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《Journal of Mechanical Strength》 2004-01
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RELIABILITY ANALYSIS FOR FATIGUE CRACK GROWTH LIFE BASED ON NEURAL NETWORK RESPONSE SURFACE

TIAN Chen YAN HongSheng HU YunChang (School of Civil Engineering, Tianjin University, Tianjin 300072, China)  
On condition that the limit state function is highly complex due to many random variables or nonlinearity, the conventional methods for calculation of failure probability are inappropriate. In response to the complexity of calculation for failure probability regarding fatigue crack growth life, a method for reliability analysis based on neural network response surface was presented. First of all, a neural network response surface was established to simulate the limit state function of fatigue crack growth life, then the gene arithmetic(GA)was used to calculate the reliability index. Numeric experiments indicate that limit state function for fatigue crack growth life can be quickly, exactly simulated by using this method, then the failure probability and the reliability index will be easily worked out. Compared with other simulation technique, neural network response surface method can greatly reduce the simulation time at the same precision level.
【Fund】: 天津市自然科学基金资助项目 (0 2 360 781 1 )~~
【CateGory Index】: O346
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