This paper presents a procedure for experimentally optimizing a multistage axial compressor. Due to the usual proprietary nature of such tests, a mean-line model of a nine-stage compressor with three rows of variable geometry is used instead of a real machine as a testbed for explaining the optimization method. The compressor is optimized to achieve design-intent corrected flow and pressure ratio while achieving acceptable efficiency and stage matching. The optimization is performed using a response surface methodology that leverages a full factorial design of experiments approach. The resulting empirical models of compressor performance are of high quality, with coefficients of determination exceeding 0.99. An important finding of the work is that stage interactions are important for modeling both efficiency and stage matching, much more than for corrected flow and pressure ratio. Additionally the empirical equations resulting from the design of experiments analysis provide sensitivities due to changes in the variable geometry. These sensitivities can be applied to understanding the impact of uncertainties related to rigging the variable geometry and for assessing potential new or upgraded compressor designs.

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