Abstract
Hot compression tests were carried out in the temperature range 850 – 1150°C at 0.1 – 60 s-1 strain rates. The hyperbolic sine equation and neural networks were used to model the constitutive behaviour. Evaluating constitutive parameters n, Q and A using the usual log – log plots does not yield constant values. The n, Q and A values were determined simultaneously using a non-linear optimisation procedure and were fitted as functions of strain. These relations, in conjunction with the hyperbolic sine equation, describe the constitutive behaviour of the steel. A 3 : 4 : 1 neural network is trained using 75% of the stress – strain data. The network predicts flow stresses and peak strains with good accuracy. Vanadium increases the peak strain, peak stress, and mean flow stress of austenite significantly.
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