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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge.

Kawamura, K.↗
NASA NTRS1985

Research on an expert system for database operation of simulation-emulation math models. Volume 2, Phase 1: Results

A reference manual is provided for NESS, a simulation expert system. This manual gives user information regarding starting and operating NASA expert simulation system (NESS). This expert system provides an intelligent interface to a generic simulation program for spacecraft attitude control problems. A menu of the functions the system can perform is provided. Control repeated returns to this menu after executing each user request.

Kawamura, K.↗
NASA NTRS1984

The potential of expert systems for remote sensing

The use of expert systems for the interpretation of remote-sensing data is discussed. Expert-system architectures are described; the systems in use, under development, or proposed in various scientific and industrial fields are listed in a table; and three image-interpretation systems are briefly characterized. It is found that expert systems have the potential to perform repetitive interpretation of image data compiled from various remote-sensing satellites, especially to detect changes over time as in the case of deforestation. A system comprising an image interpreter, change interpreter, a cause interpreter, and a global data base is outlined and illustrated with a diagram.

Mooneyhan, D. W.↗
NASA NTRS1983

The potential of expert systems for remote sensing application

An overview of the status and potential of artificial intelligence-driven expert systems in the role of image data analysis is presented. An expert system is defined and its structure is summarized. Three such systems designed for image interpretation are outlined. The use of an expert system to detect changes on the earth's surface is discussed, and the components of a knowledge-based image interpretation system and their make-up are outlined. An example of how such a system should work for an area in the tropics where deforestation has occurred is presented as a sequence of situation/action decisions.

Mooneyhan, D. W.↗
NASA NTRS1985

Expert systems development and application

Current research in the application of expert systems to problems in the flight research environment is discussed. In what is anticipated to be a broad research area, a real time expert system flight status monitor has been identified as the initial project. This real time expert system flight status monitor is described in terms of concept, application, development, and schedule.

Duke, E. L.↗
NASA NTRS1985

Description of an experimental expert system flight status monitor

This paper describes an experimental version of an expert system flight status monitor being developed at the Dryden Flight Research Facility of the NASA Ames Research Center. This experimental expert system flight status monitor (ESSFSM) is supported by a specialized knowledge acquisition tool that provides the user with a powerful and easy-to-use documentation and rule construction tool. The EESFSM is designed to be a testbed for concepts in rules, inference mechanisms, and knowledge structures to be used in a real-time expert system flight status monitor that will monitor the health and status of the flight control system of state-of-the-art, high-performance, research aircraft.

Duke, E. L.↗
NASA NTRS1986

Integration of an expert system into a user interface language demonstration

The need for a User Interface Language (UIL) has been recognized by the Space Station Program Office as a necessary tool to aid in minimizing the cost of software generation by multiple users. Previous history in the Space Shuttle Program has shown that many different areas of software generation, such as operations, integration, testing, etc., have each used a different user command language although the types of operations being performed were similar in many respects. Since the Space Station represents a much more complex software task, a common user command language--a user interface language--is required to support the large spectrum of space station software developers and users. To assist in the selection of an appropriate set of definitions for a UIL, a series of demonstration programs was generated with which to test UIL concepts against specific Space Station scenarios using operators for the astronaut and scientific community. Because of the importance of expert system in the space station, it was decided that an expert system should be embedded in the UIL. This would not only provide insight into the UIL components required but would indicate the effectiveness with which an expert system could function in such an environment.

Stclair, D. C.↗
NASA NTRS1985

The blackboard model - A framework for integrating multiple cooperating expert systems

The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.

Erickson, W. K.↗
NASA NTRS1985

Expert systems for Space Station automation

The expert systems required for automating key functions of the Manned Space Station (MSS) are explored. It is necessary that the expert systems developed be flexible, degrade gracefully in the case of a failure, and be able to work with incomplete data. The AI systems will have to perform interpretation and diagnosis, design, prediction and induction, and monitoring and control functions. Both quantitative and qualitative reasoning capabilities need improvements, as do automatic verification techniques, explanation and learning capabilities, and the use of metaknowledge, i. e., knowledge about the knowledge contained in the knowledge base. Information retrieval, fault isolation and manufacturing process control demonstrations are needed to validate expert systems for the MSS.

