HAN Da-jian, CHEN Tai-cong, SU Cheng. DIGITAL SIMULATION IN ANALYSIS OF STOCHASTIC STRUCTURES: AN ARTIFICIAL NEURAL NETWORK APPROACH[J]. Engineering Mechanics, 2004, 21(3): 49-54.
Citation: HAN Da-jian, CHEN Tai-cong, SU Cheng. DIGITAL SIMULATION IN ANALYSIS OF STOCHASTIC STRUCTURES: AN ARTIFICIAL NEURAL NETWORK APPROACH[J]. Engineering Mechanics, 2004, 21(3): 49-54.

DIGITAL SIMULATION IN ANALYSIS OF STOCHASTIC STRUCTURES: AN ARTIFICIAL NEURAL NETWORK APPROACH

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  • Received Date: November 17, 2002
  • Revised Date: February 20, 2003
  • Among all the methods for analysis of stochastic structures, Monte Carlo (MC) method, a digital simulation method, can provide the most intuitive and accurate solution. However, the disadvantages of vast computation and low computing efficiency block this method from wide use. In this paper, Artificial Neural Network (ANN) is used to replace the deterministic FEM solver in MC simulation. The idea is that FEM is only used to generate the input-output pairs needed for training ANN and that the trained ANN can map out instantly for the structural responses. Thus ANN is used to obtain all the samples for MC statistics. Two numerical examples for analysis of stochastic structures are given. The results show that the proposed MC-ANN method has much higher computing efficiency and better accuracy.
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