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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Analytical study of nozzle performance for nuclear thermal rockets

A parametric study has been conducted by the NASA-Lewis Rocket Engine Design Expert System for the convergent-divergent nozzle of the Nuclear Thermal Rocket system, which uses a nuclear reactor to heat hydrogen to high temperature and then expands it through the nozzle. It is established by the study that finite-rate chemical reactions lower performance levels from theoretical levels. Major parametric roles are played by chamber temperature and chamber pressure. A maximum performance of 930 sec is projected at 2700 K, and of 1030 at 3100 K.

Davidian, Kenneth O.↗
NASA NTRS1992

Software For Monitoring A Computer Network

SNMAT is rule-based expert-system computer program designed to assist personnel in monitoring status of computer network and identifying defective computers, workstations, and other components of network. Also assists in training network operators. Network for SNMAT located at Space Flight Operations Center (SFOC) at NASA's Jet Propulsion Laboratory. Intended to serve as data-reduction system providing windows, menus, and graphs, enabling users to focus on relevant information. SNMAT expected to be adaptable to other computer networks; for example in management of repair, maintenance, and security, or in administration of planning systems, billing systems, or archives.

Lee, Young H.↗
NASA NTRS1991

Analytical study of nozzle performance for nuclear thermal rockets

Nuclear propulsion has been identified as one of the key technologies needed for human exploration of the Moon and Mars. The Nuclear Thermal Rocket (NTR) uses a nuclear reactor to heat hydrogen to a high temperature followed by expansion through a conventional convergent-divergent nozzle. A parametric study of NTR nozzles was performed using the Rocket Engine Design Expert System (REDES) at the NASA Lewis Research Center. The REDES used the JANNAF standard rigorous methodology to determine nozzle performance over a range of chamber temperatures, chamber pressures, thrust levels, and different nozzle configurations. A design condition was set by fixing the propulsion system exit radius at five meters and throat radius was varied to achieve a target thrust level. An adiabatic wall was assumed for the nozzle, and its length was assumed to be 80 percent of a 15 degree cone. The results conclude that although the performance of the NTR, based on infinite reaction rates, looks promising at low chamber pressures, finite rate chemical reactions will cause the actual performance to be considerably lower. Parameters which have a major influence on the delivered specific impulse value include the chamber temperature and the chamber pressures in the high thrust domain. Other parameters, such as 2-D and boundary layer effects, kinetic rates, and number of nozzles, affect the deliverable performance of an NTR nozzle to a lesser degree. For a single nozzle, maximum performance of 930 seconds and 1030 seconds occur at chamber temperatures of 2700 and 3100 K, respectively.

Davidian, Kenneth O.↗
NASA NTRS1988

ART/Ada design project, phase 1. Task 2 report: Detailed design

Various issues are studied in the context of the design of an Ada based expert system building tool. Using an existing successful design as a starting point, the impact is analyzed of the Ada language and Ada development methodologies on that design, the Ada system is redesigned, and its performance is analyzed using both complexity-theoretic and empirical techniques. The algorithms specified in the overall design are refined, resolving and documenting any open design issues, identifying each system module, documenting the internal architecture and control logic, and describing the primary data structures involved in the module.

Allen, Bradley P.↗
NASA NTRS1991

Advanced technologies for Mission Control Centers

Advance technologies for Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: technology needs; current technology efforts at GSFC (human-machine interface development, object oriented software development, expert systems, knowledge-based software engineering environments, and high performance VLSI telemetry systems); and test beds.

Dalton, John T.↗
NASA NTRS1991

Spectroscopy and multivariate analyses applications related to solid rocket nozzle bondline

Chemical composition and molecular orientation define the properties of materials. Information related to chemical composition and molecular configuration is obtained by various forms of spectroscopy. Software algorithms developed for multivariate analyses, expert systems, and Artificial Intelligence (AI) are used to conduct repetitive operations. The techniques are believed to be of particular significance toward achieving TQM objectives. The objective was to obtain information related to the quality of the bondline in the solid rocket motor, SRM, nozzle. Hysol 934 NA, a room temperature curing epoxide resin, is used as the bonding agent. A good bond requires that the adhesive be placed on a properly prepared metal surface, the adhesives Part A and B be mixed in appropriate ratio from material within shelf life specifications. Spectroscopic data was obtained for surfaces prepared according to specifications, contaminated metal surfaces, samples of the epoxide adhesive at times that represent shelf aging from 3 months to 2 years, several mix ratio of A to B, and curing material. Temperature was found to be a significant factor. The study concentrated on pot life and mix ratio.

Arendale, W. F.↗
NASA NTRS1991

Composite load spectra for select space propulsion structural components

This report summarizes the development for: (1) correlation fields; (2) applications to liquid oxygen post; (3) models for pressure fluctuatios and vibration loads fluctuations; (4) additions to expert systems; and (5) scaling criteria. Implementation to computer code is also described. Demonstration sample cases are included with additional applications to engine duct and pipe bend.

Newell, James F.↗
NASA NTRS1991

The Management and Security Expert (MASE)

The Management and Security Expert (MASE) is a distributed expert system that monitors the operating systems and applications of a network. It is capable of gleaning the information provided by the different operating systems in order to optimize hardware and software performance; recognize potential hardware and/or software failure, and either repair the problem before it becomes an emergency, or notify the systems manager of the problem; and monitor applications and known security holes for indications of an intruder or virus. MASE can eradicate much of the guess work of system management.

