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Numerical Investigations of a High Pressure Compressor Exposed to Unsteady Pressure Gain Combustion Employing Data-Driven Methods
Zitatschlüssel 2021_bicalho_asme
Autor Bicalho Civinelli de Almeida, V. and Peitsch, D.
Seiten GT2021-58852
Jahr 2021
ISBN 978-0-7918-8493-5
DOI 10.1115/GT2021-58852
Ort Virtual Conference, Online
Journal ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition
Jahrgang Volume 2D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery
Monat 06
Notiz V02DT39A002,
Technische Universität Berlin:
V. Bicalho Civinelli de Almeida, D. Peitsch
Herausgeber ASME
Serie Turbo Expo: Power for Land, Sea, and Air
Zusammenfassung Pressure gain combustion (PGC) should substantially improve the thermodynamic efficiency of gas turbines by increasing the fluid total pressure as it traverses the combustion chamber. However, PGC introduces additional unsteadiness to the intrinsically complex turbomachinery flow. A high pressure compressor, located right upstream of the PGC section, is therefore constantly exposed to flow fluctuations, experiencing drop in efficiency, increase in pressure loss as well as higher stalling and structural failure risks. This numerical work analyzes how one stage of a well-established engine, namely the NASA EEE core compressor, reacts to the disturbances induced by the potential implementation of PGC. Unsteady computational fluid dynamics are employed with boundary conditions simulating the combustion unsteadiness.The main focus of the current paper is the application of data-driven methods, including the proper orthogonal decomposition (POD) and the dynamic mode decomposition (DMD), when comparing the high pressure compressor baseline operation with the PGC-disturbed case. Representative flow features and their frequency content, not identifiable with typical methods such as phase-averaging, are easily extracted from snapshots sequences. The results not only allow the identification of the most relevant coherent structures present in the unsteady flow, but also show how they change in the presence of PGC. This contribution sheds light on how novel PGC technology can be integrated with turbomachinery components, identifying modifications in the main flow features with the use of advanced decomposition techniques.
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