Abstract
In this paper both back-propagation artificial neural network (BPANN) and regression analysis are employed to predict the maximum downward deflection of the exit profile in roll-forming of symmetric channel section. To prepare a training set for BPANN, some finite element simulations were carried out. Sheet thickness, flange width, fold angle and friction coefficient were used as the input data and the maximum downward deflection as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the maximum downward deflection of the exit profile for any new given condition. Comparing FEA and BPANN results, an acceptable correlation was found.
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.
