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Failure correlation reliability analysis of solid rocket motor grain based on polynomial chaos expansion

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Abstract

Polynomial chaos expansion (PCE) method has better fitting capacity and rate of convergence than other traditional reliability analysis methods. This paper presents the failure correlation reliability analysis based on PCE for improving calculation precision and reducing computational cost. An example of solid rocket motor grain solidification and cooling is analyzed, and the failure correlation reliability between inner surface crack and insulation layer debonding is studied. Results show that an accurate failure correlation reliability analysis result can be obtained by proposed method, and the precision and efficiency of the proposed method are verified by comparing it with traditional methods.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grant No. 11962021, No. 11262014.

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Authors and Affiliations

  1. College of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, 010070, China

    Yangtian Li

  2. College of Science, Inner Mongolia University of Technology, Hohhot, Inner Mongolia, 010051, China

    Yangtian Li, Haibin Li & Guangmei Wei

Authors
  1. Yangtian Li
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  2. Haibin Li
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  3. Guangmei Wei
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Correspondence to Haibin Li.

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Recommended by Editor Chongdu Cho

Haibin Li received his M.S. and Ph.D. in Inner Mongolia University of Technology and Dalian University of Technology, respectively. Currently he is a Professor in the Mechanical Department at Inner Mongolia University of Technology. He has published more than 30 research papers, and done research in the area of theory and application of computational solid mechanics, artificial neural network analytical method, design of press sensor and path planning for multiple mobile robots.

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Li, Y., Li, H. & Wei, G. Failure correlation reliability analysis of solid rocket motor grain based on polynomial chaos expansion. J Mech Sci Technol 34, 3189–3195 (2020). https://doi.org/10.1007/s12206-020-0710-6

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  • DOI: https://doi.org/10.1007/s12206-020-0710-6

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