RANS-Based Modelling of Turbulent Flow in Submarine Pipe Bends: Effect of Computational Mesh and Turbulence Modelling

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Abstract
Pipe bend is a critical integral component, widely used in slurry pipeline systems involving various engineering applications, including natural gas hydrate production. The aim of this study is to assess the capability of RANS-based CFD models to capture the main features of the turbulent single-phase flow in pipe bends, in view of the future investigation of the hydrate slurry flow in the same geometry. This is different from the available literature in which only a few accounted for the effects of a combination of computational mesh, turbulence model, and near-wall treatment approach. In this study, three types of mesh configuration were adopted to carry out the computations, namely unstructured mesh and two structured meshes with a uniform and nonuniform inflation layer, respectively. To explore the influence of the turbulence model, standard k-ε, low-Reynolds k-ε, and nonlinear eddy viscosity turbulence model were selected to close RANS equations. Pressure coefficient, mean axial velocity, turbulence intensity, secondary flow velocity, and magnitude of secondary flow were regarded as the critical variables to make a comprehensive sensitivity analysis. Predicted results suggest that turbulent kinetic energy is the most sensitive variable to the computational mesh while others tend to stabilize. The largest difference of turbulence kinetic energy was around 26% between unstructured mesh and structured mesh with a nonuniform inflation layer. Additionally, a fully resolved boundary layer can reduce the sensitivity of mesh on turbulent kinetic energy, especially for a nonlinear turbulence model. However, the large gradient and peak value of turbulence intensity near the inner wall of the bend was not captured by the case with a fully resolved boundary layer, compared with that of the wall function used. Furthermore, it has been confirmed that the same rule was detected also for different curvature ratios, Reynolds numbers, and dimensionless wall distance y+.
Funding Information
  • National Natural Science Foundation of China (41572247, 42077237, ZR2020MD110)
  • Natural Science Foundation of Shandong Province (41572247, 42077237, ZR2020MD110)

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