Bayesian Neural Network Model for Austenite Formation in Steels

L. Gavard, H. K. D. H. Bhadeshia, D. J. C. MacKay and S. Suzuki

Abstract

The formation of austenite during the continuous heating of steels has been investigated using neural network analysis with a Bayesian framework. An extensive database consisting of the detailed chemical composition, Ac₁ and Ac₃ temperatures, and the heating rate was compiled for this purpose, using data from the published literature. This has been assessed using a neural network, with the aim of modelling the austenite--start and finish temperatures. The results from the neural network analysis are found to be consistent with what might be expected from phase transformation theory.

Materials Science and Technology, Vol. 12, 1996, 453-463.

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Computer program & documentation for Ac1 calculation

Computer program & documentation for Ac3 calculation

PDF file of explicit non-linear equations for Ac1 and Ac3.

Latex file of explicit non-linear equations for Ac1 and Ac3.

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