Abstract
This paper introduces a new method for evaluating the tensile test using finite element simulations and data-driven artificial neural networks. For this purpose, a synthetic data set was generated by finite element simulations using LS-DYNA. Artificial neural networks of two different topologies were trained and tested on parts of this synthetic data set. The networks use geometry information of the necking area as input data to predict a correction factor to convert the stress obtained from the tensile test to the equivalent flow stress. The best models are evaluated on the test set and good results are achieved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IOP Conference Series: Materials Science and Engineering
Disclaimer: 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.