Miller, Mark D.↗
NASA NTRS1991

CLIPS application user interface for the PC

The majority of applications that utilize expert system development programs for their knowledge representation and inferencing capability require some form of interface with the end user. This interface is more than likely an interaction through the computer screen. When building an application the user interface can prove to be the most difficult and time consuming aspect to program. Commercial products currently exist which address this issue. To keep pace C Language Integrated Production System (CLIPS) will need to find a solution for their lack of an easy to use Application User Interface (AUI). This paper represents a survey of the DoD CLIPS' user community and provides the backbone of a possible solution.

Jenkins, Jim↗
NASA NTRS1991

Facing page test for the astronaut science advisor presentation

The goal of the Astronaut Science Advisor (ASA) project is to improve the scientific return of experiments performed in space by providing astronaut experimenters with an 'intelligent assistant' that encapsulates much of the domain- and experiment-related knowledge commanded by the Principal Investigator (PI) on the ground. By using expert systems technology and the availability of flight-qualified personal computers, it is possible to encode the requisite knowledge and make it available to astronauts as they perform experiments in space. The system performs four major functions: diagnosis and troubleshooting of experiment apparatus, data collection, protocol management, and detection of interesting data. The experiment used for development of the system measures human adaptation to weightlessness in the context of the neurovestibular system. This so-called 'Rotating Dome' experiment was flown on the recent Spacelab Life Sciences One (SLS-1) Mission. This mission was used as an opportunity to test some of the system's functionality. Experiment data was downlinked from the orbiter, and the system then captured the data and analyzed it in real time. The system kept track of the time being used by the experiment, recognized occurrences of interesting data, summarized data statistically and generated potential new protocols that could be used to optimize the course of the experiment.

Compton, Michael M.↗
NASA NTRS1991

The astronaut science advisor: Ground testing during SLS-1

The objective of the Astronaut Science Advisor (ASA) is the improvement of the scientific return of experiments performed in space. This is accomplished through the use of expert systems technology to encode the domain and experiment knowledge commanded by the principal investigator (PI) and make it available to the astronaut experimenters. The principal functions of the ASA include the following: capture, reduce, and archive experimental data; monitor data quality and help diagnose problems with equipment when experimental data is erratic or poor; identify and permit investigation of interesting data; and suggest protocol changes that would result in better utilization of remaining time.

Compton, Michael M.↗
NASA NTRS1992

Guidelines and rules for automated assembly by robots in space

The development of an expert system for a 'Mechanical Design System' is discussed. Two different implementation approaches are described. One is coded in C, and the other is realized by a software package - 'Exsys.' The first method has the advantage of greater flexibility and quicker responses, while the latter one is easier to develop. This report discusses the feasible ways to establish a real mechanical intelligent design system applying artificial intelligence techniques so that the products designed by this system could best meet the requirements for space assembly.

Srivastava, Sadanand↗
NASA NTRS1992

Ramp Technology and Intelligent Processing in Small Manufacturing

To address the issues of excessive inventories and increasing procurement lead times, the Navy is actively pursuing flexible computer integrated manufacturing (FCIM) technologies, integrated by communication networks to respond rapidly to its requirements for parts. The Rapid Acquisition of Manufactured Parts (RAMP) program, initiated in 1986, is an integral part of this effort. The RAMP program's goal is to reduce the current average production lead times experienced by the Navy's inventory control points by a factor of 90 percent. The manufacturing engineering component of the RAMP architecture utilizes an intelligent processing technology built around a knowledge-based shell provided by ICAD, Inc. Rules and data bases in the software simulate an expert manufacturing planner's knowledge of shop processes and equipment. This expert system can use Product Data Exchange using STEP (PDES) data to determine what features the required part has, what material is required to manufacture it, what machines and tools are needed, and how the part should be held (fixtured) for machining, among other factors. The program's rule base then indicates, for example, how to make each feature, in what order to make it, and to which machines on the shop floor the part should be routed for processing. This information becomes part of the shop work order. The process planning function under RAMP greatly reduces the time and effort required to complete a process plan. Since the PDES file that drives the intelligent processing is 100 percent complete and accurate to start with, the potential for costly errors is greatly diminished.

Rentz, Richard E.↗
NASA NTRS1992

A brief overview of computational structures technology related activities at NASA Lewis Research Center

The presentation gives a partial overview of research and development underway in the Structures Division of LeRC, which collectively is referred to as the Computational Structures Technology Program. The activities in the program are diverse and encompass four major categories: (1) composite materials and structures; (2) probabilistic analysis and reliability; (3) design optimization and expert systems; and (4) computational methods and simulation. The approach of the program is comprehensive and entails exploration of fundamental theories of structural mechanics to accurately represent the complex physics governing engine structural performance, formulation, and implementation of computational techniques and integrated simulation strategies to provide accurate and efficient solutions of the governing theoretical models by exploiting the emerging advances in computer technology, and validation and verification through numerical and experimental tests to establish confidence and define the qualities and limitations of the resulting theoretical models and computational solutions. The program comprises both in-house and sponsored research activities. The remainder of the presentation provides a sample of activities to illustrate the breadth and depth of the program and to demonstrate the accomplishments and benefits that have resulted.

Hopkins, Dale A.↗
NASA NTRS1991

Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

Hockaday, Stephen↗
NASA NTRS1991

A survey of decision tree classifier methodology

Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

Safavian, S. R.↗
NASA NTRS1992

Fuzzy logic and neural network technologies

Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

Villarreal, James A.↗