Optimizing Gas Turbine Performance Using the Surrogate Management Framework and High-Fidelity Flow Modeling

Nikita Kozak, Manoj R. Rajanna, Michael C. H. Wu, Muthuvel Murugan, Luis Bravo, Anindya Ghoshal, Ming-Chen Hsu and Yuri Bazilevs
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Nikita Kozak: Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA
Manoj R. Rajanna: Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA
Michael C. H. Wu: School of Engineering, Brown University, Providence, RI 02912, USA
Muthuvel Murugan: U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005, USA
Luis Bravo: U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005, USA
Anindya Ghoshal: U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005, USA
Ming-Chen Hsu: Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA
Yuri Bazilevs: School of Engineering, Brown University, Providence, RI 02912, USA

Energies, 2020, vol. 13, issue 17, 1-16

Abstract: This work couples high-fidelity moving-domain finite element compressible flow modeling with a Surrogate Management Framework (SMF) for optimization to effectively design a variable speed gas turbine stage. The superior accuracy of high-fidelity modeling, however, comes with relatively high computational costs, which are further amplified in the iterative design process that relies on parametric sweeps. An innovative approach is developed to reduce the number of iterations needed for optimal design, leading to a significant reduction in the computational cost without sacrificing the high fidelity of the analysis. The proposed design optimization approach is applied to a novel incidence-tolerant turbomachinery blade technology that articulates the stator- and rotor-blade positions of an annular single-stage high pressure turbine to achieve peak performance. This work also extends our understanding of rotor–stator interactions by simulating complex internal flows occurring during multi-speed turbine operation. Potential variable-speed gas turbine stage designs and the proposed optimization approach are presented to provide valuable insight into this new turbomachinery technology that can positively impact future propulsion systems.

Keywords: compressible flow; stabilized and multiscale FEM; surrogate management framework; design optimization; gas turbine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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