Matthew Rines
(Advisor: Prof. Dimitri Mavris]

will propose a doctoral thesis entitled,

A Methodology For Resilience-Based Design Of An Environmental Control And Life Support System

On

Friday, July 30 at 2:00 p.m.
https://bluejeans.com/869750335/1981

Abstract

A space habitat provides life support to the crew during both normal operation and unexpected circumstances so that they are able to carry out the scientific duties of their mission. As space habitats become more complex and are located farther from Earth, there are increased challenges to ensuring resilience in system performance and crew safety. As a result of these challenges, it is beneficial for resource allocation decision making to be autonomous.

An autonomous resource allocation algorithm will reduce the workload of the crew and reliance on terrestrial decision-making. The hostility of space drives the need for rapid decision-making without requiring humans to be in the loop. Furthermore, the inability to plan for all possible situations necessitates a resource allocation strategy that can adapt and learn from experience. The methods used to autonomously learn about changes in the environment also need to be careful not to compromise the safety of the crew.

To meet these goals, a methodology is devised for developing resilient resource allocation strategies for an environmental control and life support system (ECLSS) and integrating it into the design of space habitats. Reinforcement learning techniques will be employed to allow rapid ECLSS resource allocations both for nominal and off-nominal situations. The methodology will include the ability to learn from data collected in operation as well as in a priori training simulations in order to better respond to disturbances that it had not previously experienced in simulations and other non-stationary dynamics.

This research will seek to demonstrate that a resource allocation algorithm could be developed to improve the resilience of an existing space habitat or a space habitat that is yet to be designed. The methodology will show how the resource allocation algorithm can be brought forward in the design process to the habitat’s architectural design. By investigating how different habitat configurations can affect the ECLSS’s ability to successfully allocate resources in off-nominal scenarios, a better design can be found earlier and more cost effectively.

Committee

• Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
• Prof. Glenn Lightsey – School of Aerospace Engineering
• Prof. Koki Ho – School of Aerospace Engineering
• Dr. Rodney Martin – Ames Research Center
• Dr. Michael Balchanos – School of Aerospace Engineering