A modified damage law with the fuzzy neural network method for crack initiation life prediction of notched specimen

Authors

  • Jiaying Gao School of Aeronautic Science and Engineering, BeiHang University, Beijing 100191, China
  • Peng Li School of Aeronautic Science and Engineering, BeiHang University, Beijing 100191, China
  • Qiuyang He Department of Computer Science, The University of York, York, U.K.

DOI:

https://doi.org/10.5755/j01.mech.23.6.14862

Keywords:

Modified damage law, Fuzzy neural network, Crack initiation, Notched specimen, experimental verification

Abstract

It is difficult to predict the fatigue life of notched specimen due to the complexity of notch effect. Based on the continuum damage mechanics theory of Lemaitre, a modified damage law for fatigue life prediction of notched specimen combined with the fuzzy neural network method is proposed to obtain a more reliable life. According to the fatigue experimental data, the material parameters in the damage evolution equation are demarcated. Then the fatigue life prediction of notched specimen is conducted. At last, after the stage pf experiment data collection and NN training , the established NN model will be able to reduce the relative error from 20.85% to about %7.12 in the verification test. Although the life prediction after being modified may not be accurate in every local region, the combination between the theoretical method and the fuzzy neural network method will obtain a more reliable material life in the whole.

DOI: http://dx.doi.org/10.5755/j01.mech.23.6.14862

Author Biography

  • Jiaying Gao, School of Aeronautic Science and Engineering, BeiHang University, Beijing 100191, China
    Doctor

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Published

2017-12-28

Issue

Vol. 23 No. 6 (2017)

Section

MECHANICS OF SOLID BODIES

License

The copyright for the articles in this journal is retained by the author(s) with the first publication right granted to the journal. The journal is licensed under the Creative Commons Attribution License 4.0 (CC BY 4.0).