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CLC number: O344.3
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
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Neural network method for solving elastoplastic finite element problems
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Ren Xiao-qiang, Chen Wu-jun, Dong Shi-lin, Wang Feng. Neural network method for solving elastoplastic finite element problems[J]. Journal of Zhejiang University Science A, 2006, 7(3): 378-382.
@article{title="Neural network method for solving elastoplastic finite element problems",
author="Ren Xiao-qiang, Chen Wu-jun, Dong Shi-lin, Wang Feng",
journal="Journal of Zhejiang University Science A",
volume="7",
number="3",
pages="378-382",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A0378"
}
%0 Journal Article
%T Neural network method for solving elastoplastic finite element problems
%A Ren Xiao-qiang
%A Chen Wu-jun
%A Dong Shi-lin
%A Wang Feng
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 3
%P 378-382
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0378
TY - JOUR
T1 - Neural network method for solving elastoplastic finite element problems
A1 - Ren Xiao-qiang
A1 - Chen Wu-jun
A1 - Dong Shi-lin
A1 - Wang Feng
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 3
SP - 378
EP - 382
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A0378
Abstract: A basic optimization principle of Artificial neural network—the Lagrange Programming neural network (LPNN) model for solving elastoplastic finite element problems is presented. The nonlinear problems of mechanics are represented as a neural network based optimization problem by adopting the nonlinear function as nerve cell transfer function. Finally, two simple elastoplastic problems are numerically simulated. LPNN optimization results for elastoplastic problem are found to be comparable to traditional Hopfield neural network optimization model.
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