Engineering topics

Feyock, Stefan

Publications and source records attributed to Feyock, Stefan.

11 records

NASA NTRS2002

A Uniform Ontology for Software Interfaces

It is universally the case that computer users who are not also computer specialists prefer to deal with computers' in terms of a familiar ontology, namely that of their application domains. For example, the well-known Windows ontology assumes that the user is an office worker, and therefore should be presented with a "desktop environment" featuring entities such as (virtual) file folders, documents, appointment calendars, and the like, rather than a world of machine registers and machine language instructions, or even the DOS command level. The central theme of this research has been the proposition that the user interacting with a software system should have at his disposal both the ontology underlying the system, as well as a model of the system. This information is necessary for the understanding of the system in use, as well as for the automatic generation of assistance for the user, both in solving the problem for which the application is designed, and for providing guidance in the capabilities and use of the system.

Feyock, Stefan↗

NASA NTRS1995

A path-oriented knowledge representation system: Defusing the combinatorial system

LIMAP is a programming system oriented toward efficient information manipulation over fixed finite domains, and quantification over paths and predicates. A generalization of Warshall's Algorithm to precompute paths in a sparse matrix representation of semantic nets is employed to allow questions involving paths between components to be posed and answered easily. LIMAP's ability to cache all paths between two components in a matrix cell proved to be a computational obstacle, however, when the semantic net grew to realistic size. The present paper describes a means of mitigating this combinatorial explosion to an extent that makes the use of the LIMAP representation feasible for problems of significant size. The technique we describe radically reduces the size of the search space in which LIMAP must operate; semantic nets of more than 500 nodes have been attacked successfully. Furthermore, it appears that the procedure described is applicable not only to LIMAP, but to a number of other combinatorially explosive search space problems found in AI as well.

Karamouzis, Stamos T.↗

NASA NTRS1993

A path-oriented matrix-based knowledge representation system

Experience has shown that designing a good representation is often the key to turning hard problems into simple ones. Most AI (Artificial Intelligence) search/representation techniques are oriented toward an infinite domain of objects and arbitrary relations among them. In reality much of what needs to be represented in AI can be expressed using a finite domain and unary or binary predicates. Well-known vector- and matrix-based representations can efficiently represent finite domains and unary/binary predicates, and allow effective extraction of path information by generalized transitive closure/path matrix computations. In order to avoid space limitations a set of abstract sparse matrix data types was developed along with a set of operations on them. This representation forms the basis of an intelligent information system for representing and manipulating relational data.

Feyock, Stefan↗

NASA NTRS1993

The use of multiple models in case-based diagnosis

The work described in this paper has as its goal the integration of a number of reasoning techniques into a unified intelligent information system that will aid flight crews with malfunction diagnosis and prognostication. One of these approaches involves using the extensive archive of information contained in aircraft accident reports along with various models of the aircraft as the basis for case-based reasoning about malfunctions. Case-based reasoning draws conclusions on the basis of similarities between the present situation and prior experience. We maintain that the ability of a CBR program to reason about physical systems is significantly enhanced by the addition to the CBR program of various models. This paper describes the diagnostic concepts implemented in a prototypical case based reasoner that operates in the domain of in-flight fault diagnosis, the various models used in conjunction with the reasoner's CBR component, and results from a preliminary evaluation.

Karamouzis, Stamos T.↗

NASA NTRS1993

Case-based approach to handling aircraft malfunctions

Reasoning about physical systems in operation is a difficult task, and any attempt to automate the process must overcome the problems of modeling normal behavior, diagnosing faults, and predicting future behavior. This paper describes a prototypical case-based reasoner (CBR) that operates in the domain of in-flight fault diagnosis and prognosis of aviation subsystems, particularly jet engines. The reasoner operates on the observation that the ability of a CBR program to reason about physical systems can be significantly enhanced by the addition to the CBR program of a model of the physical system to describe the system's structural, functional, and causal behavior.

