Sensitivity analysis and probabilistic re-entry modeling for debris using high dimensional model representation based uncertainty treatment
Mehta, Piyush M. and Kubicek, Martin and Minisci, Edmondo and Vasile, Massimiliano (2017) Sensitivity analysis and probabilistic re-entry modeling for debris using high dimensional model representation based uncertainty treatment. Advances in Space Research, 59 (1). 193–211. ISSN 0273-1177 (https://doi.org/10.1016/j.asr.2016.08.032)
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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.
ORCID iDs
Mehta, Piyush M., Kubicek, Martin ORCID: https://orcid.org/0000-0002-9800-1209, Minisci, Edmondo ORCID: https://orcid.org/0000-0001-9951-8528 and Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465;-
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Item type: Article ID code: 57685 Dates: DateEvent1 January 2017Published1 September 2016Published Online24 August 2016Accepted15 October 2015SubmittedSubjects: Technology > Motor vehicles. Aeronautics. Astronautics Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Strategic Research Themes > Ocean, Air and SpaceDepositing user: Pure Administrator Date deposited: 06 Sep 2016 08:35 Last modified: 11 Nov 2024 11:30 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/57685