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

5 Scopus citations

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 un-controlled re-entry scenarios. The resulting ground impact distributions are far from the typically used Gaussian or ellipsoid distributions.

Original languageEnglish (US)
Pages (from-to)193-211
Number of pages19
JournalAdvances in Space Research
Volume59
Issue number1
DOIs
StatePublished - Jan 1 2017

Bibliographical note

Funding Information:
Funding for Piyush Mehta is provided by the European Commission through the Marie Curie Initial Training Network (ITN) STARDUST under Grant No. 317185 . Partial support for Martin Kubicek is provided by ’OPTIMAD Engineering Srl’. The authors would like to acknowledge the use of the EPSRC funded ARCHIE-WeSt High Performance Computer ( www.archie-west.ac.uk ), EPSRC Grant No. EP/K000586/1 .

Keywords

  • Debris
  • Ground-impact
  • Modeling
  • Probabilistic-distribution
  • Re-entry

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