A Distributed Simulation Of A Martian Fuel Production Facility
Abstract
The future of human exploration in the solar system is contingent on the ability to exploit resources in-situ to produce mission consumables. Specifically, it has become clear that the success of a manned mission to Mars will likely depend on fuel components created on the Martian surface. While several architectures for an unmanned fuel production surface facility on Mars exist in theory, a simulation of the performance and operation of these architectures has not been created. In this paper, the framework describing a simulation of one such architecture is defined. Within this architecture, each component of the base is implemented as a state machine, with the ability to communicate with other base elements as well as a supervisor. An environment supervisor is also created which governs low level aspects of the simulation such as movement and resource distribution, in addition to higher-level aspects such as location selection with respect to operations specific behavior. This simulation will be implemented as an HLA (IEEE 1516e High Level Architecture) application, where each component of the base exists as a federate. A visualization of this simulation is created using a NASA visualization tool called DON (Distributed Observer Network). Metrics, such as fuel production throughput, are then cross validated against result data produced by a concurrent simulation project aiming to model the same scenario using different tools and methodology.
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/10.4271/2017-01-2022
Copyright Status
Unknown
Socpus ID
85030849160 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85030849160
STARS Citation
Loundy, Katherine; Schaefer, Louis; Foran, Andrew; Ninah, Catherine; and Bandong, Khristopher, "A Distributed Simulation Of A Martian Fuel Production Facility" (2017). Scopus Export 2015-2019. 6920.
https://stars.library.ucf.edu/scopus2015/6920