Hybrid NN /FEM analysis of the elastoplastic plane stress problem
Abstract
The back-propagation neural network was trained off line in order to simulate operation of the return mapping algorithm. Selection of patterns and the neural network training as well as testing processes are discussed in detail. The network was incorporated into the FE computer code ANKA as a neural procedure. The hybrid neural-network/finite-element-method program ANKA-H was used for the analysis of two elastoplastic plane stress examples: i) perforated tension strip, ii) notched beam. The results of computations point out quite good accuracy of the hybrid analysis. Some prospects of development of hybrid NN/FEM programs are given at the end of paper.
References
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[2] S. Haykin. Neural Networks - A Comprehensive Foundation. Macmillan College Pub!. Co., Maxwell Macmillan Inter., New York- Toronto, 1994.
[3] P. Hajela, L. Berke. Neurobiological computational models in structural analysis and design. Computers and Structures, 41: 657- 667, 1991.
[4] M.N. Jadid, D.F. Fairbairn. Neural-network applications in predicting moment- curvature parameters from experimental data. Engineering Applications of Artificial Intelligence, 9: 309- 319, 1996.
[5] S. Kortesis, P.G. Panagiotopoulos. Neural networks for computing in structural analysis - methods and prospects of applications. Int. J. Num. Mech. Eng., 36: 2305-2318, 1993.
Published
2023-05-25
Issue
pp. 177-188
Section
Articles
License
Copyright © The Author(s).
This work is licensed under the Creative Commons Attribution 4.0 International CC BY 4.0.
How to Cite
Waszczyszyn, Z., & Pabisek, E. (2023). Hybrid NN /FEM analysis of the elastoplastic plane stress problem. Computer Assisted Methods in Engineering and Science, 6(2), 177-188. https://cames3.ippt.pan.pl/index.php/cames/article/view/1316
