Research on knowledge representation, machine learning, and knowledge acquisition

Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments

Study of wrap-rib antenna design

The results of a parametric design study conducted to develop the significant characteristics and technology limitations of space deployable antenna systems with aperture sizes ranging from 50 up to 300 m and F/D ratios between 0.5 and 3.0 are presented. Wrap/rib type reflectors of both the prime and offset fed geometry and associated feed support structures were considered. The significant constraints investigated as limitations on achievable aperture were inherent manufacturability, orbit dynamic and thermal stability, antenna weight, and antenna stowed volume. A data base, resulting in the defined maximum achievable aperture size as a function of diameter, frequency and estimated cost, was formed

RSM 1.0 user's guide: A resupply scheduler using integer optimization

The Resupply Scheduling Model (RSM) is a PC based, fully menu-driven computer program. It uses integer programming techniques to determine an optimum schedule to replace components on or before a fixed replacement period, subject to user defined constraints such as transportation mass and volume limits or available repair crew time. Principal input for RSJ includes properties such as mass and volume and an assembly sequence. Resource constraints are entered for each period corresponding to the component properties. Though written to analyze the electrical power system on the Space Station Freedom, RSM is quite general and can be used to model the resupply of almost any system subject to user defined resource constraints. Presented here is a step by step procedure for preparing the input, performing the analysis, and interpreting the results. Instructions for installing the program and information on the algorithms are given

AAFE large deployable antenna development program: Executive summary

The large deployable antenna development program sponsored by the Advanced Applications Flight Experiments of the Langley Research Center is summarized. Projected user requirements for large diameter deployable reflector antennas were reviewed. Trade-off studies for the selection of a design concept for 10-meter diameter reflectors were made. A hoop/column concept was selected as the baseline concept. Parametric data are presented for 15-meter, 30-meter, and 100-meter diameters. A 1.82-meter diameter engineering model which demonstrated the feasiblity of the concept is described