A major challenge in the design of multi-stage compressors is the matching of stages to enable stable operation over a large range of mass flows and operating conditions. Particularly in turbofan low-pressure compressors, where a variable geometry cannot be implemented, design strategies for maximum efficiency at high speed can compromise the surge margin at low speed. In this thesis, a design optimization framework has been implemented to an industry-strength compressor-matching problem. The optimization framework combines a mean-line flow solver and a dynamic stability analysis of a six-stage low-pressure compressor of a modern turbofan engine to optimize the blade row geometry for enhanced stability at flight idle conditions. To assess the potential improvements in compressor stability at low speed, a number of optimization strategies are employed using different objective functions and stability metrics. To estimate the performance and stability of the six-stage compressor, a mean-line flow solver is developed and coupled with a previously developed dynamic compressor-stability analysis. A fan-root flow model and an endwall loss correlation are developed using performance data provided by industry.
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