Aerodynamic optimization for low pressure turbine exhaust hood using Kriging surrogate model

To further improve the pressure recovery capability of low pressure turbine exhaust hood, an aerodynamic optimization system has been developed on the Matlab platform. The shape optimization for a scale model of a low pressure exhaust hood is numerically performed to maximize the mass averaged pressure recovery coefficient while subjecting to geometric constraints. Two cubic Bezier curves are used to represent the flow guide and the bearing cone profiles, respectively. Evaluation of the aerodynamic performance of the model is carried out by the commercial CFD simulator CFX. The Kriging model is used as a surrogate, which establishes a global mapping between design variables and objective function. In order to seek a balance between local and global search, an adaptive sample criterion is employed. The optimal design exhibits a reasonable performance improvement compared with the original design.