Multi-Objective System Optimization of a Mars Atmospheric ISRU Plant

Abstract

The Mars Oxygen In-Situ Resource Utilization Experiment (MOXIE) represents the first time that NASA is demonstrating In-Situ Resource Utilization (ISRU) on the surface of another planetary body. MOXIE produces oxygen from atmospheric CO2 on Mars. It was developed for NASA’s Mars 2020 Rover and produces oxygen with greater than 99.6% purity through solid oxide electrolysis. MOXIE is a small fraction of the scale that would be necessary to produce oxygen for use as a propellant for a human Mars mission, assuming that the empty oxygen tank on a Mars ascent vehicle would be filled from a scaled-up MOXIE system.

MOXIE is a small prototype of an ISRU system that would be capable of supporting a crew of six astronauts on Mars. It is unclear, however, how to optimally scale MOXIE and what specific challenges a scaled-up version might face. This dissertation focuses on taking the lessons learned from MOXIE and determining the optimal way to scale it to a full-size system. Specifically, this dissertation defines a systems architecture for an extensible MOXIE system, called the Big Atmospheric MOXIE (BAM), based on the development of a detailed optimization model. The primary subsystems of interest are the solid oxide electrolysis (SOE) stack, the compressor, the liquefaction system, and the heat exchanger. The model has been validated with data from scaled-up SOE cell testing, past MOXIE experiments, and components used in industry.

By understanding the scalability and extensibility of key subsystems in the MOXIE system, it is possible to design a larger, optimized systems architecture model for BAM to support the first human missions to Mars. Producing this optimized, validated systems design of a scaled-up atmospheric ISRU plant for Mars has never been done before under these parameters and is the primary goal of this dissertation.