SEARCH · Engineering Papers

Results for “Knowledge bases”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

NASA NTRS2021

A Mathematical Analysis of an Example Delay Tolerant Network using the Theory of Sheaves

NASA’s High-Data Rate Architecture (HiDRA) project is working towards a general yet practical toolkit and knowledge base to help usher in the era of new technologies for space systems communications, such as optical links. The High-Rate Delay Tolerant Networking (HDTN) implementation falls under the umbrellas of both the toolkit and the knowledge base, as its advancements illuminate more general areas of Delay Tolerant Networking (DTN) that need growth. The goal of this paper is to explore the usage of particular mathematical machineries, namely temporal flow networks and sheaves, to identify fundamental, underlying structures in DTN for space systems. Satellites, space assets, ground stations, etc. give rise to a disconnected network, and it is the goal of DTN to glue disparate links together into a cohesive system, that is, a network. Depending on a given link, the latencies might be beyond that which the Transmission Control Protocol (TCP) can handle, and contact times might have one-way light times in excess of minute (sometimes significantly longer). Some links might be periodic (say, due to orbital mechanics) or they might not be. This diversity has made it difficult to probe the underlying structure. An immediate consequence is that DTNs in practice today are controlled by globally distributed contact plans (schedules), which are the input to the contact graph routing (CGR) algorithm. While this is effective for smaller networks, it will be very difficult to scale for future networks. Deeper and more rigorous theory is needed to bring DTN to the next evolutionary step. To this end, this paper introduces and suggests a mathematical framework for DTN, and applies it to a space network that is simulated using an orbital analysis toolkit. The tag-line for the structure known as sheaves is that they are the mathematically precise way of gluing local data together into unique, global data. If we consider routing, we see that networking is a “sheafy” science. We then discuss a simplified sheaf model, known as the cellular sheaf. The sheaf-theoretic analysis is presented and discussed, as it is hoped that this and related papers will help form the primordial ooze of DTN theory. Finally there is a section of future work suggesting follow-on research.

Delay Tolerant Networking↗

NASA NTRS1988

Space Station power system autonomy demonstration

The Systems Autonomy Demonstration Program (SADP) represents NASA's major effort to demonstrate, through a series of complex ground experiments, the application and benefits of applying advanced automation technologies to the Space Station project. Lewis Research Center (LeRC) and Marshall Space Flight Center (MSFC) will first jointly develop an autonomous power system using existing Space Station testbed facilities at each center. The subsequent 1990 power-thermal demonstration will then involve the cooperative operation of the LeRC/MSFC power system with the Johnson Space Center (JSC's) thermal control and DMS/OMS testbed facilities. The testbeds and expert systems at each of the NASA centers will be interconnected via communication links. The appropriate knowledge-based technology will be developed for each testbed and applied to problems requiring intersystem cooperation. Primary emphasis will be focused on failure detection and classification, system reconfiguration, planning and scheduling of electrical power resources, and integration of knowledge-based and conventional control system software into the design and operation of Space Station testbeds.

Kish, James A.↗

NASA NTRS1992

Fuzzy and neural control

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Berenji, Hamid R.↗

NASA NTRS1991

Engineering monitoring expert system's developer

This research project is designed to apply artificial intelligence technology including expert systems, dynamic interface of neural networks, and hypertext to construct an expert system developer. The developer environment is specifically suited to building expert systems which monitor the performance of ground support equipment for propulsion systems and testing facilities. The expert system developer, through the use of a graphics interface and a rule network, will be transparent to the user during rule constructing and data scanning of the knowledge base. The project will result in a software system that allows its user to build specific monitoring type expert systems which monitor various equipments used for propulsion systems or ground testing facilities and accrues system performance information in a dynamic knowledge base.

Lo, Ching F.↗

NASA NTRS1992

A rule-based system for real-time analysis of control systems

An approach to automate the real-time analysis of flight critical health monitoring and system status is being developed and evaluated at the NASA Dryden Flight Research Facility. A software package was developed in-house and installed as part of the extended aircraft interrogation and display system. This design features a knowledge-base structure in the form of rules to formulate interpretation and decision logic of real-time data. This technique has been applied for ground verification and validation testing and flight testing monitoring where quick, real-time, safety-of-flight decisions can be very critical. In many cases post processing and manual analysis of flight system data are not required. The processing is described of real-time data for analysis along with the output format which features a message stack display. The development, construction, and testing of the rule-driven knowledge base, along with an application using the X-31A flight test program, are presented.

Larson, Richard R.↗

NASA NTRS1990

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

Mitchell, Christine M.↗

NASA NTRS1988

Cooperating expert systems for Space Station - Power/thermal subsystem testbeds

The Systems Autonomy Demonstration Project (SADP) is a NASA-sponsored series of increasingly complex demonstrations to show the benefits of integrating knowledge-based systems with conventional process control in real-time, real-world problem domains that can facilitate the operations and availability of major Space Station distributed systems. This paper describes the system design, objectives, approaches, and status of each of the testbed knowledge-based systems. Simplified schematics of the systems are shown.

Wong, Carla M.↗

NASA NTRS2004

Inductive System Health Monitoring

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 uses 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. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

Iverson, David L.↗

NASA NTRS1987

SWITCH user's manual

The planning program, SWITCH, and its surrounding changed-goal-replanning program, Runaround, are described. The evolution of SWITCH and Runaround from an earlier planner, DEVISER, is recounted. SWITCH's plan representation, and its process of building a plan by backward chaining with strict chronological backtracking, are described. A guide for writing knowledge base files is provided, as are narrative guides for installing the program, running it, and interacting with it while it is running. Some utility functions are documented. For the sake of completeness, a narrative guide to the experimental discrepancy-replanning feature is provided. Appendices contain knowledge base files for a blocksworld domain, and a DRIBBLE file illustrating the output from, and user interaction with, the program in that domain.

