Open Access Conference Proceedings

The peak point coordinates (i.e. peak stress, peak strain) play a significant role in case of a flow curve description. These coordinates are strongly dependent on the temperature and strain rate, so they need to be related to these thermomechanical circumstances before use in the flow stress models. In this research, the experimental peak point coordinates of the C45 and 38MnVS6 steels were described in a wide range of thermomechanical conditions by use of two different methodologies. The first one was based on the ordinary predictive relationships utilizing the well-known Zener-Hollomon parameter. The second one was based on the artificial neural network approach. The aim was to compare appropriateness of these methods. The results have suggested better aptness in case of the assembled neural networks.

Keywords: Peak point coordinates, predictive relationship, artificial neural network

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