Title:
Exploration of Safing Event Models for Interplanetary Spacecraft
Exploration of Safing Event Models for Interplanetary Spacecraft
Author(s)
Pujari, S.
Lightsey, E. Glenn
Imken, Travis
Lightsey, E. Glenn
Imken, Travis
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Abstract
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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Date Issued
2019-03
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Paper
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