This paper presents the results of research regarding measurements of the values of pressure drops during horizontal flow of gas-liquid and gas-liquid-liquid mixture through 180o pipe bends. The conducted insightful analysis and assessment during multi-phase flow in pipe bends has enabled to develop a new method for determination of their values. This new method for determining pressure drops ensures higher precision of calculation in comparison to other methods presented in literature and can be applied for calculation of these parameters during multi-phase flows in pipe bends with various geometries.
The main topic of this study is the experimental measurement and mathematical modelling of global gas hold-up and bubble size distribution in an aerated stirred vessel using the population balance method. The air-water system consisted of a mixing tank of diameter T = 0.29 m, which was equipped with a six-bladed Rushton turbine. Calculations were performed with CFD software CFX 14.5. Turbulent quantities were predicted using the standard k-ε turbulence model. Coalescence and breakup of bubbles were modelled using the homogeneous MUSIG method with 24 bubble size groups. To achieve a better prediction of the turbulent quantities, simulations were performed with much finer meshes than those that have been adopted so far for bubble size distribution modelling. Several different drag coefficient correlations were implemented in the solver, and their influence on the results was studied. Turbulent drag correction to reduce the bubble slip velocity proved to be essential to achieve agreement of the simulated gas distribution with experiments. To model the disintegration of bubbles, the widely adopted breakup model by Luo & Svendsen was used. However, its applicability was questioned.
The main topic of this study is the mathematical modelling of bubble size distributions in an aerated stirred tank using the population balance method. The air-water system consisted of a fully baffled vessel with a diameter of 0.29 m, which was equipped with a six-bladed Rushton turbine. The secondary phase was introduced through a ring sparger situated under the impeller. Calculations were performed with the CFD software CFX 14.5. The turbulent quantities were predicted using the standard k-ε turbulence model. Coalescence and breakup of bubbles were modelled using the MUSIG method with 24 bubble size groups. For the bubble size distribution modelling, the breakup model by Luo and Svendsen (1996) typically has been used in the past. However, this breakup model was thoroughly reviewed and its practical applicability was questioned. Therefore, three different breakup models by Martínez-Bazán et al. (1999a, b), Lehr et al. (2002) and Alopaeus et al. (2002) were implemented in the CFD solver and applied to the system. The resulting Sauter mean diameters and local bubble size distributions were compared with experimental data.
Gas-liquid flows abound in a great variety of industrial processes. Correct recognition of the regimes of a gasliquid flow is one of the most formidable challenges in multiphase flow measurement. Here we put forward a novel approach to the classification of gas-liquid flow patterns. In this method a flow-pattern map is constructed based on the average energy of intrinsic mode function and the volumetric void fraction of gas-liquid mixture. The intrinsic mode function is extracted from the pressure fluctuation across a bluff body using the empirical mode decomposition technique. Experiments adopting air and water as the working fluids are conducted in the bubble, plug, slug, and annular flow patterns at ambient temperature and atmospheric pressure. Verification tests indicate that the identification rate of the flow-pattern map developed exceeds 90%. This approach is appropriate for the gas-liquid flow pattern identification in practical applications.
To find effective and practical methods to distinguish gas-liquid two-phase flow patterns, new flow pattern maps are established using the differential pressure through a classical Venturi tube. The differential pressure signal was first decomposed adaptively into a series of intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition. Hilbert marginal spectra of the IMFs showed that the flow patterns are related to the amplitude of the pressure fluctuation. The cross-correlation method was employed to sift the characteristic IMF, and then the energy ratio of the characteristic IMF to the raw signal was proposed to construct flow pattern maps with the volumetric void fraction and with the two-phase Reynolds number, respectively. The identification rates of these two maps are verified to be 91.18% and 92.65%. This approach provides a cost-effective solution to the difficult problem of identifying gas-liquid flow patterns in the industrial field.