Strength Design of Special-Shaped Holes in Double-Walled Turbine Blade Based on Neural Network
With the rapid development of aeroengine field,the service environment of hot end turbine blade is becoming increasing severe.In order to improve the heat bearing capacity of blade,the double-walled blade structure is proposed in the industry,which is based on the principle of"outer wall heat bearing,inner wall load bearing".In this paper,aiming at ensuring the structural strength of double-walled blade film hole,a parametric modeling is used to construct the blade shape and the outer wall hole structure,and the influences of hole design parameters on the perimeter structure strength of the cylindrical film hole,the conical expansion hole and the dustpan expansion hole are determined through simulation analysis.Then,according to the parameter input and the corresponding response,a Radial Basis Function(RBF)neural network model is constructed and further optimized through adjusting the weights and thresholds using the genetic algorithm to improve the accuracy of the surrogate model.Finally,the optimal hole designs for three film holes are obtained.Compared with the original cylindrical hole,the perimeter stress is reduced by 25.12％and 22.54％,respectively for the conical expansion hole and the dustpan expansion hole.
万方数据
维普
