A case study on quantifying reliability under extreme risk constraints in space missions

In this paper, we employ a Bayesian approach to uncertainty quantification of computer simulations used to assess the probability of rare events. As a case study, we assess the reliability of an Earth re-entry capsule for a Mars sample return mission that must be able to withstand the re-entry loads in order to land intact. Our study uses Gaussian Process modeling under a Bayesian regime to analyze the re-entry vehicle’s resilience against operational stress. This Bayesian framework allows for a detailed probabilistic evaluation of the system’s reliability, indicating our ability to verify stringent safety goals of rare events with a 0.999999 probability of success. The findings underscore the effectiveness of Bayesian methods for complex uncertainty quantification analyses of computer simulations, providing valuable insights for computational reliability analysis in a risk-averse setting.