GOCE Benchmarking Re-Entry Prediction Uncertainties

Summary: During the three week period between the end-of-mission and the re-entry of the ESA GOCE vehicle, orbital data collection resulted in a rich set of data from which to improve the understanding of the uncertainties associated with the re- entry process. Knowledge of the position and attitude of the GOCE vehicle during this period, allied to understanding of the aerodynamics of the vehicle and behavior of the atmosphere, can provide new insight into the processes which drive the uncertainties in the prediction of re-entry timing. From this, a benchmark of a minimal uncertainty obtained from this case, where the vehicle and the entry data are very well known can be determined. In order to perform the uncertainty quantification (UQ) analysis, the intrusive and non-intrusive UQ methods of ICELab have been used.

In particular, the non-intrusive methods have required coupling to the ATS6 Belstead Research Limited proprietary trajectory code, done with a web API over the public internet. Non-intrusive uncertainty quantification methods treat the function of interest as a black box. The way these samples are chosen depends on the non-intrusive technique used. Two methods derived from the literature on uncertainty propagation in fluid dynamics and in dynamical systems are used: the Chebyshev approach and the High Dimensional Model Representation (HDMR) based method, with Monte Carlo sampling used for validation. Uncertainties have been included on the initial state vector as well as the atmospheric conditions, inclusive of the density, solar flux and geomagnetic indexes.

Timeframe: Nov 2015 – Dec 2016

People: Edmondo Minisci, Annalisa Riccardi, Massimiliano Vasile, Romain Serra

Sponsor: European Space Agency

PartnersSpaceDyS, Belstead Research