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Performance Assessment of CFD Codes in Numerical Modelling of Plunging Jet Aeration

Author(s): M. J. D. Lahiru; P. Mannion; S. Mulligan; S. Felder; M. Kramer; E. Clifford

Linked Author(s): Matthias Kramer, Sean Mulligan, Stefan Felder

Keywords: Computational Fluid Dynamics; Plunging jet aeration; Multiphase flows; Air-entrainment

Abstract: Air entrainment is an area of increasing focus across various engineering applications and industrial processes. Plunging jet systems are a classic example of air bubble entrainment, whereby atmospheric air is “dragged” along with the free jet flow, generating a bubbly flow upon impingement on a receiving liquid pool. A better understanding of this complex multi-phase flow interaction is of fundamental importance in engineering, for example, in optimizing the efficiency of energy usage in aeration tanks. In recent years, numerical analysis methods emerged as viable and widely used methods for investigating such complex fluid dynamics scenarios. There are several CFD (computational fluid dynamics) platforms suitable for such cases, which can be categorized into commercial platforms (Ansys Fluent, Flow 3D) and open-source codes (OpenFOAM, Fluidity). In this study, the modelling capabilities of two well-established CFD software packages (Ansys Fluent and OpenFOAM) were compared for their efficacy in modelling air cavity formation in plunging liquid jets. The non dimensional ratios of the initial air cavity geometrical parameter with the plunging jet diameter were compared in both software codes and with previous experimental results. The results showed that both the Ansys FLUENT and OpenFOAM simulations overpredicted the geometrical ratios relative to the experimental results. This study identifies a number of ways that these differences can be reduced in future studies. This comparison will aid engineers and researchers by providing novel insights into the use of different CFD codes in the modelling of air entrainment in complex multiphase flows, such as in wastewater applications, and suggest improvements to experimental methods that may aid model calibration.

DOI: 10.3929/ethz-b-000727195

Year: 2024

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