An efficient approach for identifying constitutive parameters of the modified Oyane ductile fracture criterion at high temperature
The paper presents the theoretical part of a method for identifying constitutive parameters involved in the modified Oyane ductile fracture criterion at high temperature. Quite a general rigid viscoplastic model is adopted to describe material behavior. The ductile fracture criterion is in general p...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Publishing Corporation
2013
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/48998/1/YusofMustafa2013_Anefficientapproach.pdf http://eprints.utm.my/id/eprint/48998/ http://dx.doi.org/10.1155/2013/514945 |
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| Summary: | The paper presents the theoretical part of a method for identifying constitutive parameters involved in the modified Oyane ductile fracture criterion at high temperature. Quite a general rigid viscoplastic model is adopted to describe material behavior. The ductile fracture criterion is in general path-dependent and involves stresses. Therefore, the identification of constitutive parameters of this criterion is a difficult task which usually includes experimental research and numerical simulation. The latter requires a precisely specified material model and boundary conditions. It is shown in the present paper that for a wide class of material models usually used to describe the behavior of materials at high temperatures, the criterion is significantly simplified when the site of fracture initiation is located on traction free surfaces. In particular, this reduced criterion does not involve stresses. Since there are well established experimental procedures to determine the input data for the reduced criterion, the result obtained can be considered as a theoretical basis for the efficient method for identifying constitutive parameters of the modified Oyane ductile fracture criterion at high temperature. The final expression can also be used in computational models to increase the accuracy of predictions |
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