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At least 397 records · Page 22

Reliability and performance evaluation of systems containing embedded rule-based expert systems

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Beaton, Robert M.↗

Managing autonomy levels in the SSM/PMAD testbed

It is pointed out that when autonomous operations are mixed with those of a manual nature, concepts concerning the boundary of operations and responsibility become clouded. The space station module power management and distribution (SSM/PMAD) automation testbed has the need for such mixed-mode capabilities. The concept of managing the SSM/PMAD testbed in the presence of changing levels of autonomy is examined. A knowledge-based approach to implementing autonomy management in the distributed SSM/PMAD utilizing a centralized planning system is presented. Its knowledge relations and system-wide interactions are discussed, along with the operational nature of the currently functioning SSM/PMAD knowledge-based systems.

Ashworth, Barry R.↗

The Katydid system for compiling KEE applications to Ada

Components of a system known as Katydid are developed in an effort to compile knowledge-based systems developed in a multimechanism integrated environment (KEE) to Ada. The Katydid core is an Ada library supporting KEE object functionality, and the other elements include a rule compiler, a LISP-to-Ada translator, and a knowledge-base dumper. Katydid employs translation mechanisms that convert LISP knowledge structures and rules to Ada and utilizes basic prototypes of a run-time KEE object-structure library module for Ada. Preliminary results include the semiautomatic compilation of portions of a simple expert system to run in an Ada environment with the described algorithms. It is suggested that Ada can be employed for AI programming and implementation, and the Katydid system is being developed to include concurrency and synchronization mechanisms.

Filman, Robert E.↗

DataHub - Science data management in support of interactive exploratory analysis

DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactive nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc.) in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis is on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Handley, Thomas H., Jr.↗

DataHub: Science data management in support of interactive exploratory analysis

The DataHub addresses four areas of significant needs: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactives nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc), in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Handley, Thomas H., Jr.↗

DataHub: Science Data Management in Support of Interactive Exploratory Analysis

The DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, videlicet knowledge-based expert systems, science visualization, and science data management. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system.

science↗

SWAN: An expert system with natural language interface for tactical air capability assessment

SWAN is an expert system and natural language interface for assessing the war fighting capability of Air Force units in Europe. The expert system is an object oriented knowledge based simulation with an alternate worlds facility for performing what-if excursions. Responses from the system take the form of generated text, tables, or graphs. The natural language interface is an expert system in its own right, with a knowledge base and rules which understand how to access external databases, models, or expert systems. The distinguishing feature of the Air Force expert system is its use of meta-knowledge to generate explanations in the frame and procedure based environment.

Simmons, Robert M.↗

ATOS-1: Designing the infrastructure for an advanced spacecraft operations system

The space industry has identified the need to use artificial intelligence and knowledge based system techniques as integrated, central, symbolic processing components of future mission design, support and operations systems. Various practical and commercial constraints require that off-the-shelf applications, and their knowledge bases, are reused where appropriate and that different mission contractors, potentially using different KBS technologies, can provide application and knowledge sub-modules of an overall integrated system. In order to achieve this integration, which we call knowledge sharing and distributed reasoning, there needs to be agreement on knowledge representations, knowledge interchange-formats, knowledge level communications protocols, and ontology. Research indicates that the latter is most important, providing the applications with a common conceptualization of the domain, in our case spacecraft operations, mission design, and planning. Agreement on ontology permits applications that employ different knowledge representations to interwork through mediators which we refer to as knowledge agents. This creates the illusion of a shared model without the constraints, both technical and commercial, that occur in centralized or uniform architectures. This paper explains how these matters are being addressed within the ATOS program at ESOC, using techniques which draw upon ideas and standards emerging from the DARPA Knowledge Sharing Effort. In particular, we explain how the project is developing an electronic Ontology of Spacecraft Operations and how this can be used as an enabling component within space support systems that employ advanced software engineering. We indicate our hope and expectation that the core ontology developed in ATOS, will permit the full development of standards for such systems throughout the space industry.

Poulter, K. J.↗

Capturing flight system test engineering expertise: Lessons learned

Within a few years, JPL will be challenged by the most active mission set in history. Concurrently, flight systems are increasingly more complex. Presently, the knowledge to conduct integration and test of spacecraft and large instruments is held by a few key people, each with many years of experience. JPL is in danger of losing a significant amount of this critical expertise, through retirement, during a period when demand for this expertise is rapidly increasing. The most critical issue at hand is to collect and retain this expertise and develop tools that would ensure the ability to successfully perform the integration and test of future spacecraft and large instruments. The proposed solution was to capture and codity a subset of existing knowledge, and to utilize this captured expertise in knowledge-based systems. First year results and activities planned for the second year of this on-going effort are described. Topics discussed include lessons learned in knowledge acquisition and elicitation techniques, life-cycle paradigms, and rapid prototyping of a knowledge-based advisor (Spacecraft Test Assistant) and a hypermedia browser (Test Engineering Browser). The prototype Spacecraft Test Assistant supports a subset of integration and test activities for flight systems. Browser is a hypermedia tool that allows users easy perusal of spacecraft test topics. A knowledge acquisition tool called ConceptFinder which was developed to search through large volumes of data for related concepts is also described and is modified to semi-automate the process of creating hypertext links.

