A fan blade is a complicated object and obviously it is subjected to geometrical uncertainties from manufacture tolerances and other production deviations. In spite of all uncertainties a fan blade should provide stable aerodynamic efficiency and strength properties. That is why it is considered to solve a multidimensional and multidisciplinary optimization task (aerodynamics, strength and flutter sensitivity) in robust statement under geometrical uncertainties. In the proposed test case geometrical uncertainties from the fan blade manufacture tolerances and deviations are considered. The probability density function (pdf) was obtained as a result of statistical operation upon the results of blade coordinate measurements. Approximately 2500 fan blades were measured by means of CMM process to reconstruct the pdf for more than 40 geometrical uncertainties (there are blade thicknesses for different airfoil locations in several cross-sections). CFD and FEM calculations were carried out in NUMECA FINE/Turbo and ANSYS software, correspondingly.

The surrogate model technique (the response surface and the Monte-Carlo method implemented to RSM results) was applied for the uncertainty quantification and the robust optimization process for the task under consideration. APPROX software was used for surrogate model construction. The IOSO technology was employed as one of the robust optimization tools. This technology is also based on a widespread application of the response surface technique.

As a result, robust optimal solutions (the Pareto set) for all 4 considered criteria (aerodynamic efficiency, structural properties, stall margin and flutter sensitivity) were obtained. The probabilistic criteria were assessed based on the results obtained. The robust optimization results were compared with the deterministic optimization results.

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