• DocumentCode
    1637120
  • Title

    Unified uncertainty analysis using the maximum entropy approach and simulation

  • Author

    Xiao, Ning-Cong ; Huang, Hong-Zhong ; Li, Yanfeng ; Zuo, Ming J.

  • Author_Institution
    Sch. of Mech., Electron., & Ind. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Two types of uncertainty may exist in engineering. In this paper, a unified uncertainty (UUA) analysis method is proposed to handle the two types´ uncertainties. The presented method involves three main steps: (1) sampling on both random variables and interval variables, (2) approximating the maximum entropy density function by using the first four moments, (3) determining the lower and upper bounds of the system probability of failure. The proposed method is found to be more efficient, robust and sometimes more accurate than the existing methods like the unified uncertainty analysis (UUA) based on the first order reliability method (FORM-UUA) for it requires neither the search of the most probable point (MPP) nor the non-normal variables to normal transformation. One mathematical example and one engineering example are presented to demonstrate the proposed method.
  • Keywords
    function approximation; maximum entropy methods; probability; reliability theory; sampling methods; FORM-UUA; failure system probability; first order reliability method; interval variable sampling; lower bound determination; maximum entropy density function approximation; most probable point; nonnormal variables; random variable sampling; unified uncertainty analysis method; upper bound determination; Approximation methods; Entropy; Random variables; Robustness; Uncertainty; Upper bound; aleatory uncertainty; epistemic uncertainty; maximum entropy approach; mixture variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium (RAMS), 2012 Proceedings - Annual
  • Conference_Location
    Reno, NV
  • ISSN
    0149-144X
  • Print_ISBN
    978-1-4577-1849-6
  • Type

    conf

  • DOI
    10.1109/RAMS.2012.6175467
  • Filename
    6175467