Volume 44 Issue 6
Jun.  2018
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Article Contents
LI Baoyu, ZHANG Leigang, SHI Jiao, et al. Solution method of fractional moments involved in probability density estimation of structural output response[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(6): 1156-1163. doi: 10.13700/j.bh.1001-5965.2017.0664(in Chinese)
Citation: LI Baoyu, ZHANG Leigang, SHI Jiao, et al. Solution method of fractional moments involved in probability density estimation of structural output response[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(6): 1156-1163. doi: 10.13700/j.bh.1001-5965.2017.0664(in Chinese)

Solution method of fractional moments involved in probability density estimation of structural output response

doi: 10.13700/j.bh.1001-5965.2017.0664
Funds:

Equipment Development Department "13th Five-year" Equipment Research Field Foundation of China Central Military Commission 6140244010216HT15001

More Information
  • Corresponding author: ZHANG Leigang, E-mail:leigang_zhang@163.com
  • Received Date: 25 Oct 2017
  • Accepted Date: 15 Dec 2017
  • Publish Date: 20 Jun 2018
  • For the fact that the fractional moment based principle of maximum entropy for structural reliability analysis has some advantages in computational efficiency and precision, in this paper, three computational methods for accurately estimating the fractional moments of constraint condition output response involved in the principle of maximum entropy, are studied and presented, including the dimension reduction integration (DRI) method, the sparse gird integration (SGI) method and the unscented transformation (UT) method. The computational theory and process are expounded, the calculation efficiency of each method is given, and the applicability of each method is analyzed in the paper. The presented three methods can greatly reduce the number of structural input-output model estimates and ensure the accuracy of calculation at the same time, so the efficiency of statistical analysis can be greatly improved. Besides, compared with the Monte Carlo simulation method, the accuracy and efficiency of the presented methods are verified according to the applied examples.

     

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