Numerical simulation of bubble characteristics in bubble columns with different liquid viscosities and surface tensions using a CFD-PBM coupled model

Ping, Yan; Jin, Haibo; He, Guangping; Guo, Xiaoyan; Ma, Lu‐Fang; Yang, Suohe; Zhang, Rongyue

doi:10.1016/j.cherd.2019.11.030

Cited by 31 publications

(30 citation statements)

References 48 publications

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“…The Eulerian–Eulerian two-phase model was utilized in this work with the two-equation standard turbulence model. In this fluid modeling approach, the following equations are derived for each phase inside the reactor 12 : Continuity equation of phase k : Momentum equation of phase k : …”

Section: Methodsmentioning

confidence: 99%

“…gas and liquid. CFD simulations have been utilized in various studies [12][13][14] to assess these types of reactors containing water and air systems. Due to the presence of two phases inside the reactor and interaction between them, almost all studies considered the Eulerian CFD model and just the mass transfer in the reactor both internally and between phases 7,[15][16][17] .…”

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confidence: 99%

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Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow

Babanezhad

Behroyan

Nakhjiri

et al. 2021

Sci Rep

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Herein, a reactor of bubble column type with non-equilibrium thermal condition between air and water is mechanistically modeled and simulated by the CFD technique. Moreover, the combination of the adaptive network (AN) trainer with the fuzzy inference system (FIS) as the artificial intelligence method calling ANFIS has already shown potential in the optimization of CFD approach. Although the artificial intelligence method of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) has a good background for optimizing the other fields of research, there are not any investigations on the cooperation of this method with the CFD. The PSOFIS can reduce all the difficulties and simplify the investigation by elimination of the additional CFD simulations. In fact, after achieving the best intelligence, all the predictions can be done by the PSOFIS instead of the massive computational efforts needed for CFD modeling. The first aim of this study is to develop the PSOFIS for use in the CFD approach application. The second one is to make a comparison between the PSOFIS and ANFIS for the accurate prediction of the CFD results. In the present study, the CFD data are learned by the PSOFIS for prediction of the water velocity inside the bubble column. The values of input numbers, swarm sizes, and inertia weights are investigated for the best intelligence. Once the best intelligence is achieved, there is no need to mesh refinement in the CFD domain. The mesh density can be increased, and the newer predictions can be done in an easier way by the PSOFIS with much less computational efforts. For a strong verification, the results of the PSOFIS in the prediction of the liquid velocity are compared with those of the ANFIS. It was shown that for the same fuzzy set parameters, the PSOFIS predictions are closer to the CFD in comparison with the ANFIS. The regression number (R) of the PSOFIS (0.98) was a little more than that of the ANFIS (0.97). The PSOFIS showed a powerful potential in mesh density increment from 9477 to 774,468 and accurate predictions for the new nodes independent of the CFD modeling.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow

Babanezhad

Behroyan

Nakhjiri

et al. 2021

Sci Rep

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“…Liquid properties, [ 6 ] such as density, viscosity, surface tension, specific heat capacity, and electrical conductivity, are among the critical parameters that affect gas holdup and bubble size distribution in bubble columns. Several research studies have investigated the effect of liquid viscosity on bubble behaviour.…”

Section: Introductionmentioning

confidence: 99%

Effect of pressure on the hydrodynamics of a pilot‐scale bubble column operating with low and moderate viscosity Newtonian liquids

et al. 2021

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In a pilot‐scale bubble column operating with low and moderate viscosity hydrocarbons, the effect of pressure on the total and axial gas holdup as well as the regime transition velocity was investigated. Experiments were performed for two air‐Ketrul D100 and air‐Hydroseal G250 HL gas‐liquid hydrocarbon systems. It was found that increasing pressure increased gas holdup at the heterogeneous regime, and this effect was more pronounced for the low‐viscosity liquid. Moreover, increasing pressure further stabilized the homogeneous regime, and again, this stabilizing effect was more significant for the low‐viscosity liquid. Also, as a response to the pressure increasing, the axial gas holdup became more uniform in the case of the low‐viscosity liquid and less uniform in the case of the moderate‐viscosity liquid.

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“…Yan et al [14] investigated the effect of liquid properties on fluid dynamic parameters in bubble columns. In particular, they used the correction of surface tension and viscosity to highlight the influence of different liquid properties on the hydrodynamic parameters of bubble columns.…”

Section: Introductionmentioning

confidence: 99%

Semi-Analytical Model for Heat and Mass Transfer Evaluation of Vapor Bubbling

2020

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Multi-stage refrigeration systems cover a wide range of possibilities and are diffusing more and more. The idea that inspired this work derived from the need to have a tool to model the energy behavior of the intercooler inside a multi-stage refrigeration system. In this work, a semi-analytical model of a single bubble, injected into the liquid of an intercooler of a multi-stage system, has been developed. The developed model is a set of equations derived from the Fourier equation for heat conduction in defined conditions and includes the effects of sensible and latent heat. The vapor bubble is supposed to be injected in the saturated liquid contained in a tank at a defined depth, at an intermediate pressure. The model has been implemented in Matlab and the results show the influence of the liquid surface tension, the injection depth and the thermal diffusivity of the vapor. The model developed here is a useful low-cost tool for evaluating heat transfer optimization of a separator/intercooler of a multi-stage refrigeration system.

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Numerical simulation of bubble characteristics in bubble columns with different liquid viscosities and surface tensions using a CFD-PBM coupled model

Cited by 31 publications

References 48 publications

Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow

Investigation on performance of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) in a combination of CFD modeling for prediction of fluid flow

Effect of pressure on the hydrodynamics of a pilot‐scale bubble column operating with low and moderate viscosity Newtonian liquids

Semi-Analytical Model for Heat and Mass Transfer Evaluation of Vapor Bubbling

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