The former can be directly resolved, while the latter is computed using the SGS model. In the LES approach, the whole eddy range is separated into two parts, namely, the large-scale eddy and subgrid-scale (SGS) eddy. However, this approach suffers from several weaknesses, e.g., compromised accuracy and uncertainties due to assumptions in the model construction and insufficient incorporation of the fluid physics. Among these numerical methods, the RANS approach, specifically the Eddy Viscosity Model (EVM), is widely used for calculating turbulent flows thanks to its relatively high accuracy in predicting the mean flow features and its more limited computational demands. Many numerical approaches for solving turbulence have been proposed, such as the Reynolds-Averaged Navier–Stokes (RANS), the Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS) approaches. Turbulent flow can be numerically resolved with different levels of accuracy. Some future perspectives for the simulation of turbulent flow are formulated. Subsequently, the application of a turbulence model for three specific flow problems commonly encountered in metallurgical process, i.e., bubble-induced turbulence, supersonic jet transport, and electromagnetic suppression of turbulence, is discussed. An emphasis is placed on the model validation through physical experimentation. The consistency between physical experimentation/modelling and industrial cases is discussed. Different experimental techniques for model validation are given. Application and limitation of the DNS model are described. Special attention is paid to the inflow boundary condition for LES modelling. The progress of LES with different subgrid scale models is presented. The advantage and disadvantage of RANS models to characterize turbulent flows are discussed. The formulation and variation of different RANS methods are evaluated. This paper focusses on three main numerical methods, i.e., the Reynolds-Averaged Navier-Stokes (RANS), Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS) methods.
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