An approach for Probabilistic Reanalysis (PRA) of a system is presented. PRA calculates very efficiently the system reliability or the average value of an attribute of a design for many probability distributions of the input variables, by performing a single Monte Carlo simulation. In addition, PRA calculates the sensitivity derivatives of the reliability to the parameters of the probability distributions. The approach is useful for analysis problems where reliability bounds need to be calculated because the probability distribution of the input variables is uncertain or for design problems where the design variables are random. The accuracy and efficiency of PRA is demonstrated on vibration analysis of a car and on system reliability-based optimization (RBDO) of an internal combustion engine.


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    Titel :

    Probabilistic Reanalysis Using Monte Carlo Simulation


    Weitere Titelangaben:

    Sae Int. J. Mater. Manf
    Sae International Journal of Materials and Manufacturing


    Beteiligte:
    Farizal (Autor:in) / Nikolaidis, Efstratios (Autor:in) / Zhang, Geng (Autor:in) / Saleem, Sirine (Autor:in) / Mourelatos, Zissimos P. (Autor:in)

    Kongress:

    SAE World Congress & Exhibition ; 2008



    Erscheinungsdatum :

    2008-04-14


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Probabilistic Reanalysis Using Monte Carlo Simulation

    Nikolaidis, E. / Saleem, S. / Farizal et al. | British Library Conference Proceedings | 2008


    Probabilistic reanalysis using Monte Carlo simulation

    Nikolaidis,E. / Saleem,S. / Zhang,G. et al. | Kraftfahrwesen | 2008


    2008-01-0215 Probabilistic Reanalysis Using Monte Carlo Simulation

    Nikolaidis, E. / Saleem, S. / Farizal et al. | British Library Conference Proceedings | 2008



    Assessment of Imprecise Reliability Using Efficient Probabilistic Reanalysis

    Farizal / Nikolaidis, Efstratios | SAE Technical Papers | 2007