Abstract The safety level of structure with fuzzy uncertainties can be measured by failure possibility. The traditional combining the adaptive Kriging with fuzzy simulation method rely heavily on sampling efficiency, and a large number of samples in whole fuzzy domain needed to be generated, but only the samples belong to failure domain contribute significantly to the failure possibility estimation, which greatly increases the computational cost. In order to improve the sampling efficiency, a novel line sampling based fuzzy simulation combined with adaptive Kriging method is proposed in this paper. In the proposed method, the samples generated by fuzzy simulation are searched along the important direction, and the intersection points between each line and limit state surface are determined by double-loop three-point quadratic polynomial interpolation, so as to acquire higher sampling efficiency. Then the Kriging model is trained by the learning function based on the maximizing the mean square error to accurately determined the intersection points. By introducing Kriging model, the number of real performance function calls is reduced and the computational efficiency is greatly improved. Three test examples and a simplified turbine disk illustrate the effectiveness and accuracy of the proposed method.


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    Titel :

    Line sampling based fuzzy simulation coupled with adaptive Kriging for estimating failure possibility of simplified turbine disk


    Beteiligte:
    Huang, Xiaoyu (Autor:in) / Wang, Pan (Autor:in) / Xin, Fukang (Autor:in) / Li, Lei (Autor:in)


    Erscheinungsdatum :

    2023-09-04




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch