Estimation of fracture toughness of tempered nanostructured bainite

Abstract

Fine structures consisting of a mixture of extremely thin bainite plates embedded in a matrix of austenite, are now a commercial proposition. Whereas the phase transformation theory for such structures is fairly well established, the understanding of their mechanical properties is not. The present work is an attempt to express the fracture toughness of such steels using a neural network method exploiting data available for martensitic and ordinary bainitic steels. It is demonstrated that in spite of uncertainties, the model captures reasonable trends and is able to estimate unseen experimental results on the nanostructured bainite.

Keywords:

• Nanostructured bainite
• Neural network
• Toughness
• Modelling

The authors are grateful to British Universities Iraq Consortium and the Council for Assisting Refugee Academics (CARA) for funding this work, to the Ministry of Education & Scientific Research in Iraq, and to the University of Cambridge for the provision of laboratory facilities.