Modeling for Concise Space Mission Utility Simulation with Apollo as Exemplar
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Abstract
Presented is a stochastic modeling method enabling rapid yet comprehensive space mission utility simulation. The method facilitates multivariate analysis with concurrent tradespace exploration, risk assessment, and holistic design while simultaneously exploring, assessing, and developing statistically validated concepts of prospective space missions. Modeling is achieved through the synergistic integration of statistical mechanics, blackbox, Bayesian, ansatz, and analytics techniques. The method is verified for its ability to accurately depict a human spaceflight mission and validated for its ability to perform mission utility analysis by backtesting the Apollo 11–17 missions to the Moon through Monte Carlo simulation.
Keywords
Mission utility simulation Space mission engineering Surrogate modeling Apollo missions ProgspexionNotes
Acknowledgements
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
The author would like to thank all reviewers for their recommendations to this article for publication.
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