Neural network-based simulation of stress concentration factors in reliability-based optimization for mechanical components

Stress concentration damage is one of the most troublesome phenomena encountered in the practical engineering structure. In order to reduce the damage, it is very important for the stress concentration factors to determine arbitrarily and accurately. At present, more attention has been given in the problem of the stress concentration, and modern structural reliability theory and neural network technique have been improved rapidly. But it is difficult for the structural reliability problem to be solved in the case of the stress concentration. Neural network (NN) technique has been used in this work to simulate the relationship between the basic random variables and the stress concentration factors, and the explicit expression of the stress concentration factors can be obtained directly. On the basis of this, the expression of the stress concentration factors given by NN technique and reliability theory have been combined to solve the structural reliability problems in the case of the stress concentration, and then the corresponding methods of reliability analysis and optimization design have been researched in the work.