Neuro-finite element static analysis of structures by assembling elemental neuro-modelers

Recently, several algorithms have been proposed for using neural networks in dynamic analysis of small structural systems, and also constructing adaptive material modeling subroutines with the aim of their implementation in finite element computer programs. In these algorithms, the neural networks are trained based on the data obtained from tests at structural or material levels. In this paper, a new method of using neural networks for static analysis of non-linear structures is presented which works with test results at elemental level. The method is based on the assemblage of elemental information to form the global information about the structure, and hence it is called the Neuro-Finite Element (NFE) method. Multi-layer feed-forward neural networks are used. Two small sample problems, a plane truss and a plane frame, and also a larger space truss are included for illustration. The results have been promising.

• Type: Conference
• Year: 2003
• Where: EUSFLAT
• Authors: Abdolreza Joghataie
• Keywords: EUSFLAT 2003, EUSFLAT 2007, Feed-forward Neural Networks, Material Modeling Subroutines, Neural Networks