Woerner, Irene Wong↗

Atmosphere Revitalization Technology Development for Crewed Space Exploration

As space exploration objectives extend human presence beyond low Earth orbit, the solutions to technological challenges presented by supporting human life in the hostile space environment must build upon experience gained during past and present crewed space exploration programs. These programs and the cabin atmosphere revitalization process technologies and systems developed for them represent the National Aeronautics and Space Administration s (NASA) past and present operational knowledge base for maintaining a safe, comfortable environment for the crew. The contributions of these programs to the NASA s technological and operational working knowledge base as well as key strengths and weaknesses to be overcome are discussed. Areas for technological development to address challenges inherent with the Vision for Space Exploration (VSE) are presented and a plan for their development employing unit operations principles is summarized

Perry, Jay L.↗

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗

Life insurance risk assessment using a fuzzy logic expert system

In this paper, we present a knowledge based system that combines fuzzy processing with rule-based processing to form an improved decision aid for evaluating risk for life insurance. This application illustrates the use of FuzzyCLIPS to build a knowledge based decision support system possessing fuzzy components to improve user interactions and KBS performance. The results employing FuzzyCLIPS are compared with the results obtained from the solution of the problem using traditional numerical equations. The design of the fuzzy solution consists of a CLIPS rule-based system for some factors combined with fuzzy logic rules for others. This paper describes the problem, proposes a solution, presents the results, and provides a sample output of the software product.

Carreno, Luis A.↗

Reflexive reasoning for distributed real-time systems

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

Goldstein, David↗

Understanding natural language for spacecraft sequencing

The paper describes a natural language understanding system, START, that translates English text into a knowledge base. The understanding and the generating modules of START share a Grammar which is built upon reversible transformations. Users can retrieve information by querying the knowledge base in English; the system then produces an English response. START can be easily adapted to many different domains. One such domain is spacecraft sequencing. A high-level overview of sequencing as it is practiced at JPL is presented in the paper, and three areas within this activity are identified for potential application of the START system. Examples are given of an actual dialog with START based on simulated data for the Mars Observer mission.

Katz, Boris↗

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Wang, Lui↗

Smart Aerospace eCommerce: Using Intelligent Agents in a NASA Mission Services Ordering Application

This paper describes how intelligent agent technology was successfully prototyped and then deployed in a smart eCommerce application for NASA. An intelligent software agent called the Intelligent Service Validation Agent (ISVA) was added to an existing web-based ordering application to validate complex orders for spacecraft mission services. This integration of intelligent agent technology with conventional web technology satisfies an immediate NASA need to reduce manual order processing costs. The ISVA agent checks orders for completeness, consistency, and correctness, and notifies users of detected problems. ISVA uses NASA business rules and a knowledge base of NASA services, and is implemented using the Java Expert System Shell (Jess), a fast rule-based inference engine. The paper discusses the design of the agent and knowledge base, and the prototyping and deployment approach. It also discusses future directions and other applications, and discusses lessons-learned that may help other projects make their aerospace eCommerce applications smarter.

Moleski, Walt↗

Thermostructural responses of carbon phenolics in a restrained thermal growth test

The thermostructural response of carbon phenolic components in a solid rocket motor (SRM) is a complex process. It involves simultaneous heat and mass transfer along with chemical reactions in a multiphase system with time-dependent material properties and boundary conditions. In contrast to metals, the fracture of fiber-reinforced composites is characterized by the initiation and progression of multiple failures of different modes such as matrix cracks, interfacial debonding, fiber breaks, and delamination. The investigation of thermostructural responses of SRM carbon phenolics is further complicated by different failure modes under static and dynamic load applications. Historically, there have been several types of post-firing anomalies found in the carbon phenolic composites of the Space Shuttle SRM nozzle. Three major failure modes which have been observed on SRM nozzles are pocketing (spallation), ply-lift, and wedge-out. In order to efficiently control these anomalous phenomena, an investigation of fracture mechanisms under NASA/MSFC RSRM (Redesigned Solid Rocket Motor) and SPIP (Solid Propulsion Integrity Program) programs have been conducted following each anomaly. This report reviews the current progress in understanding the effects of the thermostructural behavior of carbon phenolics on the failure mechanisms of the SRM nozzle. A literature search was conducted and a technical bibliography was developed to support consolidation and assimilation of learning from the RSRM and SPIP investigation efforts. Another important objective of this report is to present a knowledge-based design basis for carbon phenolics that combines the analyses of thermochemical decomposition, pore pressure stresses, and thermostructural properties. Possible areas of application of the knowledge-based design include critical material properties development, nozzle component design, and SRM materials control.

Wang, C. Jeff↗

The generic task toolset: High level languages for the construction of planning and problem solving systems

The current generation of languages for the construction of knowledge-based systems as being at too low a level of abstraction is criticized, and the need for higher level languages for building problem solving systems is advanced. A notion of generic information processing tasks in knowledge-based problem solving is introduced. A toolset which can be used to build expert systems in a way that enhances intelligibility and productivity in knowledge acquistion and system construction is described. The power of these ideas is illustrated by paying special attention to a high level language called DSPL. A description is given of how it was used in the construction of a system called MPA, which assists with planning in the domain of offensive counter air missions.

Chandrasekaran, B.↗