# Projects in 1987–1988

## Aerojet Electrosystems: Outgassing and Contamination in Vacuum Systems

Fiki Shillor Meir

Outgassing is a process by which molecules migrate out of a material body into its surroundings. This process can become the source of contamination, particularly in the near perfect vacuum conditions encountered in space application. The proposed project developed a predictive mathematical model of outgassing based on physical principles.

## General Dynamics: Multipath Modeling

Janet Myhre
College
CGU

When the target object is close to the sea surface, radar signals reflect from that surface as well as from the object, and a signal may have traversed a number of paths on return to the emitter. This gives a number of ghost images. The latter might be reduced by choice of a frequency at which the sea surface is most absorbing. The goal of the Clinic was to identify that frequency. First a statistical model for the sea surface was constructed and its reflecting and absorbing properties analyzed. Then the radar power loss could be computed along the various paths and estimates made of the images.

## General Dynamics: Modeling and Simulation of Neural Network Image Classifiers

Stavros Busenberg

This project investigated the feasibility of using neural networks to recognize two-dimensional objects with up to twenty degrees of rotational invariance. The investigation took two paths. The first was a continued mathematical analysis of general neural networks with the aim of determining the theoretical limits of rotationally invariant object recognition. The second was the refinement and systematic use of the ATHENA software to simulate a variety of neural networks which the theoretical work suggests as candidates for successful rotationally-invariant image classification. These two approaches complement each other and were pursued in parallel, with constant interaction between them.

## Jet Propulsion Laboratory: Optimal Data Collection for MOSFET Modeling

College
CGU

Problem 1. Physical and geometrical parameters used in modeling the flow of current were not known and were hard to measure. They were inferred (“parameter extraction”) from current measurements. The clinic addressed how the latter can be reduced, retaining good accuracy on the extracted values.

Problem 2. Formulae were based on infinite length, infinite width models. Terms to correct for finite values could be added with coefficients identified by regression from measurements. The clinic addressed what values of length and width are measurements to be taken for optimal results.