The goal of this MQP is to create a dynamic model of a mirror deployment system for a space based telescope that utilizes hexagonal mirror segments. The central problem to this method is calculating the reaction torques that will be necessary to maintain the satellite's position in space as the mirrors deploy. Using Kane's method of dynamic analysis, along with the Auto-Lev software package, we intend to dynamically model two methods of deployment in order to determine their feasibility for future use. Although based on complex technologies, the CADR process will decrease the cost of missions by creating a lighter weight system to replace the old mechanical cooling methods and will significantly extend the lifetime of detectors and cryogenic coolers. Autonomous operation can be accomplished through the use of artificial intelligence software called an agent.
Agents are complex, with many components comprising a single agent.
This project will focus on the modeler component of an agent that is being developed by a team of engineers at NASA's Goddard Space Flight Center. Our goal to set up a framework of the agent's model of itself. To do this, we will analyze the possible uses for the agent's model of itself, formulate potential queries that may be asked of the modeler pertaining to the agent, and decide how best to model the data needed to answer those queries. This mission uses a network of small satellites with new microwave interferometers to gather data. Our contribution to this mission is to design, implement and test portions of the data acquisition and analysis systems for the interferometer's test platform.