Source record↗

NASA NTRS1990

Automated domain decomposition for computational fluid dynamics

Automation of flow-field zoning in two-dimensions is an important step towards easing the three-dimensional grid generation bottleneck in computational fluid dynamics. A knowledge-based approach works well, but several aspects of flow-field zoning make the use of such an approach challenging. A proposed model and language to describe the process of zoning a flow field are presented, followed by a discussion of the implementation of EZGrid, a knowledge-based two-dimensional (2-D) flow-field zoner. Results are shown for representative two-dimensional aerodynamic configurations. Finally, an approach to the evaluation of flow-field zonings is described and used to compare the performance of EZGrid with that of a human expert.

Vogel, Alison Andrews↗

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 NTRS1988

SPECTRUM - A system for the analysis of imaging spectrometer data

This paper examines several design issues related to the development of SPECTRUM, a knowledge-based system for the geological interpretation of imaging spectrometer data. SPECTRUM is implemented using a combination of the programming languages STAR and C, which are coupled both at the level of procedures - involving function calls between the two languages - and at the level of data structures - involving the formation of a hybrid knowledge base shared by the two languages. Aspects of the coupling relating to each level of the implementation are described, followed by a listing of general observations regarding the coupling of symbolic and numerical techniques as extracted from the SPECTRUM project.

Borchardt, Gary C.↗

NASA NTRS2008

Spline-Based Smoothing of Airfoil Curvatures

Constrained fitting for airfoil curvature smoothing (CFACS) is a splinebased method of interpolating airfoil surface coordinates (and, concomitantly, airfoil thicknesses) between specified discrete design points so as to obtain smoothing of surface-curvature profiles in addition to basic smoothing of surfaces. CFACS was developed in recognition of the fact that the performance of a transonic airfoil is directly related to both the curvature profile and the smoothness of the airfoil surface. Older methods of interpolation of airfoil surfaces involve various compromises between smoothing of surfaces and exact fitting of surfaces to specified discrete design points. While some of the older methods take curvature profiles into account, they nevertheless sometimes yield unfavorable results, including curvature oscillations near end points and substantial deviations from desired leading-edge shapes. In CFACS as in most of the older methods, one seeks a compromise between smoothing and exact fitting. Unlike in the older methods, the airfoil surface is modified as little as possible from its original specified form and, instead, is smoothed in such a way that the curvature profile becomes a smooth fit of the curvature profile of the original airfoil specification. CFACS involves a combination of rigorous mathematical modeling and knowledge-based heuristics. Rigorous mathematical formulation provides assurance of removal of undesirable curvature oscillations with minimum modification of the airfoil geometry. Knowledge-based heuristics bridge the gap between theory and designers best practices. In CFACS, one of the measures of the deviation of an airfoil surface from smoothness is the sum of squares of the jumps in the third derivatives of a cubicspline interpolation of the airfoil data. This measure is incorporated into a formulation for minimizing an overall deviation- from-smoothness measure of the airfoil data within a specified fitting error tolerance. CFACS has been extensively tested on a number of supercritical airfoil data sets generated by inverse design and optimization computer programs. All of the smoothing results show that CFACS is able to generate unbiased smooth fits of curvature profiles, trading small modifications of geometry for increasing curvature smoothness by eliminating curvature oscillations and bumps (see figure).

Li, W.↗

NASA NTRS1991

Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

Goldstein, David↗

NASA NTRS1988

A space station onboard scheduling assistant

One of the goals for the Space Station is to achieve greater autonomy, and have less reliance on ground commanding than previous space missions. This means that the crew will have to take an active role in scheduling and rescheduling their activities onboard, perhaps working from preliminary schedules generated on the ground. Scheduling is a time intensive task, whether performed manually or automatically, so the best approach to solving onboard scheduling problems may involve crew members working with an interactive software scheduling package. A project is described which investigates a system that uses knowledge based techniques for the rescheduling of experiments within the Materials Technology Laboratory of the Space Station. Particular attention is paid to: (1) methods for rapid response rescheduling to accommodate unplanned changes in resource availability, (2) the nature of the interface to the crew, (3) the representation of the many types of data within the knowledge base, and (4) the possibility of applying rule-based and constraint-based reasoning methods to onboard activity scheduling.

Brindle, A. F.↗

NASA NTRS1990

ISLE: Intelligent Selection of Loop Electronics. A CLIPS/C++/INGRES integrated application

The Intelligent Selection of Loop Electronics (ISLE) system is an integrated knowledge-based system that is used to configure, evaluate, and rank possible network carrier equipment known as Digital Loop Carrier (DLC), which will be used to meet the demands of forecasted telephone services. Determining the best carrier systems and carrier architectures, while minimizing the cost, meeting corporate policies and addressing area service demands, has become a formidable task. Network planners and engineers use the ISLE system to assist them in this task of selecting and configuring the appropriate loop electronics equipment for future telephone services. The ISLE application is an integrated system consisting of a knowledge base, implemented in CLIPS (a planner application), C++, and an object database created from existing INGRES database information. The embedibility, performance, and portability of CLIPS provided us with a tool with which to capture, clarify, and refine corporate knowledge and distribute this knowledge within a larger functional system to network planners and engineers throughout U S WEST.

Fischer, Lynn↗

NASA NTRS1996

Method of Testing and Predicting Failures of Electronic Mechanical Systems

A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

Iverson, David L.↗

NASA NTRS1990

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

Source record↗