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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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NASA NTRS1991

CLIPS: A tool for the development and delivery of expert systems

The C Language Integrated Production System (CLIPS) is a forward chaining rule-based language developed by the Software Technology Branch at the Johnson Space Center. CLIPS provides a complete environment for the construction of rule-based expert systems. CLIPS was designed specifically to provide high probability, low cost, and easy integration with external systems. Other key features of CLIPS include a powerful rule syntax, an interactive development environment, high performance, extensibility, a verification/validation tool, extensive documentation, and source code availability. The current release of CLIPS, version 4.3, is being used by over 2,500 users throughout the public and private community including: all NASA sites and branches of the military, numerous Federal bureaus, government contractors, 140 universities, and many companies.

Riley, Gary↗

NASA NTRS1989

A diagnostic prototype of the potable water subsystem of the Space Station Freedom ECLSS

In analyzing the baseline Environmental Control and Life Support System (ECLSS) command and control architecture, various processes are found which would be enhanced by the use of knowledge based system methods of implementation. The most suitable process for prototyping using rule based methods are documented, while domain knowledge resources and other practical considerations are examined. Requirements for a prototype rule based software system are documented. These requirements reflect Space Station Freedom ECLSS software and hardware development efforts, and knowledge based system requirements. A quick prototype knowledge based system environment is researched and developed.

Lukefahr, Brenda D.↗

NASA NTRS1996

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

artificial intelligence image processing knowledge↗

NASA NTRS1987

A systems engineering approach to automated failure cause diagnosis in space power systems

Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.

Dolce, James L.↗

NASA NTRS1989

Tracking and data relay satellite fault isolation and correction using PACES: Power and attitude control expert system

The Power and Attitude Control Expert System (PACES) is an object oriented and rule based expert system which provides spacecraft engineers with assistance in isolating and correcting problems within the Power and Attitude Control Subsystems of the Tracking and Data Relay Satellites (TDRS). PACES is designed to act in a consultant role. It will not interface to telemetry data, thus preserving full operator control over spacecraft operations. The spacecraft engineer will input requested information. This information will include telemetry data, action being performed, problem characteristics, spectral characteristics, and judgments of spacecraft functioning. Questions are answered either by clicking on appropriate responses (for text), or entering numeric values. A context sensitive help facility allows access to additional information when the user has difficulty understanding a question or deciding on an answer. The major functionality of PACES is to act as a knowledge rich system which includes block diagrams, text, and graphics, linked using hypermedia techniques. This allows easy movement among pieces of the knowledge. Considerable documentation of the spacecraft Power and Attitude Control Subsystems is embedded within PACES. The development phase of TDRSS expert system technology is intended to provide NASA with the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking and Data Relay Satellite Program.

Erikson, Carol-Lee↗

NASA NTRS1994

SCL: An off-the-shelf system for spacecraft control

In this age of shrinking military, civil, and commercial space budgets, an off-the-shelf solution is needed to provide a multimission approach to spacecraft control. A standard operational interface which can be applied to multiple spacecraft allows a common approach to ground and space operations. A trend for many space programs has been to reduce operational staff by applying autonomy to the spacecraft and to the ground stations. The Spacecraft Command Language (SCL) system developed by Interface and Control Systems, Inc. (ICS) provides an off-the-shelf solution for spacecraft operations. The SCL system is designed to provide a hyper-scripting interface which remains standard from program to program. The spacecraft and ground station hardware specifics are isolated to provide the maximum amount of portability from system to system. Uplink and downlink interfaces are also isolated to allow the system to perform independent of the communications protocols chosen. The SCL system can be used for both the ground stations and the spacecraft, or as a value added package for existing ground station environments. The SCL system provides an expanded stored commanding capability as well as a rule-based expert system on-board. The expert system allows reactive control on-board the spacecraft for functions such as electrical power systems (EPS), thermal control, etc. which have traditionally been performed on the ground. The SCL rule and scripting capability share a common syntax allowing control of scripts from rules and rules from scripts. Rather than telemeter over sampled data to the ground, the SCL system maintains a database on-board which is available for interrogation by the scripts and rules. The SCL knowledge base is constructed on the ground and uploaded to the spacecraft. The SCL system follows an open-systems approach allowing other tasks to communicate with SCL on the ground and in space. The SCL system was used on the Clementine program (launched January 25, 1994) and is required to have bidirectional communications with the guidance, navigation, and control (GNC) algorithms which were written as another task. Sequencing of the spacecraft maneuvers are handled by SCL, but the low-level thruster pulse commands are handled by the GNC software. Attitude information is reported back as telemetry, allowing the SCL expert system to inference on the changing data. The Clementine SCL flight software was largely reused from another Naval Center for Space Technology (NCST) satellite program. This paper details the SCL architecture and how an off-the-shelf solution makes sense for multimission spacecraft programs. The Clementine mission will be used as a case study in the application of the SCL to a 'fast track' program. The benefits of such a system in a 'better, cheaper, faster' climate will be discussed.

