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Identification of plastic properties of metallic structures by artificial neural networks based on plane strain small punch test

Author

Listed:
  • Mohammad Ehsan Hassani

    (Petro State Co)

  • Wenke Pan

    (Siemens Industrial Turbomachinery Ltd)

Abstract

In order to assess the strength of aged and in service components, small punch test (SPT) has emerged. However, it has two disadvantages, firstly using of the hemispherical punch which is difficult to manufacture in most conventional workshops and secondly the known difficulties in obtaining the flat disk samples. This paper discusses a novel approach, the plane strain small punch test to identify the plastic properties of metallic structures. To do so, a new apparatus was designed and manufactured to perform a series of plane strain SPT in room temperature. An artificial neural network was established and trained by the corresponding load displacement responses obtained from the simulations to predict the plastic properties of Stainless Steel 304L.

Suggested Citation

  • Mohammad Ehsan Hassani & Wenke Pan, 2017. "Identification of plastic properties of metallic structures by artificial neural networks based on plane strain small punch test," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 646-654, September.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:3:d:10.1007_s13198-017-0617-5
    DOI: 10.1007/s13198-017-0617-5
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