A Study on the Life Prediction Method using Artificial Neural Network under Creep-Fatigue Interaction

인공 신경망을 이용한 크리프-피로 상호작용시 수명예측기법에 관한 연구

  • Published : 2001.11.01

Abstract

The effect of tensile hold time on the creep-fatigue interaction in AISI 316 stainless steel was investigated. To study the fatigue characteristics of the material, strain controlled low cycle fatigue(LCF) tests were carried out under the continuous triangular waveshape with three different total strain ranges of 1.0%, 1.5% and 2.0%. To study the creep-fatigue interaction, 5min., 10min., and 30min. of tensile hold times were applied to the continuous triangular waveshape with the same three total strain ranges. The creep-fatigue life was found to be the longest when the 5min. tensile hold time was applied and was the shortest when the 30min. tensile hold time was applied. The cause fur the shortest creep-fatigue life under the 30min. tensile hold time is believed to be the effect of the increased creep damage per cycle as the hold time increases. The creep-fatigue life prediction using artificial neural network(ANN) showed closer prediction values to the experimental values than by the modified Coffin-Manson method.

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References

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