Study On Aerodynamic Performance Optimization Of Turbine Blade Based On CFD

Blade was the key core component of the turbomachinery equipment, such as aircraft engine, steam turbine and so on, which played a decisive role in the performance of the whole machine. And it had an important influence on national energy, national defense and other important fields. Along with scientific and technological progress, the development of high performance turbomachinery put forward new challenges to the design and machining requirements for the blade. Such as higher performance of blade shape and surface profile design, higher machining precision and surface roughness level. Aiming at the above problems, this paper emphatically researched on the blade shape and surface profile optimization design, and the influence of surface roughness on the aerodynamic performance of turbomachinery.In this paper, based on the CFD simulation technology, multi-objective aerodynamic optimization design for the turbomachinery blade shape was studied. The mesh deformation technique was introduced into the optimization design of the blade shape, and the automatic deformation control of the fluid grid of blade was realized. The new blade shape was generated by updating the grid node position of the mesh model directly, which avoided the process of blade geometry parameters and the mesh re-dividing. The design parameters were reduced and the efficiency of the optimization design was improved. Response Surface Model, Kriging, Radial Based Function approximate models and Hybrid Multi-Gradient Exploration, modified Non-dominated Sorting Genetic Algorithm were compared and analyzed, the results show that the Kriging approximation model has high fitting accuracy and good robustness, Hybrid Multi-Gradient Exploration optimization algorithm has high efficiency and accurate result. Thus a combinatorial optimization design method was proposed, which formed by optimum Latin hypercube design method, Kriging approximation model and Hybrid Multi-Gradient Exploration. Through the above mentioned optimization design method, a new multi-objective aerodynamic optimization design platform was constructed, which was based on the mesh free-form deformation. And the equal entropy efficiency and the total pressure ratio were took as objective functions, the deformation of grids control parameters were took as design variations to implement the aerodynamic optimize design of aeroengine blade. Through the analysis and summary of the optimization results, the effectiveness of the blade aerodynamic optimization design platform was verified, and the optimization efficiency was higher compared with the traditional blade aerodynamic optimization design method.A study on the local detail fine aerodynamic optimization design of turbomachinery blade surface profile was carried out. The fine design made the design parameters increase, and the calculation quantity was also increased significantly. The general optimization method was difficult to fit the design requirements. Thus, the adjoint method, which is almost independent of the amount of computation and the number of design variables, was introduced into the fine design of the blade surface profile. Based on the adjoint method and the adjoint equation of the flow field, the gradient of the objective function to the control point of mesh free-form deformation was derived. The advantages and disadvantages of the three unconstrained gradient optimization algorithms were analyzed and compared, which were the steepest descent method, the conjugate gradient method and the quasi Newton method. And the BFGS quasi Newton method with Armijo-Goldstein line search algorithm was determined as the optimal gradient optimization algorithm. Thus, the blade three dimensional detail fine aerodynamic optimization design platform was constructed, which based on the adjoint method, the mesh free-form deformation method and the gradient optimization algorithm. Through the optimization design platform, took the outlet entropy as the objective function, mesh deformation parameters as design variables, aeroengine blade surface fine aerodynamic optimization design was achieved effectively. The results show that the influence of blade profile on its performance is deeply understood through gradient information, and compared to the global search algorithm, the computation quantity is greatly reduced, which greatly improves the efficiency of the optimization design. The optimization design platform and the blade global multi-objective aerodynamic optimization design platform form a complementary relationship.In the end, the influence of blade surface roughness on the aerodynamic performance of turbomachinery was studied. The micro morphology of rough surface was analyzed from the aspect of blade machining mechanism. Based on the existing aerodynamic model and the relationship between surface roughness and aerodynamics, the influence of blade surface roughness on the aerodynamic performance was studied, and the surface roughness of blade fillet, blade hub and blade tip, which were difficult to polished, was also researched. The results show that the increase of the surface roughness of aeroengine blade increases the blade loss and degrades the aerodynamic performance. The influence of the roughness of the suction surface of the blade on the performance is greater than that of the pressure surface. The surface roughness of the difficult polishing area also increases the blade loss, the blade hub has the greatest impact on its performance. When the blade surface roughness Ra is less than 0.1um, the surface is smooth and the blade can obtain the most ideal aerodynamic performance. When the blade surface roughness Ra is greater than 1.5um, the impact extent of surface roughness on the performance of the blade becomes larger.The research results obtained in this paper play an active role in the development and improvement of the 3D Aerodynamic Optimization Design System of the turbomachinery, also has guiding significance in the processing and maintenance of the turbomachinery blade.