Session: 36-05 Robust Design and response surface methods (1)

Paper Number: 121977

121977 - Robust Design Optimization of a Compressor Rotor Using Recursive Cokriging Based Multi-Fidelity Uncertainty Quantification and Multi-Fidelity Optimization 

This work focuses on the application of multi-fidelity methods for the robust design optimization of engine components. The robust design optimization approach develops geometric designs that have high efficiencies and are less sensitive to manufacturing and operational uncertainties. However, the uncertainty quantification techniques required to evaluate the robustness are computationally expensive, which limits their use in optimization. Multi-fidelity methods offer a promising solution to reduce the computational cost while maintaining the accuracy in both uncertainty quantification and optimization.

 A Kriging and a multi-fidelity recursive Cokriging framework are developed, implemented, and applied to a test function. In addition, a multi-fidelity super efficient global optimization algorithm is developed. The optimizer is surrogate model-based and can handle constraints. The developed methods are then applied to a compressor test case of a high pressure compressor blade row with 9 uncertainty and 24 design parameters of the geometry. The 2.5 \% quantile of the stage efficiency is used as a robustness measure and it is therefore optimized. Additionally, design bounds and performance constraints are applied. Various uncertainty quantification techniques are analyzed. A multi-fidelity uncertainty quantification approach is developed that combines simplified coarse-grid low-fidelity results with high-fidelity results to reduce the computational cost while maintaining a high accuracy. Uncertainty quantification techniques of three fidelity levels are then developed and used for the multi-fidelity approach in the design space. The robust design optimization of the compressor is performed. The optimal designs obtained from the multi-fidelity approach show superior performance compared to existing robust design optima in the literature.

Presenting Author: Marcus Wiegand Technische Universität Dresden, Institute of Fluid Mechanics, Chair of Turbomachinery and Flight Propulsion

Presenting Author Biography: Marcus Wiegand is a research associate at the Chair of Turbomachinery and Flight Propulsion at Technische Universität Dresden, Germany, since 2023. He holds a Dipl.-Ing. (equivalent to M.S.) degree in Aerospace Engineering from Technische Universität Dresden, Germany, which he received in 2023. He completed his diploma thesis in cooperation with Rolls-Royce Germany.

During his diploma thesis, Marcus Wiegand worked in the field of robust design optimization. Furthermore, his research interests encompass the development of sustainable aircraft propulsion systems, such as hybrid-electric engines, with a special focus on modeling their performance. He is currently working on this as a research associate at Technische Universität Dresden.

Authors:

Marcus Wiegand Technische Universität Dresden, Institute of Fluid Mechanics, Chair of Turbomachinery and Flight Propulsion
Andriy Prots Technische Universität Dresden, Institute of Fluid Mechanics, Chair of Turbomachinery and Flight Propulsion
Marcus Meyer Rolls-Royce Deutschland Ltd & Co KG.
Robin Schmidt Rolls-Royce Deutschland Ltd & Co KG.
Matthias Voigt Technische Universität Dresden, Institute of Fluid Mechanics, Chair of Turbomachinery and Flight Propulsion
Ronald Mailach Technische Universität Dresden, Institute of Fluid Mechanics, Chair of Turbomachinery and Flight Propulsion