Georgeff, M. P.↗
NASA NTRS1984

An application of expert systems technology to remotely sensed image analysis

In October of 1983, a project was initiated at NASA/Ames Research Center to design a prototype expert system capable of producing a preliminary land cover classification from an unsupervised classification of Landsat Multispectral Scanner (MSS) imagery and associated collateral data. This paper outlines the problem of determining land cover classes from an unsupervised classification, presents a brief overview of expert systems, and continues with a description of the design and current state of implementation of NASA/Ames' prototype Landsat MSS image analysis expert system.

Erickson, W. K.↗
NASA NTRS1985

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

The development of an expert system prototype for determining software functional requirements for NASA Goddard's Command Management System (CMS) is described. The role of the CMS is to transform general requests into specific spacecraft commands with command execution conditions. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Subjects covered include: the problem environment of determining CMS software functional requirements; the expert system approach for handling CMS requirements development; validation and evaluation procedures for the expert system.

Liebowitz, J.↗
NASA NTRS1986

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Rogers, J. L.↗
NASA NTRS1986

A prototype expert system in OPS5 for data error detection

A prototype expert system has been developed in the OPS5 language to perform error checking on data which spacecraft builders/users supply to the NASA Goddard Space Flight Center for processing on the Communications Link Analysis and Simulation System (CLASS) computer. This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules. In its operational phase, TRAPS will run in the Oak Ridge Production Language (ORPL) on the CLASS computer. ORPL, an implementation of OPS5 in MULTIFORTH on a desktop computer, is now being ported to SS-FORTH on the CLASS computer. This paper discusses the expert system problem domain, development approch, tools, results, and future plans stemming from the TRAPS project.

Rash, James↗
NASA NTRS1987

Using hybrid expert system approaches for engineering applications

In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a number of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.

Allen, R. H.↗
NASA NTRS1987

Verification issues for rule-based expert systems

Verification and validation of expert systems is very important for the future success of this technology. Software will never be used in non-trivial applications unless the program developers can assure both users and managers that the software is reliable and generally free from error. Therefore, verification and validation of expert systems must be done. The primary hindrance to effective verification and validation is the use of methodologies which do not produce testable requirements. An extension of the flight technique panels used in previous NASA programs should provide both documented requirements and very high levels of verification for expert systems.

Culbert, Chris↗
NASA NTRS1987

CLIPS: An expert system tool for delivery and training

The C Language Integrated Production System (CLIPS) is a forward chaining rule-based language. The requirements necessary for an expert system tool which is used for development, delivery, and training are examined. Because of its high portability, low cost, and ease of integration with external systems, CLIPS has great potential as an expert system tool for delivery and training. In addition, its representation flexibility, debugging aids, and performance, along with its other strengths, make it a viable alternative for expert system development.

Riley, Gary↗
NASA NTRS1987

Development of a coupled expert system for the spacecraft attitude control problem

A majority of the current expert systems focus on the symbolic-oriented logic and inference mechanisms of artificial intelligence (AI). Common rule-based systems employ empirical associations and are not well suited to deal with problems often arising in engineering. Described is a prototype expert system which combines both symbolic and numeric computing. The expert system's configuration is presented and its application to a spacecraft attitude control problem is discussed.

Kawamura, K.↗
NASA NTRS1987

Vapor Compression Distillation Subsystem (VCDS) Component Enhancement, Testing and Expert Fault Diagnostics Development, Volume 2

A wide variety of Space Station functions will be managed via computerized controls. Many of these functions are at the same time very complex and very critical to the operation of the Space Station. The Environmental Control and Life Support System is one group of very complex and critical subsystems which directly affects the ability of the crew to perform their mission. Failure of the Environmental Control and Life Support Subsystems are to be avoided and, in the event of failure, repair must be effected as rapidly as possible. Due to the complex and diverse nature of the subsystems, it is not possible to train the Space Station crew to be experts in the operation of all of the subsystems. By applying the concepts of computer-based expert systems, it may be possible to provide the necessary expertise for these subsystems in dedicated controllers. In this way, an expert system could avoid failures and extend the operating time of the subsystems even in the event of failure of some components, and could reduce the time to repair by being able to pinpoint the cause of a failure when one cannot be avoided.

Mallinak, E. S.↗