Systems-Modelling of Compact Tension Energy in High Strength Pipeline Steel

The research in this paper aims at linking the steel crack propagation process to the prediction of released flat fracture energy. In this work, an adaptive fuzzy modelling approach and a neural network model with double loop training process were developed in order to build the model for the prediction of flat fracture energy which is normally released during the compact tension (CT) test of X100 pipeline steel. Using the proposed modelling technique, a rule-based fuzzy prediction model as well as a Back-Propagation (BP) neural network model were constructed and optimized automatically from the experimental data. These two models related the load, crack mouth opening displacement (CMOD), and crack length to the released flat fracture energy. The relationship between the fracture propagation and the flat fracture energy was investigated in this paper in detail. The results showed that it is able to predict the flat fracture energy using the proposed modelling approach, and the resulting model can be a useful part of a more comprehensive modelling structure in the future.