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NASA NTRS1988

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies.

Rash, James↗

NASA NTRS1988

Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Truszkowski, Walter F.↗

NASA NTRS1988

Artificial intelligence in a mission operations and satellite test environment

A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

Busse, Carl↗

NASA NTRS1987

Artificial gravity - The evolution of variable gravity research

The development of a space life science research program based on the use of rotational facilities is described. In-flight and ground centrifuges can be used as artificial gravity environments to study the following: nongravitational biological factors; the effects of 0, 1, and hyper G on man; counter measures for deconditioning astronauts in weightlessness; and the development of suitable artificial gravity for long-term residence in space. The use of inertial fields as a substitute for gravity, and the relations between the radius of the centrifuge and rotation rate and specimen height and rotation radius are examined. An example of a centrifuge study involving squirrel monkeys is presented.

Fuller, Charles A.↗

NASA NTRS1989

Application Of Artificial Intelligence To Wind Tunnels

Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

Lo, Ching F.↗

NASA NTRS1988

Artificial intelligence approaches to software engineering

Artificial intelligence approaches to software engineering are examined. The software development life cycle is a sequence of not so well-defined phases. Improved techniques for developing systems have been formulated over the past 15 years, but pressure continues to attempt to reduce current costs. Software development technology seems to be standing still. The primary objective of the knowledge-based approach to software development presented in this paper is to avoid problem areas that lead to schedule slippages, cost overruns, or software products that fall short of their desired goals. Identifying and resolving software problems early, often in the phase in which they first occur, has been shown to contribute significantly to reducing risks in software development. Software development is not a mechanical process but a basic human activity. It requires clear thinking, work, and rework to be successful. The artificial intelligence approaches to software engineering presented support the software development life cycle through the use of software development techniques and methodologies in terms of changing current practices and methods. These should be replaced by better techniques that that improve the process of of software development and the quality of the resulting products. The software development process can be structured into well-defined steps, of which the interfaces are standardized, supported and checked by automated procedures that provide error detection, production of the documentation and ultimately support the actual design of complex programs.

Johannes, James D.↗

NASA NTRS1989

Feasibility of generating an artificial burst in a turbulent boundary layer, phase 2

Various drag accounts for about half of the total drag on commercial aircraft at subsonic cruise conditions. Two avenues are available to achieve drag reduction: either laminar flow control or turbulence manipulation. The present research deals with the latter approach. The primary objective of Phase 2 research was to investigate experimentally the feasibility of substantially reducing the skin-friction drag in a turbulent boundary layer. The method combines the beneficial effects of suction and a longitudinally ribbed surface. At a sufficiently large spanwise separation, the streamwise grooves act as a nucleation site causing a focusing of low-speed streaks over the peaks. Suction is then applied intermittently through longitudinal slots located at selected locations along those peaks to obliterate the low-speed regions and to prevent bursting. Phase 2 research was divided into two tasks. In the first, selective suction from a single streamwise slot was used to eliminate either a single burst-like event or a periodic train of artificially generated bursts in laminar and turbulent boundary layers that develop on a flat plate towed in a water channel. The results indicate that equivalent values of the suction coefficient as low as 0.0006 were sufficient to eliminate the artificially generated bursts in a laminar boundary layer.

Gad-El-hak, Mohamed↗

NASA NTRS1987

The spinning artificial gravity environment: A design project

The SAGE, or Spinning Artificial Gravity Environment, design was carried out to develop an artificial gravity space station which could be used as a platform for the performance of medical research to determine the benefits of various, fractional gravity levels for astronauts normally subject to zero gravity. Desirable both for its medical research mission and a mission for the study of closed loop life-support and other factors in prolonged space flight, SAGE was designed as a low Earth orbiting, solar powered, manned space station.

Pignataro, Robert↗

NASA NTRS1988

Intrinsic and artificial bias in the KONUS cumulative number distribution

The known biases affecting the KONUS gamma burst cumulative number distribution are discussed and categorized as intrinsic (unavoidable) and artificial (avoidable). Artificial biases are removed to obtain a revised, more faithful representation of the true KONUS log N-log Pc, where Pc is in counts (1/0.25 s). A low Pc turnover is still apparent in the revised log N-log Pc. Conflicting claims that the KONUS log N-log Pc is compatible with a nearby disk or an isotropic, homogeneous distribution are tested using the revised log N-log Pc and a rigorous treatment of the KONUS intrinsic gamma background bias. The claims are shown to be improbable. Other possibilities and problms concerning log N-log Pc are discussed, but the need for a complete explanation of the low Pc turnover remains.

Jennings, Mark C.↗

NASA NTRS1987

Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

Gilmore, John F.↗

NASA NTRS1988

1988 Goddard Conference on Space Applications of Artificial Intelligence, Greenbelt, MD, May 24, 1988, Proceedings

Rash, James L.↗

NASA NTRS1988

Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Truszkowski, Walter F.↗

NASA NTRS1988

Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

Leong, Harrison Monfook↗

NASA NTRS1989

An artificial gravity demonstration experiment

An artificial gravity experiment which is tethered to a Delta second stage and which uses the Small Expendable Deployer System is proposed. Following tether deployment, the Delta vehicle performs the required spin-up maneuver and can then be passivated. A surplus reentry vehicle houses the artificial gravity life science experiments. When the experiments are completed, the reentry phase of the experiment is initiated by synchronizing the spin of the configuration with the required deorbit impulse.

Rupp, C.↗

NASA NTRS1988

The use of tethers for an artificial gravity facility

The principles of operation and the design of the Artificial Gravity Research Facility (AGRF), which is a centrifuge to be constructed and operated for research and development purposes in a low-earth orbit, are examined, with particular attention given to the use of tethers for this facility. The differences and similarities between the AGRF and the previous artificial-gravity concepts are discussed in the framework of modern understanding of the effects of partial gravity and rotating environments on the human organism. The impact of tension-stiffened tethers on the system mass of the AGRF is examined, together with their effect on space operations and safety.

Lemke, L. G.↗

NASA NTRS1988

Artificial intelligence approaches to astronomical observation scheduling

Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

Johnston, Mark D.↗

NASA NTRS1989

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗

NASA NTRS1990

The 1990 Goddard Conference on Space Applications of Artificial Intelligence

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Rash, James L.↗