Numerical Analysis About Strain-Softening And Research Of Neural Computational Mechanics In Mechanics Simulation

This paper comprises two parts: one is named "Numerical Analysis of Strain-Softening" and the other is named "Neural Computational Mechanics". The first part of the paper studies the problems on theory x computational methods and computational models of strain-softening. The second part puts neural network into mechanics simulation, and a new branch of computational mechanics called "The neural computational mechanics" is built.In the first part of this paper some works are performed as follows:1. In theory, It is graphically illustrated that strain-softening materials satisfy the IPyushin hypothesis at the space of strain. The non-Uniqueness of solution to structure considering material strain-softening wills occur evens if under conditions of small deformation. At the same time, a coupled-principle that is used to judge the bifurcation of structure is put forward. At last a numerical method to obtain the limit load of structure is given.2. In terms of computational models for simulating strain-softening, It is showed that the finite element with inner fictitious crack and the finite element with cracking band are the same in essence, and that some non-local models can not overcome the problems of mesh's dependence and zero consumes of energy.3. As to computational methods, it is showed that every accelerated initial stiffness scheme can not make sure of the converge of iteration while considering material's strain softening. A new method that fits strain-harden as well as strain-softening is given.4. With the finite element with inner softening band, the cracking of Xi Luodu arch-dam is analyzed. Some useful conclusions are arrived at.In the second part of this paper some works are performed as follows:1. At first, some basic neural networks are introduced, and their characteristics are discussed. The neural computational mechanics-a new branch of computational mechanics- is put forward, and the definition, the system and the research direction are given.2. The neural algorithms for automatic generation of FE mesh and simulation of construction stages are put forward. With them the FE mesh can be adjusted automatically and the structure of different stages may be analyzed with a FE mesh.3. A new neural network and algorithm used to draw the constitutive relation of material from information of the force and displacement is put forward. The system of drawing the constitutive relation of material by neural network is improved.4. The design principle of neural network for structure's optimum is researched in theory and a general design method is given. A new enejgy function of Hopfield network is put forward. On the basis of this function, the unnecessary of Kuadao symmetry is proved. The modified Hopfield network that can solve the equations of unsymmetrical stiffness matrix is designed.