Probabilistic HCF-Investigation of Compressor Blades

During the design process of compressor blades predominantly deterministic models are used for High Cycle Fatigue (HCF) strength investigations. The scatter of HCF that results e.g. through abrasion of the production machines [1] or inhomogeneities of the blade material, is accounted by safety factors and conservative assumptions. A more realistic approach to consider these uncertainties is the application of probabilistic methods. Therefore, further information about HCF and eigenfrequency scatter of the really produced blades can be used for a robust design during the design process. Within a measurement campaign 400 blades of a Rolls-Royce High Pressure Compressor were randomly selected and scanned using an automated process that applies the optical measurement technique of strip projection. The measurement data of the airfoil were subdivided into constant spanwise profile slices. Geometric airfoil parameters were determined on each of the profile slices [2]. Due to the large number of scanned blades each geometric airfoil parameter can be described as a distribution function with corresponding parameters. These distribution functions are the input parameters for the probabilistic investigation — the Monte-Carlo-Simulation (MCS). Within the MCS an automatically transfer process varies at first the profile slices of a CAD-airfoil and in a second step morphs an existent 3D finite element mesh applying the meshmorphing tool of the FE preprocessor Hypermesh. The HCF and eigenfrequency scatter of all blades were calculated with the interpretation of the MCS results and parameters were detected with the largest influence on HCF-strength and eigenfrequencies. A detailed interpretation of the HCF-strength at one example shows the power of the probabilistic investigation. The interpretation helps the engineer to understand the entire system and to design a robust blade.Copyright © 2009 by Rolls-Royce Deutschland Ltd. & Co. KG