Structural optimal design method for perforating guns based on computational intelligence

This paper first analyzed the frame structure of oil perforating gun with finite element method. Then a non -linear mapping function was constructed within BP neural networks from maximum stress at blind hole to blind hole depth and diameter calculated. The objective function values used for solving the structural optimization problems with genetic algorithm were obtained, modified genetic algorithm was used to optimize perforating gun structure. The results show that application of this optimal technology based on neural networks and genetic algorithm to perforating gun structural design is effective and reasonable. The technology provides a new thought and method for solving those optimization problems existing in complex structure with multi-variables especially when the optimization object can hardly be explicitly expressed as the function of design variables.