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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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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Extracting spectral albedo from NOAA-9 AVHRR multiple view data using an atmospheric correction procedure and an expert system

A 100 km by 200 km area of the Sahel was selected to demonstrate a new method of extracting hemispherical reflectance (albedo) from directional satellite data. Utilizing a stratification of the Gao region of Mali based on soil texture, satellite data for homogeneous areas were selected. These data were employed in a knowledge-based expert system called VEG, which is designed to handle a wide variety of types of input data. The calculated directional reflectance factors at ground level are very similar to ground measurements noted in the literature.

Kimes, D. S.↗
NASA NTRS1988

Heat exchanger expert system logic

The reduction is described of the operation and fault diagnostics of a Deep Space Network heat exchanger to a rule base by the application of propositional calculus to a set of logic statements. The value of this approach lies in the ease of converting the logic and subsequently implementing it on a computer as an expert system. The rule base was written in Process Intelligent Control software.

Cormier, R.↗
NASA NTRS1990

PI-in-a-box: An expert system to advise astronauts during experiments

Perhaps the scarcest resource for manned flight experiments - on Spacelab or on Space Station Freedom - will continue to be crew time. To maximize the efficiency of the crew, and to make use of their abilities to work as scientist collaborators as well as equipment operators, normally requires more training in a wide variety of disciplines than is practical. The successful application of on-board expert systems, as envisioned by the 'Principal Investigator (PI)-in-a-Box' program, should alleviate the training bottleneck and provide the astronaut with the guidance and coaching needed to permit him or her to operate an experiment according to the desires and knowledge of the PI, despite changes in conditions. In addition to the functions of providing expert devise concerning scheduling and repair, the program should bring the astronaut into the scientific evaluation phase of an experiment by sharing with him the guidance and observations regarding the relevance and importance of data as it is being generated. Initial reaction from the astronaut community has been positive.

Young, Laurence R.↗
NASA NTRS1992

The use of expert systems in combination with active and passive microwave data to classify sea ice

The authors report on a system for sea ice classification which combines passive and active microwave data with algorithmic and heuristic classification techniques in order to classify sea ice unambiguously. They describe initial algorithmic classification, extraction of features and symbolic information, the application of data-dependent expert systems, and the establishment of feature correspondence between data sets.

Haverkamp, Donna↗
NASA NTRS1988

An expert system approach to turbopump health monitoring

A preliminary report is presented on the development of a system for monitoring the High Pressure Oxidizer Turbopump of the SSME. System development will proceed by defining the degradation mechanism of the turbopump, identifying those conventional and advanced sensor measurements that can monitor these mechanisms, and determining the digital processing requirements for these measurements. Once the failures and associated measurements have been defined, an expert system will be developed that can make both diagnostic and prognostic inferences about the condition and performance of the turbopump.

Perry, John G.↗
NASA NTRS1998

An Image Retrieval and Processing Expert System for the World Wide Web

This paper presents a system that is being developed in the Laboratory of Applied Remote Sensing and Image Processing at the University of P.R. at Mayaguez. It describes the components that constitute its architecture. The main elements are: a Data Warehouse, an Image Processing Engine, and an Expert System. Together, they provide a complete solution to researchers from different fields that make use of images in their investigations. Also, since it is available to the World Wide Web, it provides remote access and processing of images.

Rodriguez, Ricardo↗
NASA NTRS1989

HST battery test expert systems

During the testing of nickel-cadmium and nickel-hydrogen batteries for the Hubble Space Telescope, an urgent need for data management was recognized. Testing of these batteries generates much needed data that is used for vital decision making, such as when to recondition, change the charging scheme, or adjust the workload of the batteries. To solve this problem, an expert system called NICBES was developed. NICBES can recognize a testbed anomaly, identify the malfunctioning component, recommend a course of action, evaluate battery status, and provide decision support. A description of NICBES and some of its enhancements are given.

