A Discrete-Event Simulation Of The Nasa Fuel Production Plant On Mars

Abstract

The National Aeronautics and Space Administration (NASA) is preparing for a manned mission to Mars to test the sustainment of civilization on the planet Mars. This research explores the requirements and feasibility of autonomously producing fuel on Mars for a return trip back to Earth. As a part of NASA's initiative for a manned trip to Mars, our team's work creates and analyzes the allocation of resources necessary in deploying a fuel station on this foreign soil. Previous research has addressed concerns with a number individual components of this mission such as power required for fuel station and tools; however, the interactions between these components and the effects they would have on the overall requirements for the fuel station are still unknown to NASA. By creating a baseline discrete-event simulation model in a simulation software environment, the research team has been able to simulate the fuel production process on Mars. This research will mainly utilize the fuel component processing times, travel requirements, and In Situation Resource Utilization concepts to reach the end goal of producing enough fuel to safely get the astronauts home. This simulation displays the inner-working of each subcomponent and the effects that they have on the behavior of the overall system. The validation and verification of the fuel station simulation model includes reviewing historic models, NASA subject matter fuel experts, and a concurrent model. The results, which have been sought out for decades but technology and knowledge were limiting, will provide representative metrics and analysis of environmental effects and interaction of resources to create and maintain fuel on the red planet. This simulation model is the just the starting point of the planning and design strategies.

Publication Date

1-1-2017

Publication Title

SAE Technical Papers

Volume

2017-September

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.4271/2017-01-2017

Socpus ID

85030780928 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85030780928

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