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Accelerated 3D Aerodynamic Optimization of Gas Turbine Blades

[+] Author Affiliations
Philipp Amtsfeld, Michael Lockan, Dieter Bestle

Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany

Marcus Meyer

Rolls-Royce Deutschland Ltd & Co KG, Blankenfelde-Mahlow, Germany

Paper No. GT2014-25618, pp. V02BT39A013; 9 pages
  • ASME Turbo Expo 2014: Turbine Technical Conference and Exposition
  • Volume 2B: Turbomachinery
  • Düsseldorf, Germany, June 16–20, 2014
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4561-5
  • Copyright © 2014 by Rolls-Royce Deutschland Ltd & Co KG


State-of-the-art aerodynamic blade design processes mainly consist of two phases: optimal design of 2D blade sections and then stacking them optimally along a three-dimensional stacking line. Such a quasi-3D approach, however, misses the potential of finding optimal blade designs especially in the presence of strong 3D flow effects. Therefore, in this paper a blade optimization process is demonstrated which uses an integral 3D blade model and 3D CFD analysis to account for three-dimensional flow features. Special emphasis is put on shortening design iterations and reducing design costs in order to obtain a rapid automatic optimization process for fully 3D aerodynamic turbine blade design which can be applied in an early design phase already.

The three-dimensional parametric blade model is determined by up to 80 design variables. At first, the most important design parameters are chosen based on a non-linear sensitivity analysis. The objective of the subsequent optimization process is to maximize isentropic efficiency while fulfilling a minimal set of constraints. The CFD model contains both important geometric features like tip gaps and fillets, and cooling and leakage flows to sufficiently represent real flow conditions.

Two acceleration strategies are used to cut down the turn-around time from weeks to days. Firstly, the aerodynamic multi-stage design evaluation is significantly accelerated with a GPU-based RANS solver running on a multi-GPU workstation. Secondly, a response surface method is used to reduce the number of expensive function evaluations during the optimization process. The feasibility is demonstrated by an application to a blade which is a part of a research rig similar to the high pressure turbine of a small civil jet engine. The proposed approach enables an automatic aerodynamic design of this 3D blade on a single workstation within few days.

Copyright © 2014 by Rolls-Royce Deutschland Ltd & Co KG



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