To reduce the computational time of the iterations in robust design, meta-models are frequently utilized to approximate time-consuming computer aided engineering models. However, the bias of meta-model uncertainty largely affects the robustness of the prediction results, this uncertainty need to be addressed before design optimization. In this paper, an efficient uncertainty quantification method considering both model and parameter uncertainties is proposed. Firstly, the uncertainty of parameters are characterized by statistical distributions. The Bayesian inference is then performed to improve the predictive capabilities of the surrogate models, meanwhile, the model uncertainty can also be quantified in the form of variance. Monte Carlo sampling is finally utilized to quantify the compound uncertainties of model and parameter. Furthermore, the proposed uncertainty quantification method is used for robust design. A numerical example and a real-world vehicle lightweight case study are used to demonstrate the validity of the proposed method.


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    Titel :

    Quantification of Meta-model and Parameter Uncertainties in Robust Design


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Chen, Chong (Autor:in) / Yu, Helen (Autor:in) / Li, Jie (Autor:in) / Jiang, Yazhou (Autor:in) / Zhan, Zhenfei (Autor:in)

    Kongress:

    SAE 2016 World Congress and Exhibition ; 2016



    Erscheinungsdatum :

    2016-04-05




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch


    Schlagwörter :


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    Robust Autopilot Design Strategy for Functionally Dependent Parameter Uncertainties

    Shaviv, G. E. / Idan, M. | British Library Online Contents | 1996


    Robust Autopilot Design Strategy for Functionally Dependent Parameter Uncertainties

    Shaviv, G. E. / Idan, M. / American Institute of Aeronautics and Astronautics et al. | British Library Conference Proceedings | 1996


    Robust Aeroservoelastic Design with Structural and Trim Parameter Uncertainties

    Dai, Yuting / Wu, Zhigang / Yang, Chao et al. | AIAA | 2012