energetic Neutral Atoms and Composition) and one on forthcoming solar and heliospheric space missions. In the following we give a brief summary of the contributions presented at the JD in each section. An ext.cnded discussion of the topics cov- ered by JD is expected to appear in a comprehensive book on the Sun and the Heliosphere which will be edited by us and printed by Kluwer in year 2004. Posters which were exhibited as part of the Joint Discussion are listed at the end of this summary.

Suess, Steven T.↗

Analysis and Monitoring of Cyber-Physical Systems via Environmental Domain Knowledge & Modeling

While verifying adherence to a specification (i.e., specification-based testing) is important, the results are only as valid as the specification itself. Problematically, verifying a system specification must be done within the context of changing or even unknown environmental domain knowledge that could render the specification ineffective or incorrect. This issue is even more apparent in the context of self-adaptive systems, where uncertainty in both the system configuration and environment can impact the validity of the system. This paper introduces a method to explicitly model domain knowledge of the environment as a secondary system to enable design-time verification against documented environmental assumptions (i.e., those elements external to the system). In addition, run-time monitors are used to detect scenarios in the actual environment not specified by the modeled environmental domain knowledge. Rather than simply identifying unexpected inputs, our approach is able to identify run-time violations of the environmental domain knowledge, even when inputs appear valid based on the domain assumptions embedded in the system specification. These violations can then be used to correspondingly update the system and environmental specifications via automated run-time adaptation or subsequent design-time revisions. We illustrate our approach by applying our method to a running example of a goal-based model of a baby monitor.

Byron DeVries↗

Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

Bosworth, Edward L., Jr.↗

Object-oriented fault tree evaluation program for quantitative analyses

Object-oriented programming can be combined with fault free techniques to give a significantly improved environment for evaluating the safety and reliability of large complex systems for space missions. Deep knowledge about system components and interactions, available from reliability studies and other sources, can be described using objects that make up a knowledge base. This knowledge base can be interrogated throughout the design process, during system testing, and during operation, and can be easily modified to reflect design changes in order to maintain a consistent information source. An object-oriented environment for reliability assessment has been developed on a Texas Instrument (TI) Explorer LISP workstation. The program, which directly evaluates system fault trees, utilizes the object-oriented extension to LISP called Flavors that is available on the Explorer. The object representation of a fault tree facilitates the storage and retrieval of information associated with each event in the tree, including tree structural information and intermediate results obtained during the tree reduction process. Reliability data associated with each basic event are stored in the fault tree objects. The object-oriented environment on the Explorer also includes a graphical tree editor which was modified to display and edit the fault trees.

Patterson-Hine, F. A.↗

A cross-disciplinary response to improve test activities: The corporate memory capitalization in Ariane4 test domain

The Assembly, Integration, Test, and Validation (AIT/AIV) of the Ariane4 Vehicle Equipment Bay was held at Matra Marconi Space (MMS) site of Toulouse for several years. For this activity, incident interpretation necessitates a great deal of different knowledge. When complex faults occur, particularly those appearing during overall control tests, experts of various domains (EGSE, software, on-board equipment) have to join for investigation sessions. Thus, an assistance tool for the identification of faulty equipment will improve the efficiency of diagnosis and the overall productivity of test activities. As a solution, the Aramiihs laboratory proposed considering the opportunity of a knowledge based system intended to assist the tester in diagnosis. This knowledge based system is, in fact, a short-term achievement of a long-term goal which is the capitalization of corporate memory in the Ariane4 test domain. Aramiihs is a research unit where engineers from MMS and researchers from the IRIT-CNRS cooperate on problems concerning new types of man-system interaction.

Vo, Dinh Phuoc↗

An application of object-oriented knowledge representation to engineering expert systems

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

D S Logie↗