Abstract
A back-propagation neural network was applied to fatigue life prediction under multiaxial random loading. The proposed artificial neural network (ANN) model was demonstrated by predicting the multiaxial fatigue life and finding critical locations of an automotive sub-frame within reasonable time. While the conventional methods calculating multiaxial fatigue life with critical plane model require very long-time, this method outputs instantaneously result for a given set of input after the ANN model has been trained. The performance of the ANN model was evaluated by comparing outputs of the ANN with results of the conventional calculation method and acceptable in most fatigue design considerations. Particularly, this method gave good results in searching critical locations.
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.
