This paper presents an enhanced Bayesian based model validation method together with probabilistic principal component analysis (PPCA). The PPCA is employed to address multivariate correlation and to reduce the dimensionality of the multivariate functional responses. The Bayesian hypothesis testing is used to quantitatively assess the quality of a multivariate dynamic system. Unlike the previous approach, the differences between test and CAE results are used for dimension reduction though PPCA and then to assess the model validity. In addition, physics-based thresholds are defined and transformed to the PPCA space for Bayesian hypothesis testing. This new approach resolves some critical drawbacks of the previous method and provides desirable properties of a validation method, e.g., symmetry. A dynamic system with multiple functional responses is used to demonstrate this new approach.


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    Titel :

    A Study of Model Validation Method for Dynamic Systems


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Yang, Ren-Jye (Autor:in) / Fu, Yan (Autor:in) / Zhan, Zhenfei (Autor:in)

    Kongress:

    SAE 2010 World Congress & Exhibition ; 2010



    Erscheinungsdatum :

    2010-04-12




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch


    Schlagwörter :


    A study of model validation method for dynamic systems

    Fu,Y. / Zhan,Z. / Yang,R.J. et al. | Kraftfahrwesen | 2010


    2010-01-0419 A Study of Model Validation Method for Dynamic Systems

    Fu, Y. / Zhan, Z. / Yang, R.-J. et al. | British Library Conference Proceedings | 2010



    Bayesian probabilistic PCA approach for model validation of dynamic systems

    Jiang,X. / Yang,R.J. / Barbat,S. et al. | Kraftfahrwesen | 2009