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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.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Knowledge-based fault monitoring and diagnosis in Space Shuttle propellant loading

The LOX Expert System (LES), now being developed as a tool for the constraint-based monitoring and analysis of propellant loading at the Kennedy Space Center (KSC), is discussed. The loading of LOX at the KSC and its control and monitoring by the Launch Processing System are summarized, and the relevant problem for LES is presented. The LES database is briefly described, and the interaction of LES with KNOBS, a constraint- and frame-oriented knowledge-based system developed as a demonstration system in aid of tactical air mission planning, is the context of launch processing is discussed in detail. The design and fault isolation techniques of LES are also discussed.

Scarl, E. A.↗
NASA NTRS1984

Present state of knowledge of the upper atmosphere: An assessment report

A program of research, technology, and monitoring of the phenomena of the upper atmosphere, to provide for an understanding of and to maintain the chemical and physical integrity of the Earth's upper atmosphere was developed. NASA implemented a long-range upper atmospheric science program aimed at developing an organized, solid body of knowledge of upper atmospheric processes while providing, in the near term, assessments of potential effects of human activities on the atmosphere. The effects of chlorofluorocarbon (CFC) releases on stratospheric ozone were reported. Issues relating the current understanding of ozone predictions and trends and highlights recent and future anticipated developments that will improve our understanding of the system are summarized.

Source record↗
NASA NTRS1986

Present state of knowledge of the upper atmosphere: An assessment report; processes that control ozone and other climatically important trace gases

The state of knowledge of the upper atmosphere was assessed as of January 1986. The physical, chemical, and radiative processes which control the spatial and temporal distribution of ozone in the atmosphere; the predicted magnitude of ozone perturbations and climate changes for a variety of trace gas scenarios; and the ozone and temperature data used to detect the presence or absence of a long term trend were discussed. This assessment report was written by a small group of NASA scientists, was peer reviewed, and is based primarily on the comprehensive international assessment document entitled Atmospheric Ozone 1985: Assessment of Our Understanding of the Processes Controlling Its Present Distribution and Change, to be published as the World Meteorological Organization Global Ozone Research and Monitoring Project Report No. 16.

Watson, R. T.↗
NASA NTRS1986

Automatic probabilistic knowledge acquisition from data

A computer program for extracting significant correlations of attributes from masses of data is outlined. This information can then be used to develop a knowledge base for a probabilistic expert system. The method determines the best estimate of joint probabilities of attributes from data put into contingency table form. A major output from the program is a general formula for calculating any probability relation associated with the data. These probability relations can be utilized to form IF-THEN rules with associated probability, useful for expert systems.

Gevarter, W. B.↗
NASA NTRS1986

Knowledge-based load leveling and task allocation in human-machine systems

Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

Chignell, M. H.↗
NASA NTRS1986

A knowledge-based expert system for scheduling of airborne astronomical observations

KAOS (Kuiper Airborne Observatory Scheduler) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

Nachtsheim, P. R.↗
NASA NTRS1986

Orbital transfer vehicle launch operations study: Automated technology knowledge base, volume 4

A simplified retrieval strategy for compiling automation-related bibliographies from NASA/RECON is presented. Two subsets of NASA Thesaurus subject terms were extracted: a primary list, which is used to obtain an initial set of citations; and a secondary list, which is used to limit or further specify a large initial set of citations. These subject term lists are presented in Appendix A as the Automated Technology Knowledge Base (ATKB) Thesaurus.

Source record↗
NASA NTRS1985

A knowledge-based expert system for scheduling of airborne astronomical observations

The Kuiper Airborne Observatory Scheduler (KAOS) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

Nachtsheim, P. R.↗
NASA NTRS1985

Progress in knowledge-based flight monitoring

Features and applications of the script-based flight monitor SECURE are described. Implemented on an on-board computer, SECURE treats a flight as a regular sequence of contexts (situations) defined in a knowledge base with a hierarchical structure for successively more finely delineated flight phases, i.e., takeoff, cruise and landing. SECURE provides normalcy references for flight monitoring and allows context identification, which allows the presentation of checklists. An implementation of SECURE, written in MACLISP, on a DC-10 flight simulator is described.

Chen, D. C.↗
NASA NTRS1987

Diagnosis and sensor validation through knowledge of structure and function

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗
NASA NTRS1988

Knowledge-Acquisition Tool For Expert System

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

Disbrow, James D.↗
NASA NTRS1987

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

Peuquet, Donna J.↗
NASA NTRS1987

Knowledge acquisition for a simple expert controller

A method is presented for process control which has the properties of being incremental, cyclic and top-down. It is described on the basis of the development of an expert controller for a simple, but nonlinear control route. A quality comparison between expert controller and process operator shows the ability of the method for knowledge acquisition.

Bieker, B.↗
NASA NTRS1987

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.↗
NASA NTRS1987

Temporal and contextual knowledge in model-based expert systems

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.

Toth-Fejel, Tihamer↗
NASA NTRS1987

Clips as a knowledge based language

CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system.

Harrington, James B.↗
NASA NTRS1987

HSTDEK: Developing a methodology for construction of large-scale, multi-use knowledge bases

The primary research objectives of the Hubble Space Telescope Design/Engineering Knowledgebase (HSTDEK) are to develop a methodology for constructing and maintaining large scale knowledge bases which can be used to support multiple applications. To insure the validity of its results, this research is being persued in the context of a real world system, the Hubble Space Telescope. The HSTDEK objectives are described in detail. The history and motivation of the project are briefly described. The technical challenges faced by the project are outlined.

Freeman, Michael S.↗
NASA NTRS1987

Similarity networks as a knowledge representation for space applications

Similarity networks are a powerful form of knowledge representation that are useful for many artificial intelligence applications. Similarity networks are used in applications ranging from information analysis and case based reasoning to machine learning and linking symbolic to neural processing. Strengths of similarity networks include simple construction, intuitive object storage, and flexible retrieval techniques that facilitate inferencing. Therefore, similarity networks provide great potential for space applications.

Bailey, David↗