Sensitivity analysis and probabilistic re-entry modeling for debris using high dimensional model representation based uncertainty treatment

Piyush M. Mehta, Martin Kubicek, Edmondo Minisci, Massimiliano Vasile

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
48 Downloads (Pure)

Abstract

Well-known tools developed for satellite and debris re-entry perform break- up and trajectory simulations in a deterministic sense and do not perform any uncertainty treatment. The treatment of uncertainties associated with the re-entry of a space object requires a probabilistic approach. A Monte Carlo campaign is the intuitive approach to performing a probabilistic analysis, however, it is computationally very expensive. In this work, we use a recently developed approach based on a new derivation of the high dimensional model representation method for implementing a computationally efficient probabilistic analysis approach for re-entry. Both aleatoric and epistemic uncertainties that affect aerodynamic trajectory and ground impact location are considered. The method is applicable to both controlled and uncontrolled re-entry scenarios. The resulting ground impact distributions are far from the typically used Gaussian or ellipsoid distributions.
Original languageEnglish
Pages (from-to)193–211
Number of pages19
JournalAdvances in Space Research
Volume59
Issue number1
Early online date1 Sep 2016
DOIs
Publication statusPublished - 1 Jan 2017

Keywords

  • space debris
  • reentry modelling
  • ground impact
  • probabilistic distribution
  • re-entry
  • space situational awareness
  • low Earth orbit (LEO)

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