This paper demonstrates the use of generalized polynomial chaos expansion for the propagation of uncertainties present in various dynamical models. Specifically, a sampling based non-intrusive approach using pseudospectral stochastic collocation is employed to obtain the coefficients required for the generalized polynomial chaos expansion. Various recently developed quadrature techniques are employed within the generalized polynomial chaos expansion framework in order to illustrate their efficacy. In addition to that, the paper also provides an efficient numerical quadrature technique to be used as a sampling technique in stochastic collocation to quantify the uncertainties which are governed by different distribution functions. Results are presented for the orbital motion of a 2U CubeSat subject to initial condition uncertainty and drag related parametric uncertainty demonstrating the accuracy and effectiveness of the proposed technique. Further, stochastic sensitivity analysis is performed to gain insight into the impact of uncertain variables on the evolution of the quantities of interest.
Generalized Polynomial Chaos Expansion Approach for Uncertainty Quantification in Small Satellite Orbital Debris Problems
J Astronaut Sci
The Journal of the Astronautical Sciences ; 67 , 1 ; 225-253
2020-03-01
29 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Stochastic systems , Uncertainty propagation , Orbital uncertainty , Generalized polynomial chaos expansion , Sensitivity analysis Engineering , Aerospace Technology and Astronautics , Mathematical Applications in the Physical Sciences , Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
SAE Technical Papers | 2020
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