大弯角串列叶型形状及相对位置的耦合优化设计

To improve the design quality of tandem blade, an automatic optimization system of tandem blade was developed based on an improved particle swarm optimization algorithm (IPSO), adaptive Kriging model and non-uniform rational B-splines(NURBS)method. The optimization system can be used to realize the coupling optimization for shape and relative position of tandem blade. Given that Particle swarm optimization (PSO) algorithm has the advantage of fast convergence speed and may also fall into local optimal solution, an improved particle swarm optimization algorithm was proposed. It can effectively balance the global and local searching ability of PSO by adaptively changing the inertia factor, learning factor, and the number of neighborhood particles. The artificial immune operator can effectively maintain the population diversity of PSO. In addition, NURBS method was used to parameterize tandem blade, and a perturbation method of NURBS control points was designed. It was proved that the improved expected improvement (EI) criterion can make Kriging more easily jump out of the local optimal solution. The optimization system was validated by optimizing a large-turning tandem blade. Results indicate that, as compared with original tandem blade, at design condition, the total pressure loss coefficient of the optimized blade decreased by 40.4%. Besides, the static pressure ratio of optimized blade was higher and the total pressure loss coefficient was smaller at all incidence conditions. The performance of optimized blade was largely improved at positive incidence. It also proved that the coupling optimization design method of tandem blade had a good application value.