Buckley, Brian↗

NASA NTRS2015

Rule-Based Flight Software Cost Estimation

This paper discusses the fundamental process for the computation of Flight Software (FSW) cost estimates. This process has been incorporated in a rule-based expert system [1] that can be used for Independent Cost Estimates (ICEs), Proposals, and for the validation of Cost Analysis Data Requirements (CADRe) submissions. A high-level directed graph (referred to here as a decision graph) illustrates the steps taken in the production of these estimated costs and serves as a basis of design for the expert system described in this paper. Detailed discussions are subsequently given elaborating upon the methodology, tools, charts, and caveats related to the various nodes of the graph. We present general principles for the estimation of FSW using SEER-SEM as an illustration of these principles when appropriate. Since Source Lines of Code (SLOC) is a major cost driver, a discussion of various SLOC data sources for the preparation of the estimates is given together with an explanation of how contractor SLOC estimates compare with the SLOC estimates used by JPL. Obtaining consistency in code counting will be presented as well as factors used in reconciling SLOC estimates from different code counters. When sufficient data is obtained, a mapping into the JPL Work Breakdown Structure (WBS) from the SEER-SEM output is illustrated. For across the board FSW estimates, as was done for the NASA Discovery Mission proposal estimates performed at JPL, a comparative high-level summary sheet for all missions with the SLOC, data description, brief mission description and the most relevant SEER-SEM parameter values is given to illustrate an encapsulation of the used and calculated data involved in the estimates. The rule-based expert system described provides the user with inputs useful or sufficient to run generic cost estimation programs. This system's incarnation is achieved via the C Language Integrated Production System (CLIPS) and will be addressed at the end of this paper.

computational intelligence↗

NASA NTRS1986

A rule based computer aided design system

A Computer Aided Design (CAD) system is presented which supports the iterative process of design, the dimensional continuity between mating parts, and the hierarchical structure of the parts in their assembled configuration. Prolog, an interactive logic programming language, is used to represent and interpret the data base. The solid geometry representing the parts is defined in parameterized form using the swept volume method. The system is demonstrated with a design of a spring piston.

Premack, T.↗

NASA NTRS1986

An Ada inference engine for expert systems

The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.

Lavallee, David B.↗

NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Schwabacher, Mark A.↗

NASA NTRS1991

Planning and Resource Management in an Intelligent Automated Power Management System

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Morris, Robert A.↗

NASA NTRS1994

Diagnosing anomalies of spacecraft for space maintenance and servicing

Very often servicing of satellites is necessary to replace components which are responsible for anomalous behavior of satellite operations due to adverse interactions with the natural space environment. A major difficulty with this diagnosis is that those responsible for diagnosing these anomalies do not have the tools to assess the role of the space environment causing the anomaly. To address this issue, we have under development a new rule-based, expert system for diagnosing spacecraft anomalies. The knowledge base consists of over two-hundred rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Lauriente, Michael↗

NASA NTRS2007

Accident/Mishap Investigation System

InvestigationOrganizer (IO) is a Web-based collaborative information system that integrates the generic functionality of a database, a document repository, a semantic hypermedia browser, and a rule-based inference system with specialized modeling and visualization functionality to support accident/mishap investigation teams. This accessible, online structure is designed to support investigators by allowing them to make explicit, shared, and meaningful links among evidence, causal models, findings, and recommendations.

Keller, Richard↗

NASA NTRS1990

Rule-based mechanisms of learning for intelligent adaptive flight control

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Handelman, David A.↗

NASA NTRS1994

An expert system for configuring a network for a Milstar terminal

This paper describes a rule-based expert system which assists the user in configuring a network for Air Force terminals using the Milstar satellite system. The network configuration expert system approach uses CLIPS. The complexity of network configuration is discussed, and the methods used to model it are described.

Mahoney, Melissa J.↗

NASA NTRS1989

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗

NASA NTRS1996

Intelligent Tools for Planning Knowledge base Development and Verification

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

errors↗

NASA NTRS1986

Implementation of artificial intelligence rules in a data base management system

The intelligent front end prototype was transformed into a RIM-integrated system. A RIM-based expert system was written which demonstrated the developed capability. The use of rules to produce extensibility of the intelligent front end, including the concept of demons and rule manipulation rules were investigated. Innovative approaches such as syntax programming were to be considered.

Feyock, S.↗