ANN back-propagation prediction model for fracture toughness in microalloy steel

Fracture toughness of microalloy steel was evaluated as per ASTM E399 standard. Artificial neural network back-propagation model was developed to predict the behavior of fracture toughness and tensile strength its a function of microstructure. Both fracture toughness and tensile strength were found to increase with the increase in martensite content in a dual phase microstructure of microalloy steel. The primary objective of the ANN Back-propagation (BP) prediction model was to validate and extend the application of microalloy steels for various engineering applications. ANN training model was found to be in good agreement with the experimental results. The ANN training model has been used to predict the best/optimum toughness properties in terms of intercritical annealing temperature and martensite content, This can be used as a practical tool for predicting the fracture toughness in other series of steels comprising dual-phase microstructures and also to optimize strength and ductility properties. (C) 2002 Elsevier Science Ltd. All rights reserved.