Robust Multiphysics Optimization of Fan Blade

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, the fan blade should provide stable aerodynamic efficiency and strength properties. That is why it is considered to solve multidimensional and multidisciplinary optimization task (aerodynamics, strength, and flutter sensitivity) in robust statement under geometrical uncertainties. In the proposed test case, geometrical uncertainties from 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 blades coordinate measurements. Approximately, 2500 fan blades were measured by means CMM process to reconstruct 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. A 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. In the present work, 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 four considered criteria were obtained. Probabilistic criteria were assessed based on the results obtained. Robust optimization results were compared with deterministic optimization results.