Nonuniform height endwall fence optimization of a low-pressure turbine cascade

As the lift of turbine increases, the secondary flow in the endwall region seriously restricts improvement of the aerodynamic performance of low-pressure turbine. The particle swarm optimization is improved to pursue stronger optimization ability. An optimization platform is built that combines Bayesian optimization (BO), the eXtreme Gradient Boosting (XGBoost) algorithm and improved chaos particle swarm optimization. The test results show that the surrogate model optimization method proposed in this paper has more prominent application potential in the field of aerodynamic optimization. The above optimization method is used for the optimization design of the nonuniform height endwall fence (NHEF) of a high-lift low-pressure turbine cascade to achieve an efficient secondary flow control effect. The NURBS curve is used to realize the parameterization of the NHEF. The secondary flow control mechanism of traditional fences and NHEF has been compared and analysed in detail. The numerical results show that the NHEF can effectively prevent the cross migration of the boundary layer, and the fence vortex induced by the fence can suppress the development of the passage vortex. The total pressure loss at the outlet of the cascade installed NHEF is reduced by 14.82%. The secondary flow control effect of the NHEF is better than that of a traditional fence. The feature importance analysis results of input variables show that the pitchwise position of the fence has the most obvious influence on the loss of the cascade. In addition, based on the results of feature importance, a 53% length reduction fence is designed to reduce the extra weight brought by the fence. The design achieves the effect of comprehensively considering the weight and aerodynamic performance.