Space debris reentry prediction and ground risk estimation using a probabilistic breakup model

While the number of artificial space object re-enter the Earth atmosphere daily, predicting the reentry of a space debris remains an open problem. The reentry prediction is a multi-physics problem involving aerodynamics computations in rarefied and continuum flow, heat transfer calculations and structural breakup predictions. Additionally, numerous uncertainties coming from unknown initial flight conditions, material properties or uncal-ibrated model parameters affect our ability to make accurate predictions. In this work, we propose an original reentry prediction framework that associates deterministic physical solvers with a stochastic breakup model and uncertainty quantification tools to make robust reentry predictions and a statistical estimate of the impact location. Our method is able to predict breakup distributions and ground impact locations efficiently using simplified but robust models at reasonable computational cost. This framework is used to predict the reentry of an Upper Stage deorbited from a GTO orbit.