Unexpected spacecraft failures and anomalies may prompt on-board systems to change a spacecraft's state to a safe mode in order to isolate and resolve the problem. The motivation for this paper is to investigate methods to tailor the impact of safing events for spacecraft of different classes, destination, duration, and other categories of interest. Modeling spacecraft inoperability due to a spacecraft entering safe mode could enable mission planners to more effectively manage spacecraft margins and shape design and operations requirements during the conceptual design phase. This paper contributes to the area of safing event modeling by using available datasets to develop various distributions of frequency and recovery durations of safing events for interplanetary spacecraft missions. A safing event dataset compiled by JPL is first split into multiple subsets based on various mission classifiers. Using a previously developed mission simulation framework, a distribution of the likelihood of inoperability rates is computed through a Monte Carlo simulation. Three main safing event model types are formulated, implemented, and compared in this paper: a single Weibull distribution, a mixture of two Weibull distributions, and a Gaussian Process model. For each model type, two distributions are incorporated into the mission simulation framework: time-between-events and the recovery duration of a safing event. By specifying appropriate parameters in the mission simulation framework and Gaussian Process model, a Monte Carlo simulation is conducted for a solar-electric Mars orbiter similar to the proposed Next Mars Orbiter. Mission implications from simulated outage times and safing events by each model could motivate greater operability, faster fault resolution by operations teams, and greater system margins. By incorporating Gaussian Process models into a mission simulation framework, a process is established by which historical mission data may be incorporated and used to model future safing events for interplanetary mission concepts. This enables mission planners to make more informed decisions during spacecraft development.
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