Multiphysics Coupling Analysis And Cooling Structure Optimization Design Of High-pressure Turbine Blades

Raising the turbine inlet gas temperature is of great significance for improving engine performance,such as increasing engine thrust,improving engine efficiency and engine thrust-to-weight ratio.Raising the gas temperature at the inlet of the turbine will greatly increase the thermal load of the turbine components,and the thermal stress will also increase,which will cause great harm to the blades.Therefore,in order to ensure the normal operation of turbine blades and improve their service life,it is of great strategic significance to study advanced turbine cooling technology.This thesis analyzes the cooling performance of a certain type of high-pressure turbine blade under the coupling of multi-physics,and further optimizes the design of the cooling structure,so as to provide a technical reference for improving the cooling effect of the high-pressure turbine blade.Firstly,the temperature distribution of the high-pressure turbine blade under multiphysics coupling is analyzed,and then the influence of the size,position and shape of the cooling channel in the high-pressure turbine blade on the cooling effect is systematically studied.Then,based on the intelligent optimization algorithm,the multi-disciplinary optimization design of the cooling structure of the high-pressure turbine blade is carried out.In the process of optimizing the design,a multi-physics coupling analysis proxy model of the high-pressure turbine blade based on the BP neural network is established,and the optimization is improved under the premise of ensuring the optimization accuracy.efficiency.Finally,the optimized blade is verified.The work of this thesis is summarized as follows:（1）Parametric modeling of high-pressure turbine blades based on the mid-arc coordinate parameter method.By arranging control points on the plane cascade and on the mid-arc,the coordinates of the control points are represented by parameters,and the relationship between the parameters and the profile is established.The relationship between the two realizes the parametric modeling of the plane cascade.For the internal cooling channel,it is represented by multiple parameters according to its own characteristics.Finally,the model of the high-pressure turbine blade is obtained by stretching the plane cascade.（2）Based on the finite element theory,the fluid-solid-thermal multi-physics coupling simulation analysis is carried out on the high-pressure turbine blades.Using the sequential decoupling method,the temperature distribution cloud map of the highpressure turbine blades is firstly analyzed,and then the structural field analysis is performed to calculate the risk of the turbine blades.Maximum stress,deformation at the point.（3）Analysis of cooling effect of different internal cooling channel structures:Through a large number of experimental comparative analysis,the influence of the number,size and shape of internal cooling channels on the cooling effect of high-pressure turbine blades was explored,and the maximum cooling effect of high-pressure turbine blades under different cooling effects was further analyzed.stress,deformation.（4）Optimal design of the internal cooling channel structure under the constraints of maximum stress,strain and deformation;first,taking maximizing cooling efficiency as the objective function,considering the maximum stress and deformation constraints,combined with BP neural network to establish the optimal design model of the internal cooling channel structure of the high-pressure turbine blade.Secondly,based on the particle swarm algorithm,the multi-disciplinary optimization design of high-pressure turbine blades is realized,and the optimal solution is sought in the design domain.Finally,multi-physics coupling simulation analysis is carried out for the optimized blade to verify the rationality of the optimization method.