Estimation of deformation induced martensite in austenitic stainless steels

Das, Arpan and Tarafder, S and Chakraborti, P C (2011) Estimation of deformation induced martensite in austenitic stainless steels. Materials Science and Engineering A, 529 (1). pp. 9-20.

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The extent of deformation induced martensite (DIM) is controlled by steel chemistry, strain rate, stress, strain, grain size, stress state, initial texture and temperature of deformation. In this research, a neural network model within a Bayesian framework has been created using extensive published data correlating the extent of DIM with its influencing parameters in a variety of austenitic grade stainless steels. The Bayesian method puts error bars on the predicted value of the rate and allows the significance of each individual parameter to be estimated. In addition, it is possible to estimate the isolated influence of particular variable such as grain size, which cannot in practice be varied independently. This demonstrates the ability of the method to investigate the new phenomena in cases where the information cannot be accessed experimentally. The model has been applied to confirm that the predictions are reasonable in the context of metallurgical principles, present experimental data and other recent data published in the literatures. © 2011 Elsevier B.V.

Item Type:Article
Official URL/DOI:
Uncontrolled Keywords:Austenitic stainless steels; Bayesian neural network; Deformation induced martensite; Martensitic transformation; Significance
Divisions:Material Science and Technology
ID Code:4202
Deposited By:Dr. A K Sahu
Deposited On:05 Nov 2011 12:08
Last Modified:21 Nov 2011 12:06
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