Johnson, Yvette B.↗
NASA NTRS1993

Improved Real-Time Monitoring Using Multiple Expert Systems

Monitor/Analyzer of Real-Time Voyager Engineering Link (MARVEL) computer program implements combination of techniques of both conventional automation and artificial intelligence to improve monitoring of complicated engineering system. Designed to support ground-based operations of Voyager spacecraft, also adapted to other systems. Enables more-accurate monitoring and analysis of telemetry, enhances productivity of monitoring personnel, reduces required number of such personnel by performing routine monitoring tasks, and helps ensure consistency in face of turnover of personnel. Programmed in C language and includes commercial expert-system software shell also written in C.

Schwuttke, Ursula M.↗
NASA NTRS1992

A second generation expert system for checking and diagnosing AXAF's electric power system

AXAF - Advanced X-ray Astrophysics Facility - is a third NASA's great space observatory. Each of these observatories is intended to cover different parts of the electromagnetic spectrum (x-ray for AXAF) and to provide high resolution images of celestial sources in our universe. While the spacecraft is in orbit, the electric power system (EPS) performance is monitored via sensors measuring voltages, currents, pressures, and temperatures. The sensor data are sent from the spacecraft to the ground station as telemetry and analyzed on arrival. Monitoring, diagnosis and maintenance of such EPS is an arduous task which requires expertise and constant attention of the ground personnel. To help the ground crew in this task, much of it should be automated and delegated to expert systems, which draw engineer's attention to possible malfunctions and allows him to review the telemetry to determine the source of the trouble, diagnose the suspected fault and to propose a corrective action. Those systems are built on assumptions such as: (1) domain knowledge is available and can be represented as a set of rules; (2) domain knowledge is circumscribed, static, and monotonic; and (3) expert decision making can be emulated by a logical inference mechanism.

Bykat, Alex↗
NASA NTRS1988

Expert systems for adaptive control of large space structures

It is expected that space systems for the future will evolve to structures of unprecedented size with associated extreme control requirements. A method is necessary that is sufficiently general to initiate stable control of a vehicle and subsequently learn the true nature of the structure. It is suggested that a suitable constructed expert system (ES) would be capable of learning by appending observations to a knowledge base. To verify that an ES can control a large space structure, numerical simulations of a simple structure subjected to periodic vibrations and the performance of a classical controllers were performed. The ES was then exercised to show its ability to truthfully mimic nominal control and to demonstrate its superiority to the classical controller, given sensor failures. An ES generating software package, The Intelligent Machine Model, was employed. It uses the pattern matching technique. Results of this program are discussed.

Gartrell, Charles F.↗
NASA NTRS1985

On orbit mission planning using the shuttle trajectory and launch window expert system

With the Space Transportation System (STS) entering the operational era, the need for standardized, automated, mission planning computer tools has become apparent. In order to support an increased flight rate without an increase in manpower, quicker and more efficient methods are needed to perform standard tasks. The Shuttle Trajectory and Launch Window Expert System (STALEX) was developed to automate many aspects of early mission planning for space shuttle missions carrying geosynchronous communications satellites. Most of the commercial Shuttle missions planned for the next 3 years will carry at least one of this type of satellite. The applications of STALEX include payload deployment scheduling, launch window analysis, orbital trajectory determination, and landing opportunity selection.

Ahlf, P. R.↗
NASA NTRS1991

Expert system verification and validation study. Delivery 3A and 3B: Trip summaries

Key results are documented from attending the 4th workshop on verification, validation, and testing. The most interesting part of the workshop was when representatives from the U.S., Japan, and Europe presented surveys of VV&T within their respective regions. Another interesting part focused on current efforts to define industry standards for artificial intelligence and how that might affect approaches to VV&T of expert systems. The next part of the workshop focused on VV&T methods of applying mathematical techniques to verification of rule bases and techniques for capturing information relating to the process of developing software. The final part focused on software tools. A summary is also presented of the EPRI conference on 'Methodologies, Tools, and Standards for Cost Effective Reliable Software Verification and Validation. The conference was divided into discussion sessions on the following issues: development process, automated tools, software reliability, methods, standards, and cost/benefit considerations.

