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Three-Dimensional Multi-Objective Design Optimization of a 6.5-Stage Axial Flow Compressor Blades With Lean and Twist


 With great development in numerical optimization and wide application of computational fluid dynamic methods, the three-dimensional design optimization of multi-stage axial flow compressor will become a routine practice in the future. The common critical issue arisen from the practice is how to carry out the three-dimensional design optimization of multi-stage axial flow compressor at an affordable design cost. To tackle this problem, a three-dimensional design optimization method is developed, in which reference vector guided evolutionary algorithm, the ensemble of surrogate models, adaptive sampling method and computational fluid dynamics (CFD) simulation are integrated, to improve the adiabatic efficiency and broaden the stability margin. The ensemble of surrogate model consists of linear regression model, support vector regression model, Kriging model and radial basis function. The blade lean and twist are set as design variables for all the stators while for the rotors only the blade twist is considered. By taking advantage of these advanced methods, a 6.5-stage axial flow compressor with totally 60 design variables is optimized at design speed-line. CFD calculations show that the adiabatic efficiency at design point is increased by 0.88%. The stall margin is increased from 12.72% to 14.08%, and the choke margin is increased from 20.41% to 21.35%. Flow analysis of the optimal compressor indicates that the blade lean is mainly responsible for suppressing the endwall flow separation while the blade twist for the stage match between adjacent blade rows. This work is of great significance for three-dimensional multi-objective design optimization of multi-stage axial flow compressor.