Neural Networks in Crashworthiness Analysis of Thin-Walled Profile with Foam Filling
| 1 | Faculty of Mechanical Engineering, Lublin University of Technology, Lublin, Poland |
CORRESPONDING AUTHOR
Michał Karol Rogala
Faculty of Mechanical Engineering, Lublin University of Technology, Lublin, Poland
Faculty of Mechanical Engineering, Lublin University of Technology, Lublin, Poland
Publication date: 2020-09-01
Adv. Sci. Technol. Res. J. 2020; 14(3):93–99
KEYWORDS
TOPICS
ABSTRACT
This article presents numerical tests of thin-walled compressed columns with square cross-section. Crush efficiency indicators were determined using finite element method (Abaqus) and neural networks of MLP. The models had a constant circular trigger, with a diameter of 32mm. During dynamic analysis the samples were loaded with 1700J. The numerical models were filled with aluminum foam from 40mm to 180mm every 20mm. The study presents conclusions for thin-walled models with crushable foam.
RELATED ARTICLE
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.