Abstract 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.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Generalized Polynomial Chaos Expansion Approach for Uncertainty Quantification in Small Satellite Orbital Debris Problems


    Beteiligte:


    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.60 Raumfahrttechnik
    Lokalklassifikation TIB:    770/7040




    Uncertainty Quantification in Vibroacoustic Analysis of a Vehicle Body Using Generalized Polynomial Chaos Expansion

    Schmid, J.D. / Sepahvand, K. / Luegmair, M. et al. | SAE Technical Papers | 2020


    Uncertainty Quantification for Ignition Delay Times Using Polynomial Chaos Expansion

    Clark, Ryan J. / Hageman, Mitchell D. / Knadler, Michael S. et al. | TIBKAT | 2023


    Uncertainty Quantification for Ignition Delay Times using Polynomial Chaos Expansion

    Clark, Ryan J. / Hageman, Mitchell D. / Knadler, Michael S. et al. | AIAA | 2023