Abstract:A machine learning (ML) approach is developed to predict effects of blend repairs on airfoil frequency, modal assurance criterion (MAC), and modal displacement. The method is demonstrated on a transonic compressor rotor airfoil. A parametric blend geometry is developed that encompassing a large range of blend geometries. This repair geometry is used to modify the airfoil surface definition and a mesh morphing process transforms the nominal finite element model to the repaired configuration. A multi-level full … Show more
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