Search NASA⌕ Search

SEARCH · Search NASA

Results for “knowledge engineering”

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.

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

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Stclair, D. C.↗
NASA NTRS1995

SPARTNIK: Engineering catalyst for government and industry

Industrial demands for highly motivated and competent technical personnel to carry forward with the technological goals of the US has posed a significant challenge to graduating engineers. While curricula has improved and diversified over time to meet these industry demands, relevant industry experience is not always available to undergraduates. The microsatellite development program at San Jose State University (SJSU) has allowed an entire undergraduate senior class to utilize a broad range of training and education to refine their engineering skills, bringing them closer to becoming engineering professionals. Close interaction with industry mentors and manufacturers on a real world project provides a significant advantage to educators and students alike. With support from companies and government agencies, the students have designed and manufactured a microsatellite, designed to be launched into a low Earth orbit. This satellite will gather telemetry for characterizing the state of the spacecraft. This will enable the students to have a physical check on their predicted value of spacecraft subsystem performance. Additional experiments will also be undertaken during the two year lifetime, including micro-meteorite impact sensing and capturing digital color images of the Earth. This paper will detail the process whereby students designed, prototype and manufactured a small satellite in a large team environment, along with the experiments that will be performed on board. With the project's limited funds, it needed the support of many industry companies to help with technical issues and hardware acquisition. Among the many supporting companies, NASA's space shuttle small payloads program could be used for an affordable launch vehicle for the student project. The paper address these collaborations between the student project and industry support, as well as explaining the benefits to both. The paper draws conclusion on how these types of student projects can be used by industry as a feasible resource for developing small platforms for space based experiments, as well as increasing the practical experience and engineering knowledge of graduating students. These benefits to industry and universities, can lead to a close working relationship between the two. These types of projects can facilitate the development of low-cost space rated parts to be used by the industry and university projects. It can also help with the understanding and use of acceptable risk non-space rated parts reducing the cost of the spacecraft. This will lead to the development of low cost platforms for space based experiments, providing research companies an inexpensive, long duration platform to conduct their in-space experiments, while better preparing engineering undergraduates for their transition into the work force.

Prass, James D.↗
NASA NTRS1992

Proceedings of the Workshop on Change of Representation and Problem Reformulation

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Lowry, Michael R.↗
NASA NTRS1993

An expert system shell for inferring vegetation characteristics: Changes to the historical cover type database (Task F)

All the options in the NASA VEGetation Workbench (VEG) make use of a database of historical cover types. This database contains results from experiments by scientists on a wide variety of different cover types. The learning system uses the database to provide positive and negative training examples of classes that enable it to learn distinguishing features between classes of vegetation. All the other VEG options use the database to estimate the error bounds involved in the results obtained when various analysis techniques are applied to the sample of cover type data that is being studied. In the previous version of VEG, the historical cover type database was stored as part of the VEG knowledge base. This database was removed from the knowledge base. It is now stored as a series of flat files that are external to VEG. An interface between VEG and these files was provided. The interface allows the user to select which files of historical data to use. The files are then read, and the data are stored in Knowledge Engineering Environment (KEE) units using the same organization of units as in the previous version of VEG. The interface also allows the user to delete some or all of the historical database units from VEG and load new historical data from a file. This report summarizes the use of the historical cover type database in VEG. It then describes the new interface to the files containing the historical data. It describes minor changes that were made to VEG to enable the externally stored database to be used. Test runs to test the operation of the new interface and also to test the operation of VEG using historical data loaded from external files are described. Task F was completed. A Sun cartridge tape containing the KEE and Common Lisp code for the new interface and the modified version of the VEG knowledge base was delivered to the NASA GSFC technical representative.

Source record↗
DOE OSTI2024

Effects of residual oxygen on superconducting niobium films

The integration of niobium (Nb) into emerging superconducting circuits can enhance their performance and function. However, growth of high purity Nb can be challenging due to its high reactivity with oxygen. Here, in this study, we examine the role of residual oxygen inside the growth chamber in transforming the structural, chemical, and superconducting properties of Nb films. We demonstrate that an increase in unintentional oxygen impurities lowers the superconducting critical temperature of Nb. This evolution coincides with the reduction of Nb crystal domains, which are separated by highly disordered oxygen-rich regions. Moreover, chemical analysis reveals the formation of niobium monoxide within the film during growth. These findings provide a comprehensive picture of how residual oxygen in the growth chamber can affect the properties of the Nb films. This study contributes to the materials science and engineering knowledge of superconducting Nb growth.

