Nonparametric Importance Sampling Techniques for Sensitivity Analysis and Reliability Assessment of a Launcher Stage Fallout

Pierre Derennes (), Vincent Chabridon (), Jérôme Morio (), Mathieu Balesdent (), Florian Simatos, Jean-Marc Bourinet and Nicolas Gayton
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Pierre Derennes: Université de Toulouse
Vincent Chabridon: Université Paris Saclay
Jérôme Morio: Université de Toulouse
Mathieu Balesdent: Université Paris Saclay
Florian Simatos: Université de Toulouse
Jean-Marc Bourinet: Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal
Nicolas Gayton: Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal

A chapter in Modeling and Optimization in Space Engineering, 2019, pp 59-86 from Springer

Abstract: Abstract Space launcher complexity arises, on the one hand, from the coupling between several subsystems such as stages or boosters and other embedded systems, and on the other hand, from the physical phenomena endured during the flight. Optimal trajectory assessment is a key discipline since it is one of the cornerstones of the mission success. However, during the real flight, uncertainties can affect the different flight phases at different levels and be combined to lead to a failure state of the space vehicle trajectory. After their propelled phase, the different stages reach successively their separation altitudes and may fall back into the ocean. Such a dynamic phase is of major importance in terms of launcher safety since the consequence of a mistake in the prediction of the fallout zone can be dramatic in terms of human security and environmental impact. For that reason, the handling of uncertainties plays a crucial role in the comprehension and prediction of the global system behavior. Consequently, it is of major concern to take them into account during the reliability analysis. In this book chapter, two new sensitivity analysis techniques are considered to characterize the system uncertainties and optimize its reliability.

Date: 2019
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DOI: 10.1007/978-3-030-10501-3_3

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