Automated Multidisciplinary Optimization of a Transonic Axial Compressor

Abstract

The current paper describes DLR’s optimizer AutoOpti, the implementation of the metamodel “Kriging” as accelerating technique, and the process chain in the automated, multidisciplinary optimization of fans and compressors on basis of a recent full stage optimization of a highly loaded, transonic axial compressor. Methods and strategies for an aerodynamic performance map optimization coupled with a finite element analysis on the structural side are presented. The high number of 231 free design parameters, a very limited number of CFD simulations, and conflicting demands both within the aerodynamic requirements and between the disciplines are a challenging optimization task. To navigate such a multi-dimensional search space, metamodels have successfully been used as accelerating technique. Using four aerodynamic operating points at two rotational speeds allows adjusting a required stability margin and optimizing the working line performance under this constraint. The investigated compressor concept is a highly loaded transonic stage with a single row rotor and a tandem stator, designed for a very high total pressure ratio. A. Introduction ompressors for aircraft engines are constantly developed towards higher aerodynamic loading to reduce the installation length, weight, and number of parts with no degradation in efficiency. This leads to more complex geometries and consequently to more complex flow structures. An automated optimization approach is to be preferred in order to take advantage of new design freedoms, while reducing or at least maintaining development time. Automated optimization is also suggested by recent progress in simulation technologies in several fields such as steady and unsteady computational fluid dynamics (CFD), structural and thermal finite element analysis (FEM). Moreover, processors have become increasingly powerful, and parallel computing on huge clusters can be considered state of the art technology for CFD and FEM applications. Thus, it has become possible to employ optimization methods in the design of various parts of heavy duty gas turbines and aircraft engines, even when calculations require large computational resources.