A neurocomputing model for the elastoplasticity Original Research Article

To shorten the time of the structural analysis based on the finite element method is very important and of interest to engineers and mechanics. In this paper, on the foundation of the “Parametric Variational Principle for elastoplasticity”, a new variational principle called “Two-type-variable Variational Principle” is proposed so that the neural networks theory can be used to solve the elastoplastic problems. For the two-type-variable minimum potential energy principle, the energy function and the constraint conditions of the neural networks are built up, and the structure and parameters are given. As an example, the simulation on the neurocomputation of a simple truss is taken. It is shown that the neurocomputed conclusions are well agreement with that of theoretical analyzed and the solution of the elastoplasticity can be obtained within an elapsed time of the circuit time-constant (nano-second-order).