Karamouzis, Stamos T.↗

NASA NTRS1991

Design of an intelligent information system for in-flight emergency assistance

The present research has as its goal the development of AI tools to help flight crews cope with in-flight malfunctions. The relevant tasks in such situations include diagnosis, prognosis, and recovery plan generation. Investigation of the information requirements of these tasks has shown that the determination of paths figures largely: what components or systems are connected to what others, how are they connected, whether connections satisfying certain criteria exist, and a number of related queries. The formulation of such queries frequently requires capabilities of the second-order predicate calculus. An information system is described that features second-order logic capabilities, and is oriented toward efficient formulation and execution of such queries.

Feyock, Stefan↗

NASA NTRS1990

Simulation-based reasoning about the physical propagation of fault effects

The research described deals with the effects of faults on complex physical systems, with particular emphasis on aircraft and spacecraft systems. Given that a malfunction has occurred and been diagnosed, the goal is to determine how that fault will propagate to other subsystems, and what the effects will be on vehicle functionality. In particular, the use of qualitative spatial simulation to determine the physical propagation of fault effects in 3-D space is described.

Feyock, Stefan↗

NASA NTRS1989

Automatic determination of fault effects on aircraft functionality

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

Feyock, Stefan↗

NASA NTRS1988

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

The purpose of this research effort is to investigate the benefits that might be derived from applying artificial intelligence tools in the area of conceptual design. Therefore, the emphasis is on the artificial intelligence aspects of conceptual design rather than structural and optimization aspects. A prototype knowledge-based system, called STRUTEX, was developed to initially configure a structure to support point loads in two dimensions. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user by integrating a knowledge base interface and inference engine, a data base interface, and graphics while keeping the knowledge base and data base files separate. The system writes a file which can be input into a structural synthesis system, which combines structural analysis and optimization.

Rogers, James L.↗

NASA NTRS1988

Implementing embedded artificial intelligence rules within algorithmic programming languages

Most integrations of artificial intelligence (AI) capabilities with non-AI (usually FORTRAN-based) application programs require the latter to execute separately to run as a subprogram or, at best, as a coroutine, of the AI system. In many cases, this organization is unacceptable; instead, the requirement is for an AI facility that runs in embedded mode; i.e., is called as subprogram by the application program. The design and implementation of a Prolog-based AI capability that can be invoked in embedded mode are described. The significance of this system is twofold: Provision of Prolog-based symbol-manipulation and deduction facilities makes a powerful symbolic reasoning mechanism available to applications programs written in non-AI languages. The power of the deductive and non-procedural descriptive capabilities of Prolog, which allow the user to describe the problem to be solved, rather than the solution, is to a large extent vitiated by the absence of the standard control structures provided by other languages. Embedding invocations of Prolog rule bases in programs written in non-AI languages makes it possible to put Prolog calls inside DO loops and similar control constructs. The resulting merger of non-AI and AI languages thus results in a symbiotic system in which the advantages of both programming systems are retained, and their deficiencies largely remedied.

Feyock, Stefan↗

NASA NTRS1987

Fault diagnosis based on continuous simulation models

The results are described of an investigation of techniques for using continuous simulation models as basis for reasoning about physical systems, with emphasis on the diagnosis of system faults. It is assumed that a continuous simulation model of the properly operating system is available. Malfunctions are diagnosed by posing the question: how can we make the model behave like that. The adjustments that must be made to the model to produce the observed behavior usually provide definitive clues to the nature of the malfunction. A novel application of Dijkstra's weakest precondition predicate transformer is used to derive the preconditions for producing the required model behavior. To minimize the size of the search space, an envisionment generator based on interval mathematics was developed. In addition to its intended application, the ability to generate qualitative state spaces automatically from quantitative simulations proved to be a fruitful avenue of investigation in its own right. Implementations of the Dijkstra transform and the envisionment generator are reproduced in the Appendix.

Feyock, Stefan↗