French, Scott↗
NASA NTRS1985

Expert systems and their use in augmenting design optimization

The challenging requirements that are evolving for future aircraft demand that each design be optimally integrated, for the penalties imposed by nonoptimal performance are significant. Classic numerical optimization algorithms have been and will continue to be important tools for aircraft designers. These methods are, however, limited to certain categories of aircraft design variables, leaving the remainder to be determined by the user. A method that makes use of knowledge-based expert systems offers the potential for aiding the conceptual design process in a way that is similar to that of numerical optimization, except that it would address discrete, discontinuous, abstract, or any other unoptimized aspect of vehicle design and integration. Other unique capabilities such as automatic discovery and learning in design may also be achievable in the near term. This paper discusses current practice in conceptual aircraft design and knowledge-based systems, and how knowledge-based systems can be used in conceptual design.

Kidwell, G. H.↗
NASA NTRS1988

An expert systems application to space base data processing

The advent of space vehicles with their increased data requirements are reflected in the complexity of future telemetry systems. Space based operations with its immense operating costs will shift the burden of data processing and routine analysis from the space station to the Orbital Transfer Vehicle (OTV). A research and development project is described which addresses the real time onboard data processing tasks associated with a space based vehicle, specifically focusing on an implementation of an expert system.

Babb, Stephen M.↗
NASA NTRS1988

Expert systems for MSFC power systems

Future space vehicles and platforms including Space Station will possess complex power systems. These systems will require a high level of autonomous operation to allow the crew to concentrate on mission activities and to limit the number of ground support personnel to a reasonable number. The Electrical Power Branch at NASA-Marshall is developing advanced automation approaches which will enable the necessary levels of autonomy. These approaches include the utilization of knowledge based or expert systems.

Weeks, David J.↗
NASA NTRS1991

An expert system for planning and scheduling in a telerobotic environment

A knowledge based approach to assigning tasks to multi-agents working cooperatively in jobs that require a telerobot in the loop was developed. The generality of the approach allows for such a concept to be applied in a nonteleoperational domain. The planning architecture known as the task oriented planner (TOP) uses the principle of flow mechanism and the concept of planning by deliberation to preserve and use knowledge about a particular task. The TOP is an open ended architecture developed with a NEXPERT expert system shell and its knowledge organization allows for indirect consultation at various levels of task abstraction. Considering that a telerobot operates in a hostile and nonstructured environment, task scheduling should respond to environmental changes. A general heuristic was developed for scheduling jobs with the TOP system. The technique is not to optimize a given scheduling criterion as in classical job and/or flow shop problems. For a teleoperation job schedule, criteria are situation dependent. A criterion selection is fuzzily embedded in the task-skill matrix computation. However, goal achievement with minimum expected risk to the human operator is emphasized.

Ntuen, Celestine A.↗
NASA NTRS1991

Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

Shewhart, Mark↗
NASA NTRS1990

The network management expert system prototype for Sun Workstations

Networking has become one of the fastest growing areas in the computer industry. The emergence of distributed workstations make networking more popular because they need to have connectivity between themselves as well as with other computer systems to share information and system resources. Making the networks more efficient and expandable by selecting network services and devices that fit to one's need is vital to achieve reliability and fast throughput. Networks are dynamically changing and growing at a rate that outpaces the available human resources. Therefore, there is a need to multiply the expertise rapidly rather than employing more network managers. In addition, setting up and maintaining networks by following the manuals can be tedious and cumbersome even for an experienced network manager. This prototype expert system was developed to experiment on Sun Workstations to assist system and network managers in selecting and configurating network services.

Leigh, Albert↗