Abstract
AbstractThe 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 the elicited model is able to predict the flat fracture energy using the proposed modelling approach, and can hence form an important part of a more comprehensive modelling structure in the future.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
