Abstract

PurposeThis study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.Design/methodology/approachA quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.FindingsThe proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.Originality/valueCFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.

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