This effort focuses on the comparison of unsteadiness due to as-measured turbine blades in a transonic turbine to that obtained with blueprint geometries via computational fluid dynamics (CFD). A Reynolds-averaged Navier–Stokes flow solver with the two-equation Wilcox turbulence model is used as the numerical analysis tool for comparison between the blueprint geometries and as-manufactured geometries obtained from a structured light optical measurement system. The nominal turbine CFD grid data defined for analysis of the blueprint blade were geometrically modified to reflect as-manufactured turbine blades using an established mesh metamorphosis algorithm. The approach uses a modified neural network to iteratively update the source mesh to the target mesh. In this case, the source is the interior CFD surface grid while the target is the surface blade geometry obtained from the optical scanner. Nodes interior to the CFD surface were updated using a modified iterative spring analogy to avoid grid corruption when matching as-manufactured part geometry. This approach avoids the tedious manual approach of regenerating the CFD grid and does not rely on geometry obtained from coordinate measurement machine (CMM) sections, but rather a point cloud representing the entirety of the turbine blade. Surface pressure traces and the discrete Fourier transforms (DFT) thereof from numerical predictions of as-measured geometries are then compared both to blueprint predictions and to experimental measurements. The importance of incorporating as-measured geometries in analyses to explain deviations between numerical predictions of blueprint geometries and experimental results is readily apparent. Further analysis of every casting produced in the creation of the test turbine yields variations that one can expect in both aero-performance and unsteady loading as a consequence of manufacturing tolerances. Finally, the use of measured airfoil geometries to reduce the unsteady load on a target blade in a region of interest is successfully demonstrated.

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