36 MATERIALS SCIENCE↗
NASA NTRS1971

Remote sensor support requirements for planetary missions

The study approach, methods, results, and conclusions of remote sensor support requirements for planetary missions are summarized. Major efforts were made to (1) establish the scientific and engineering knowledge and observation requirements for planetary exploration in the 1975 to 1985 period; (2) define the state of the art and expected development of instrument systems appropriate for sensing planetary environments; (3) establish scaling laws relating performance and support requirements of candidate remote sensor systems; (4) establish fundamental remote sensor system capabilities, limitations, and support requirements during encounter and other dynamical conditions for specific missions; and (5) construct families of candidate remote sensors compatible with selected missions. It was recommended that these data be integrated with earlier results to enhance utility, and that more restrictions be placed on the system.

Weddell, J. B.↗
NASA NTRS1984

Using knowledge of agricultural practices to enhance through-the-season interpretation of Landsat data

Landsat data contain features that can be interpreted to produce information about crops, in support of crop estimation procedures. This paper considers ways in which detailed knowledge of agricultural practices and events might increase and improve the utilization of Landsat data in both the predictive and observational or measurement components of such procedures. Landsat observables related to agricultural practices and events throughout the cropping season are listed. Agricultural fields are identified as the preferred observational units for incorporating refined agricultural understanding, such as crop rotation patterns, into machine procedures. Uses of Landsat data from both prior seasons and the current season are considered, as is use of predictive models of crop appearance. The investigation of knowledge engineering systems tailored to through-the-season estimation problems is recommended for long range development.

Malila, W. A.↗
NASA NTRS1986

Lunar materials and processes

The paper surveys current information, describes some important unknowns about lunar materials, and discusses ways to gain more scientific and engineering knowledge concerning the industrial processes that could be used on the moon for the production of products useful in future enterprises in space. Lunar rocks and soils are rich in oxygen, but it is mostly chemically bound in silicates, so that chemical or thermal energy must be supplied to recover it. Iron and titanium are abundant and, in some of their known forms, readily recoverable; aluminum is plentiful but harder to extract. Methods for recovering lunar oxygen and metals fall into three classes: chemical, electrolytic, and dissociative, broadly characterized by their respective process temperatures. Examples of these methods are briefly discussed.

Burke, J. D.↗
NASA NTRS1985

Feasibility of expert systems to enhance Space Station subsystem controllers

Results are described from a project to build a prototype expert system for automated fault isolation and correction of a regenerative CO2 removal device that is typical of functions of the air revitalization group in the Space Station environmental control and life support system (ECLSS). The software was developed using one of the powerful commercial knowledge engineering environments. The goal of the project was to evaluate the feasibility of using a software development environment to rapidly design, construct, test, and change expert system software. The use of expert systems to enhance automatic controllers and the use of information on device design and on device troubleshooting and repair procedures in developing expert systems are discussed.

Malin, J. T.↗
NASA NTRS1985

Evaluation of expert systems - An approach and case study

Techniques that were applied in defining an expert system prototype for first-cut evaluations of the software functional requirements of NASA satellite command management activities are described. The prototype was developed using the Knowledge Engineering System. Criteria were selected for evaluating the satellite software before defining the expert system prototype. Application of the prototype system is illustrated in terms of the evaluation procedures used with the COBE satellite to be launched in 1988. The limited number of options which can be considered by the program mandates that biases in the system output must be well understood by the users.

Liebowitz, J.↗
NASA NTRS1987

Microprocessor control and networking for the amps breadboard

Future space missions will require more sophisticated power systems, implying higher costs and more extensive crew and ground support involvement. To decrease this human involvement, as well as to protect and most efficiently utilize this important resource, NASA has undertaken major efforts to promote progress in the design and development of autonomously managed power systems. Two areas being actively pursued are autonomous power system (APS) breadboards and knowledge-based expert system (KBES) applications. The former are viewed as a requirement for the timely development of the latter. Not only will they serve as final testbeds for the various KBES applications, but will play a major role in the knowledge engineering phase of their development. The current power system breadboard designs are of a distributed microprocessor nature. The distributed nature, plus the need to connect various external computer capabilities (i.e., conventional host computers and symbolic processors), places major emphasis on effective networking. The communications and networking technologies for the first power system breadboard/test facility are described.

Floyd, Stephen A.↗
NASA NTRS1987

Using output to evaluate and refine rules in rule-based expert systems

The techniques described provide an effective tool which knowledge engineers and domain experts can utilize to help in evaluating and refining rules. These techniques have been used successfully as learning mechanisms in a prototype adaptive diagnostic expert system and are applicable to other types of expert systems. The degree to which they constitute complete evaluation/refinement of an expert system depends on the thoroughness of their use.

