A Model for The Prediction of Fracture Toughness Using Neural Network | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 30, Issue 5, March 2012, Pages 868-885 PDF (240.33 K) | ||
| DOI: 10.30684/etj.30.5.13 | ||
| Authors | ||
| Aseel abdulbaky; Dhafer Al-Fattal; Harry Bhadeshia; Talal Abdul Jabbar | ||
| Abstract | ||
| The purpose of this research programme is to develop quantitative models for the prediction of mechanical properties (fracture toughness) using experimental data collected from the literature, together with a powerful computational technique known as neural network. Creating a truly general model requires a combination of available data and metallurgical knowledge. This model is proposed for martensitic and ordinary bainitic steels in addition to the more recent class of non-structural super-bainitic steels. Super-bainitic steels are attractive for many applications such as armour. The model of fracture toughness, based on chemical composition, heat treatment an d mechanical properties is proposed. The predictions of fracture toughness are generally acceptable but the uncertainties are high and more input data need to be collected for super-bainitic steels when available in the future to improve the predictions of this model. | ||
| Keywords | ||
| Fracture toughness; predictions; neural network | ||
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