PAN AIR summary document (version 1.0)

The capabilities and limitations of the panel aerodynamics (PAN AIR) computer program system are summarized. This program uses a higher order panel method to solve boundary value problems involving the Prandtl-Glauert equation for subsonic and supersonic potential flows. Both aerodynamic and hydrodynamic problems can be solved using this modular software which is written for the CDC 6600 and 7600, and the CYBER 170 series computers

Automated system for integration and display of physiological response data

The system analysis approach was applied in a study of physiological systems in both 1-g and weightlessness, for short and long term experiments. A whole body, algorithm developed as the first step in the construction of a total body simulation system is described and an advanced biomedical computer system concept including interactive display/command consoles is discussed. The documentation of the design specifications, design and development studies, and user's instructions (which include program listings) for these delivered end-terms; the reports on the results of many research and feasibility studies; and many subcontract reports are cited in the bibliography

NASA scientific and technical publications: A catalog of special publications, reference publications, conference publications, and technical papers, 1989

This catalog lists 190 citations of all NASA Special Publications, NASA Reference Publications, NASA Conference Publications, and NASA Technical Papers that were entered into the NASA scientific and technical information database during accession year 1989. The entries are grouped by subject category. Indexes of subject terms, personal authors, and NASA report numbers are provided

Multidisciplinary Expert-aided Analysis and Design (MEAD)

The MEAD Computer Program (MCP) is being developed under the Multidisciplinary Expert-Aided Analysis and Design (MEAD) Project as a CAD environment in which integrated flight, propulsion, and structural control systems can be designed and analyzed. The MCP has several embedded computer-aided control engineering (CACE) packages, a user interface (UI), a supervisor, a data-base manager (DBM), and an expert system (ES). The supervisor monitors and coordinates the operation of the CACE packages, the DBM; the ES, and the UI. The DBM tracks the control design process. Models created or installed by the MCP are tracked by date and version, and results are associated with the specific model version with which they were generated. The ES is used to relieve the control engineer from tedious and cumbersome tasks in the iterative design process. The UI provides the capability for a novice as well as an expert to utilize the MCP easily and effectively. The MCP version 2(MCP-2.0) is fully developed for flight control system design and analysis. Propulsion system modeling, analysis, and simulation is also supported; the same is true for structural models represented in state-space form. The ultimate goal is to cover the integration of flight, propulsion, and structural control engineering, including all discipline-specific functionality and interfaces. The current MCP-2.0 components and functionality are discussed

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 197, September 1979

This bibliography lists 193 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1979

Control design and simulation of systems modeled using ADAMS

A technique for control design and simulation using the ADAMS software and a control design software package is presented. For design of control systems ADAMS generates a minimum realization linear time invariant (LTI), state space representation of multi-body models. This LTI representation can be produced in formats for input to several commercial control design packages. The user can exercise various design strategies in the control design software to arrive at a suitable compensator. The resulting closed loop model can then be simulated using ADAMS. This procedure is illustrated with two examples

A study of mapping exogenous knowledge representations into CONFIG

Qualitative reasoning is reasoning with a small set of qualitative values that is an abstraction of a larger and perhaps infinite set of quantitative values. The use of qualitative and quantitative reasoning together holds great promise for performance improvement in applications that suffer from large and/or imprecise knowledge domains. Included among these applications are the modeling, simulation, analysis, and fault diagnosis of physical systems. Several research groups continue to discover and experiment with new qualitative representations and reasoning techniques. However, due to the diversity of these techniques, it is difficult for the programs produced to exchange system models easily. The availability of mappings to transform knowledge from the form used by one of these programs to that used by another would open the doors for comparative analysis of these programs in areas such as completeness, correctness, and performance. A group at the Johnson Space Center (JSC) is working to develop CONFIG, a prototype qualitative modeling, simulation, and analysis tool for fault diagnosis applications in the U.S. space program. The availability of knowledge mappings from the programs produced by other research groups to CONFIG may provide savings in CONFIG's development costs and time, and may improve CONFIG's performance. The study of such mappings is the purpose of the research described in this paper. Two other research groups that have worked with the JSC group in the past are the Northwest University Group and the University of Texas at Austin Group. The former has produced a qualitative reasoning tool named SIMGEN, and the latter has produced one named QSIM. Another program produced by the Austin group is CC, a preprocessor that permits users to develop input for eventual use by QSIM, but in a more natural format. CONFIG and CC are both based on a component-connection ontology, so a mapping from CC's knowledge representation to CONFIG's knowledge representation was chosen as the focus of this study. A mapping from CC to CONFIG was developed. Due to differences between the two programs, however, the mapping transforms some of the CC knowledge to CONFIG as documentation rather than as knowledge in a form useful to computation. The study suggests that it may be worthwhile to pursue the mappings further. By implementing the mapping as a program, actual comparisons of computational efficiency and quality of results can be made between the QSIM and CONFIG programs. A secondary study may reveal that the results of the two programs augment one another, contradict one another, or differ only slightly. If the latter, the qualitative reasoning techniques may be compared in other areas, such as computational efficiency

MITT writer and MITT writer advanced development: Developing authoring and training systems for complex technical domains

MITT Writer is a software system for developing computer based training for complex technical domains. A training system produced by MITT Writer allows a student to learn and practice troubleshooting and diagnostic skills. The MITT (Microcomputer Intelligence for Technical Training) architecture is a reasonable approach to simulation based diagnostic training. MITT delivers training on available computing equipment, delivers challenging training and simulation scenarios, and has economical development and maintenance costs. A 15 month effort was undertaken in which the MITT Writer system was developed. A workshop was also conducted to train instructors in how to use MITT Writer. Earlier versions were used to develop an Intelligent Tutoring System for troubleshooting the Minuteman Missile Message Processing System

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Automatic programming of simulation models

The concepts of software engineering were used to improve the simulation modeling environment. Emphasis was placed on the application of an element of rapid prototyping, or automatic programming, to assist the modeler define the problem specification. Then, once the problem specification has been defined, an automatic code generator is used to write the simulation code. The following two domains were selected for evaluating the concepts of software engineering for discrete event simulation: manufacturing domain and a spacecraft countdown network sequence. The specific tasks were to: (1) define the software requirements for a graphical user interface to the Automatic Manufacturing Programming System (AMPS) system; (2) develop a graphical user interface for AMPS; and (3) compare the AMPS graphical interface with the AMPS interactive user interface