Abstract
The rotating stall generated by the centrifugal pump impeller reduces efficiency and causes severe flow fluctuations and noise due to surging. In the present work, the six-bladed impeller in the centrifugal pump was simulated by RANS, LES, and Hybrid RANS/LES turbulence models using ANSYS CFX. The turbulence models considered were the Shear Stress Transport (SST), Detached Eddy Simulation (DES), Stress-Blended Eddy Simulation (SBES), Scale Adaptive Simulation (SAS), and Wall-Adapted Local Eddy-viscosity (WALE). The design load condition and the quarter-load condition were applied for the boundary conditions, and the experimental results were compared and analyzed using velocity profile and turbulent kinetic energy at the impeller mid-height. Under the design load condition, all turbulence models predicted results similar to the experimental results. In the off-design load condition, LES predicted the experimental value most accurately, followed by SST-RM of RANS with high accuracy, and the hybrid RANS/LES model showing lower prediction accuracy; SBES predicted excessive recirculation flow. However, if sufficient grid resolution is achieved, hybrid RANS/LES model can simulate the rotating stall under the off-design flow condition than RANS models. Both DES and SAS model show relatively low mesh dependent results with acceptable accuracy.
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Acknowledgements
This research is supported by the Nuclear Safety Research Program through the Korea Foundation of Nuclear Safety (KOFONS) using the financial resource granted by the Nuclear Safety and Security Commission (NSSC) of the Republic of Korea (No. 1805007) and by Korea Institute of Energy Technology Evaluation and Planning (KETEP) Grant funded by the Korea government (MOTIE) (20224000000440)
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Park, S.H., Lee, G.H., Kim, D. et al. Assessment of the predictive capabilities of various turbulence models for the simulation of rotating stall in the centrifugal pump impeller. J Vis (2024). https://doi.org/10.1007/s12650-024-00998-8
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DOI: https://doi.org/10.1007/s12650-024-00998-8