Massively Parallel Large Eddy Simulation of Rotating Turbomachinery for Variable Speed Gas Turbine Engine Operation †

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2020-02-06

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Jain, N.; Bravo, L.; Kim, D.; Murugan, M.; Ghoshal, A.; Ham, F.; Flatau, A. Massively Parallel Large Eddy Simulation of Rotating Turbomachinery for Variable Speed Gas Turbine Engine Operation. Energies 2020, 13, 703.

Abstract

Gas turbine engines are required to operate at both design and off-design conditions that can lead to strongly unsteady flow-fields and aerodynamic losses severely impacting performance. Addressing this problem requires effective use of computational fluid dynamics tools and emerging models that resolve the large scale fields in detail while accurately modeling the under-resolved scale dynamics. The objective of the current study is to conduct massively parallel large eddy simulations (LES) of rotating turbomachinery that handle the near-wall dynamics using accurate wall models at relevant operating conditions. The finite volume compressible CharLES solver was employed to conduct the simulations over moving grids generated through Voronoi-based unstructured cells. A grid sensitivity analysis was carried out first to establish reliable parameters and assess the quality of the results. LES simulations were then conducted to understand the impact of blade tip clearance and operating conditions on the stage performance. Variations in tip clearance of 3% and 16% chord were considered in the analysis. Other design points included operation at 100% rotor speed and off-design conditions at 75% and 50% of the rotor speed. The simulation results showed that the adiabatic efficiency improves dramatically with reduction in tip gap due to the decrease in tip leakage flow and the resulting flow structures. The analysis also showed that the internal flow becomes highly unsteady, undergoing massive separation, as the rotor speed deviates from the design point. This study demonstrates the capability of the framework to simulate highly turbulent unsteady flows in a rotating turbomachinery environment. The results provide much needed insight and massive data to investigate novel design concepts for the US Army Future Vertical Lift program.

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