• DocumentCode
    2895660
  • Title

    Structural Reliability Analysis Based on Neural Network and Finite Element Method

  • Author

    Duan, Wei ; Chen, Li-xin ; Wang, Zhang-Qi

  • Author_Institution
    Sch. of Mech. Eng., North China Electr. Power Univ., Baoding
  • fYear
    2006
  • fDate
    13-16 Aug. 2006
  • Firstpage
    3063
  • Lastpage
    3068
  • Abstract
    A new approach for structural reliability analysis with implicit performance function is presented by combining the neural network, finite element method (FEM) and first-order reliability method (FORM). BP network is applied to approximate the implicit performance function, which is more flexible and adaptive than the polynomial function used in response surface method. The first derivatives of the performance function with respect to random variables can be obtained by the successful trained BP network, which plays an important role in calculating the reliability index. The training samples come from the numerical results of FEM. Two examples are given to demonstrate the validity of the method. The method can be applied to the structural reliability analysis with implicit performance function
  • Keywords
    backpropagation; finite element analysis; neural nets; polynomials; reliability theory; response surface methodology; structural engineering computing; BP network; finite element method; first-order reliability method; neural network; polynomial function; response surface method; structural reliability analysis; Analytical models; Artificial neural networks; Cybernetics; Electronic mail; Finite element methods; Machine learning; Mechanical engineering; Neural networks; Neurons; Performance analysis; Random variables; Response surface methodology; BP neural network; Structural reliability analysis; finite element method; first-order reliability method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2006 International Conference on
  • Conference_Location
    Dalian, China
  • Print_ISBN
    1-4244-0061-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2006.258367
  • Filename
    4028590