Assessment of RANS Turbulence Models in Prediction of the Hydrothermal Plume in the Longqi Hydrothermal Field

Abstract

In this paper, the numerical models are selected to simulate the hydrothermal plume based on the water temperature observation data of the Longqi hydrothermal field in the Southwest Indian Ridge (SWIR). Then, the unsteady Reynolds-averaged Navier–Stokes equations are solved to evaluate the performance of the Realizable k-ε (rke) model and the SST k-ω (sst) model in hydrothermal plume simulation. By comparing the calculated results with the Conductivity Temperature Depth (CTD) observation data and the literature results, the difference in prediction performance between the two models is evaluated. Before the numerical simulation, the optimal mesh parameters are determined by considering the grid independence test. The results show that the relative difference of the maximum plume height calculated by the two models is within 5%. Compared with the CTD 05-2, the rke model calculates the root mean square error of the velocity is 0.5081, which is smaller than that of the sst model. In terms of turbulent viscosity, the rke model is in good agreement with reference value in predicting turbulent viscosity. Therefore, the turbulent viscosity distribution calculated by the rke model is more consistent with the plume development process than that calculated by the sst model. In addition, the two models have the same effect on the prediction of turbulent kinetic energy and plume temperature.

Keywords

• computational fluid dynamics
• models comparison
• southwest Indian ridge
• hydrothermal plume
• turbulent viscosity
• maximum plume rising height