Study of the thermo-mechanical behavior of medium carbon microalloyed steel during hot forming process using an artificial neural network
DOI:
https://doi.org/10.3989/revmetalm.066Keywords:
Artificial neuronal network, Dynamic material model, Hot working, Microalloyed steels, Processing mapsAbstract
The thermo-mechanical behavior of medium carbon microalloyed steel has been analyzed by an Artificial Neural Network (ANN). The flow curves for training the ANN have been obtained from the hot compression tests, carried out over a temperature range varying from 900 to 1150 °C and at different true strain rates ranging from 10-4 to 10 s-1. It has been found that the ANN model developed in this study is capable to predict accurately and efficiently the flow behavior of the studied steel and there is a good agreement between the experimental results and the ANN results. To analyze the formability of the studied steel, processing maps have been constructed on the basis of the Dynamic Materials Model (DMM), using the ANN values of the flow stress. The study of maps reveals the different domains of the flow behavior of the studied steel and shows the great similarity between the experimental results and the theoretical results, so the use of the ANN can constitute an interesting alternative for design and study of hot forming processes.
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