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A New Adaptive Response Surface Model for Reliability Analysis of 2.5D C/SiC Composite Turbine Blade

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Abstract

In order to calculate the failure probability of complex structures such as a 2.5D/SiC composites turbine blade and improve the structure safety, a new adaptive model of Response Surface (RS) analysis has been developed in this paper, which can improve the computational efficiency of structural failure problem while ensure the accuracy. The Gaussian Process Regression (GPR) theory was used to establish the RS and reconstruct the performance function of structure. And, an Adaptive Latin hypercube Sampling (ALHS) strategy was adopted in the process of establishing and correcting the RS. Finally the Direct Simulation Monte Carlo(DSMC)was utilized to calculate the failure probability of the performance function replacing the complex structure. Two numerical examples were calculated to validate the accuracy and computational efficiency of the proposed method. Additionally the finite element stress analysis results of 2.5D C/SiC composite turbine blade were used to structural reliability analysis by the proposed method. The approach in this paper provides a new way to evaluate the risk of the complex structures.

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Acknowledgements

Supports of this project provided by National Basic Research Program of China, National Natural Science Foundation of China (51675266), the Fundamental Research Funds for the Central Universities (NJ20160038, NS2017011),Foundation of Graduate Innovation Center in NUAA (No.kfjj20160213), Foundation of Graduate Innovation Center in NUAA (No.kfjj20170208) are gratefully acknowledged.

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Authors and Affiliations

  1. College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People’s Republic of China

    Yaning Chang, Zhigang Sun, Weiyi Sun & Yingdong Song

  2. Key Laboratory of Aero-engine Thermal Environment and Structure, Ministry of Industry and Information Technology, Nanjing, 210016, People’s Republic of China

    Zhigang Sun & Yingdong Song

  3. Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People’s Republic of China

    Yingdong Song

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  1. Yaning Chang
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  2. Zhigang Sun
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Correspondence to Zhigang Sun.

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Chang, Y., Sun, Z., Sun, W. et al. A New Adaptive Response Surface Model for Reliability Analysis of 2.5D C/SiC Composite Turbine Blade. Appl Compos Mater 25, 1075–1091 (2018). https://doi.org/10.1007/s10443-017-9652-2

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  • DOI: https://doi.org/10.1007/s10443-017-9652-2

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