In turbomachinery optimisation problems, run time is often a critical factor due to high dimensionality of the design search space. This work explores the use of the multi-fidelity method to speed up an aerodynamic optimisation algorithm applied to axial compressor blades. A rotor blade is optimised in a two-stage blade geometry for maximum isentropic efficiency. The single-fidelity reference optimisation uses a high-fidelity evaluation process employing Menter SST turbulence equations and a mesh of 903.000 cells. Five multi-fidelity optimisation setups are tested, which employ the same high-fidelity process, but
distinct low-fidelity processes ranging from a fine mesh and RANS turbulence equations to a coarse mesh and inviscid Euler equations. It is found that multi-fidelity optimisation could cause a delay in run time of up to 39.9%, equivalent to almost three days and a loss in optimum efficiency of 0:11%. The best result is a speed-up of 14.1%, equivalent to 1 day of time savings and an improvement in efficiency of 0.02%. The speed-up of 50% demonstrated in literature could not be achieved since the high-fidelity model in this work is much cheaper. The best cost ratio achieved in this work is comparable with 0.14, but the correlation coefficient of 0.46 is insufficient. It is shown that at their optimum efficiencies, two selected single-fidelity and multi-fidelity optima have different geometries and aerodynamic behaviour. For improving performance using the multi-fidelity method, it is recommended to increase the fidelity gap between the low-fidelity and the high-fidelity processes. The cost ratio of a new low-fidelity process
can be estimated with an error of at most 5%, by using 10 member designs. Furthermore, the correlation coefficient can be estimated with an error of at worst 35%, using 20 blade designs. From the results in this thesis, it is recommended to employ a cheaper low-fidelity process using for instance through-flow
calculations or to make the high-fidelity process more expensive by adding more design features.