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The proceedings of the conference are presented. This second conference on Artificial Intelligence for Space Applications brings together a diversity of scientific and engineering work and is intended to provide an opportunity for those who employ AI methods in space applications to identify common goals and to discuss issues of general interest in the AI community.
Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.
Analytical and experimental techniques for modeling the aerothermodynamics of hypersonic flight are assessed, together with the problems which will be encountered in developing reusable hypersonic vehicles. Emphasis is placed on a numerical coupling between a nonequilibrium chemistry model and hypersonic flow kinematics. Finite difference and finite element descriptions of flow fields in which molecules encounter a shock wave and undergo various motion (and thereby energy) transformations are discussed. The effects of artificial smearing of the shock wave are considered in terms of the resulting effects on the distribution of the energies and chemical composition of the transition region. Results are provided from schlieren photographs of shock-tube experiments, Navier-Stokes calculations of axisymmetric flow over a conical body, and calculations using a spectral multidomain approach for chemically reacting flows.
The development of a methodology for the production of highly reliable software is one of the greatest challenges facing the computer industry. Meeting this challenge will undoubtably involve the integration of many technologies. This paper describes the use of Artificial Intelligence technologies in the automated analysis of the formal algebraic specifications of abstract data types. These technologies include symbolic execution of specifications using techniques of automated deduction and machine learning through the use of examples. On-going research into the role of knowledge representation and problem solving in the process of developing software is also discussed.
Current knowledge on artificial gravity is presented with emphasis placed on the unique characteristics of such an environment and their effects on crew performance and vehicle habitability. A parametric optimization of the vehicle size and operation is performed. The following set of 'optimum' parameter values is obtained: a cost of 15.8 billion dollars, a radius of 80 feet, a rotation rate of 4.8 rpm, and a g-value of 0.62. Consideration is also given to the problems of adaptation, retention of adaptation, and simultaneous adaptation to both nonrotating and rotating environments.
Investigations involving artificial excitation of various shear flows are reviewed. Potential applications of excitation in flow control, e.g., in enhancing mixing, and in delaying transition and separation are discussed. An account is given of the current activities at NASA Lewis Research Center in this regard.
Four artificial dissipation models which augment central difference schemes were examined for hypersonic external flows. The models were a first and third order dissipation model, a directionally scaled first and third order dissipation model, a flux limited dissipation model, and a flux difference split dissipation model. Each model was implemented in the lower-upper symmetric-Gauss-Seidel (LU-SGS) algorithm to solve the full Navier-Stokes equations. The latter two models can be regarded as total variation diminishing (TVD) schemes. Test results for model problems showed that the flux limited dissipation model was robust enough to predict a high speed blunt body flow with strong shock and expansion waves. The flux difference split dissipation model was capable of shock capturing with higher resolution, but was less robust. First and third order dissipation models turned out to be neither accurate nor robust enough for high Mach number flow computations.
The two Ba releases in the solar wind, termed artificial comets (the first in interplanetary space, the second in the terrestrial magnetosheath), showed a number of common magnetic features. Both times a magnetic cavity was detected and a field pile-up observed with magnitudes several times the ambient field strength upstream of the cavity. The magnetic fluctuations in the compressed region are generally enhanced by a factor comparable to the amount of field pile-up. There is a peak in the spectra of both events around 0.1 Hz in the component which is perpendicular to the solar-wind velocity vector and almost field-aligned. This magnetosonic wave has been interpreted as the fundamental mode of resonance oscillations of the compression zone. For frequencies beyond 2 Hz the spectra decrease more steeply in the case of the second 'comet' than in the first. This is due to the interaction of the supersonic solar wind with the first comet. The spectra obtained during the first comet at the solar-wind/ion-cloud interface are identical to those observed during bow-shock crossings.
This paper describes the automation of one class of aeronautical design activity using artificial intelligence and advanced software techniques. Its purpose is to suggest concepts, terminology, and approaches that may be useful in enhancing design automation. By understanding the basic concepts and tasks in design, and the technologies that are available, it will be possible to produce, in the future, systems whose capabilities far exceed those of today's methods. Some of the tasks that will be discussed have already been automated and are in production use, resulting in significant productivity benefits. The concepts and techniques discussed are applicable to all design activity, though aeronautical applications are specifically presented.
Artificial Satellite Analysis Program (ASAP) is general orbit-predicting computer program incorporating sufficient orbit-modeling accuracy for design and planning of missions and analysis of maneuvers. Suitable for study of planetary-orbit missions with spacecraft trajectories of reconnaissance (flyby) and exploratory (mapping) nature. Not written for specific mission and intended use for almost any planetary orbiting mission. Written in FORTRAN 77.
A simple and effective method of artificial compression is introduced. This method is based on a modification of the slopes of the ENO (essentially nonoscillatory) reconstruction and, with the help of suitable chosen parameters, greatly improves the resolution of the contact discontinuities. Numerical examples are provided to test the performance of the method and to give some suggestions as to the choice of the parameters.
Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.
Now that Artificial Intelligence (AI) is gaining acceptance, it is important to examine some of the obstacles that still stand in the way of its progress. Ironically, many of these obstacles are related to management and are aggravated by the very characteristcs that make AI useful. The purpose of this paper is to heighten awareness of management issues in AI development and to focus attention on their resolution.
A prototype simulation is being developed under contract to the Royal Aerospace Establishment (RAE), Farnborough, England, to assist in the discrimination of artificial space objects/debris. The methodology undertaken has been to link Object Oriented programming, intelligent knowledge based system (IKBS) techniques and advanced computer technology with numeric analysis to provide a graphical, symbolic simulation. The objective is to provide an additional layer of understanding on top of conventional classification methods. Use is being made of object and rule based knowledge representation, multiple reasoning, truth maintenance and uncertainty. Software tools being used include Knowledge Engineering Environment (KEE) and SymTactics for knowledge representation. Hooks are being developed within the SymTactics framework to incorporate mathematical models describing orbital motion and fragmentation. Penetration and structural analysis can also be incorporated. SymTactics is an Object Oriented discrete event simulation tool built as a domain specific extension to the KEE environment. The tool provides facilities for building, debugging and monitoring dynamic (military) simulations.
The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI.
This final report describes the accomplishments of the General Purpose Intelligent Sensor Interface task of the Applications of Artificial Intelligence to Space Station grant for the period from October 1, 1987 through September 30, 1988. Portions of the First Biannual Report not revised will not be included but only referenced. The goal is to develop an intelligent sensor system that will simplify the design and development of expert systems using sensors of the physical phenomena as a source of data. This research will concentrate on the integration of image processing sensors and voice processing sensors with a computer designed for expert system development. The result of this research will be the design and documentation of a system in which the user will not need to be an expert in such areas as image processing algorithms, local area networks, image processor hardware selection or interfacing, television camera selection, voice recognition hardware selection, or analog signal processing. The user will be able to access data from video or voice sensors through standard LISP statements without any need to know about the sensor hardware or software.
In a software system the size of the Space Station Software Support Environment (SSE), no one software development or implementation methodology is presently powerful enough to provide safe, reliable, maintainable, cost effective real time or near real time software. In an environment that must survive one of the most harsh and long life times, software must be produced that will perform as predicted, from the first time it is executed to the last. Many of the software challenges that will be faced will require strategies borrowed from Artificial Intelligence (AI). AI is the only development area mentioned as an example of a legitimate reason for a waiver from the overall requirement to use the Ada programming language for software development. The limits are defined of the applicability of the Ada language Ada Programming Support Environment (of which the SSE is a special case), and software engineering to AI solutions by describing a scenario that involves many facets of AI methodologies.
The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.