Active Mission Success Estimation through PHM-Informed Probabilistic Modelling

Adam R. Short and Douglas L. Van Bossuyt
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phmc_15_051.pdf799.35 KBAugust 24, 2015 - 12:17pm

Prognostics and Health Management (PHM) techniques have traditionally been used to analyze electrical and mechanical systems, but similar techniques can be adapted for less mechatronically-focused processes such as crewed space missions. By applying failure analysis techniques taken from PHM, the probability of success for missions can be calculated. Extensive work has been done on predicting space mission failure, but many of the methods do not take full advantage of modern computing power and the potential of real-time calculation of mission failure probabilities. To address this problem, a new method has been developed that tracks and calculates the probability of mission failure as the mission progresses, and can be adapted for shifting mission objectives and parameters. This form of mission modelling takes a broader view of the mission and objectives, and present probabilities of success for multiple possible choices that can be used to inform decisions and maximize probability of mission success. For this paper, a hypothetical crewed Mars survival mission is considered where an astronaut has been left behind on the surface and must survive for an extended period of time before making a long distance journey to a new launch site for potential rescue. The method presented here helps to establish probabilistic models for mission success and can be used to help inform mission decisions.

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Submission Keywords: 
model design space exploration
applications: space
mission planning
Submission Topic Areas: 
Modeling and simulation
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