St.clair, D. C.↗
NASA NTRS1988

AI and simulation: What can they learn from each other

Simulation and Artificial Intelligence share a fertile common ground both from a practical and from a conceptual point of view. Strengths and weaknesses of both Knowledge Based System and Modeling and Simulation are examined and three types of systems that combine the strengths of both technologies are discussed. These types of systems are a practical starting point, however, the real strengths of both technologies will be exploited only when they are combined in a common knowledge representation paradigm. From an even deeper conceptual point of view, one might even argue that the ability to reason from a set of facts (i.e., Expert System) is less representative of human reasoning than the ability to make a model of the world, change it as required, and derive conclusions about the expected behavior of world entities. This is a fundamental problem in AI, and Modeling Theory can contribute to its solution. The application of Knowledge Engineering technology to a Distributed Processing Network Simulator (DPNS) is discussed.

Colombano, Silvano P.↗
NASA NTRS1988

Requirements for a tool to aid in the development of expert systems for space station applications

The Space Station Program is currently in the early stages of design. The extended life of the program and the wide range of planned capabilities present NASA with a major challenge to make effective use of all available resources. Expert systems may represent one of the most important techniques NASA can use to improve performance and functionality of the Space Station. The recent growth in expert system applications has been spurred by the availability of commercial expert system development tools. These state-of-the-art tools provide multiple representation techniques, sophisticated user interfaces, and powerful development tools; allowing programmers to develop expert systems without requiring years of training in knowledge engineering. The requirements are described for a software tool to aid in the development and delivery of expert systems intended for use in the Space Station Program. The intent is to define a tool that would be useful for a very broad range of expert system applications.

Culbert, Chris↗
NASA NTRS1988

Benchmarking expert system tools

As part of its evaluation of new technologies, the Artificial Intelligence Section of the Mission Planning and Analysis Div. at NASA-Johnson has made timing tests of several expert system building tools. Among the production systems tested were Automated Reasoning Tool, several versions of OPS5, and CLIPS (C Language Integrated Production System), an expert system builder developed by the AI section. Also included in the test were a Zetalisp version of the benchmark along with four versions of the benchmark written in Knowledge Engineering Environment, an object oriented, frame based expert system tool. The benchmarks used for testing are studied.

Riley, Gary↗
NASA NTRS1988

Two implementations of the Expert System for the Flight Analysis System (ESFAS) project

A comparison is made between the two most sophisticated expert system building tools, the Automated Reasoning Tool (ART) and the Knowledge Engineering Environment (KEE). The same problem domain (ESFAS) was used in making the comparison. The Expert System for the Flight Analysis System (ESFAS) acts as an intelligent front end for the Flight Analysis System (FAS). FAS is a complex configuration controlled set of interrelated processors (FORTRAN routines) which will be used by the Mission Planning and Analysis Div. (MPAD) to design and analyze Shuttle and potential Space Station missions. Implementations of ESFAS are described. The two versions represent very different programming paradigms; ART uses rules and KEE uses objects. Due to each of the tools philosophical differences, KEE is implemented using a depth first traversal algorithm, whereas ART uses a user directed traversal method. Either tool could be used to solve this particular problem.

Wang, Lui↗
NASA NTRS1987

FIESTA: An operational decision aid for space network fault isolation

The Fault Tolerance Expert System for Tracking and Data Relay Satellite System (TDRSS) Applications (FIESTA) is a fault detection and fault diagnosis expert system being developed as a decision aid to support operations in the Network Control Center (NCC) for NASA's Space Network. The operational objectives which influenced FIESTA development are presented and an overview of the architecture used to achieve these goals are provided. The approach to the knowledge engineering effort and the methodology employed are also presented and illustrated with examples drawn from the FIESTA domain.

Lowe, Dawn↗
NASA NTRS1987

Expert systems built by the Expert: An evaluation of OPS5

Two expert systems were written in OPS5 by the expert, a Ph.D. astronomer with no prior experience in artificial intelligence or expert systems, without the use of a knowledge engineer. The first system was built from scratch and uses 146 rules to check for duplication of scientific information within a pool of prospective observations. The second system was grafted onto another expert system and uses 149 additional rules to estimate the spacecraft and ground resources consumed by a set of prospective observations. The small vocabulary, the IF this occurs THEN do that logical structure of OPS5, and the ability to follow program execution allowed the expert to design and implement these systems with only the data structures and rules of another OPS5 system as an example. The modularity of the rules in OPS5 allowed the second system to modify the rulebase of the system onto which it was grafted without changing the code or the operation of that system. These experiences show that experts are able to develop their own expert systems due to the ease of programming and code reusability in OPS5.

Jackson, Robert↗