Effects of Turbulence Models on Flow Characteristics of a Vertical Fire Pump

Osman, F. K.; Zhang, J.; Lai, L.; Kwarteng, A. A.

doi:10.47176/jafm.15.06.1303

Effects of Turbulence Models on Flow Characteristics of a Vertical Fire Pump

Document Type : Regular Article

Authors

¹ National Research Center of Pumps, Jiangsu University, Zhenjiang, 212013, China

² Department of Mechanical Engineering, University of Mines and Technology, Tarkwa, Ghana

10.47176/jafm.15.06.1303

Abstract

The flow in the vertical long-axis fire pump exhibits complex, three-dimensional, unsteady flow features. In an attempt to understand the effects of turbulence models on the flow mechanism and performance characteristics of the pump, the ANSYS CFX software was used to carry out numerical studies on the vertical fire pump using URANS. The main objective of this study was to investigate the unsteady flow dynamics within the vertical fire pump and the influence of applying different computational turbulence models. The study then sought to conduct a brief analysis of the unsteady pressure pulsation characteristics of the pump. The reliability of the CFD model was validated with an external characteristic test. The transient pressure distribution, velocity field and external characteristics were analyzed. The results were compared to experimental results, where it was revealed that the SST k-ω model showed 1.82% and 0.81% improvements in efficiency and head, respectively, over the k-ε models. In terms of the power performance, however, the standard k-ε is less likely to over-predict the power used by the pump in overload conditions as compared to the other turbulence models. The pressure charts did not show significant reactions to varying turbulence models across all the studied flow rates. However, the velocity streamlines revealed that there were several disruptions in streamwise flow, where both the standard and RNG k-ε models exhibited more recirculation areas than the SST k-ω and standard k-ω models. Overall, for this type of application, SST k-ω was the best-performing turbulence model, while RNG k-ε showed the poorest performance. Nonetheless, the RNG k-ε also has its strengths. This investigation would serve as a theoretical reference for further research and development in fluid machinery.

Keywords

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