TURBINE BLADE RELIABILITY-BASED OPTIMIZATION USING A VARIABLE- COMPLEXITY METHOD

This paper investigates the application and implementation of an aircraft engine turbine blade reliability-based optimization (RBO). The turbine blade is designed to be minimum volume while satisfying component reliability-based constraints on displacement and stress. Design variables consist of computer aided design (CAD) shape parameters. Uncertainty is introduced via random variable models of material and load parameters. A sequential qaudratic programming (SQP) technique is used in conjunction with first-order reliability theory to design the blade. State-of-the-art CAD techniques are employed to automate and coordinate the necessary finite element analyses required by the optimization and reliability algorithms. Three RBO constraint evaluation techniques are examined: the mean-value (MV) firstorder reliability method, the Hasofer-Lind RackwitzFiessler first-order reliability method (FORM), and a variable-complexity (VC) approach. Computational costs of the different RBO strategies and a discussion of implementation issues are presented.