Hydrodynamics of Ionic Liquids in Bubble Columns

Lange, Vicky; Azzopardi, B.J.; Licence, Pete

doi:10.5772/51658

Cited by 4 publications

(4 citation statements)

References 34 publications

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“…The relationship between the voltage output and the liquid hold up is usually nonlinear and requires an off-line calibration. The voltage output from each conductance probe at each measurement point was normalized using the maximum voltage output of each probe when the pipe is fully filled with water (slug body section) to produce a dimensionless value in the same way as the conductance probe was calibrated off-line to account for temperature variations during the experiments [33].…”

Section: Methodsmentioning

confidence: 99%

Two-Phase Air–Water Slug Flow Measurement in Horizontal Pipe Using Conductance Probes and Neural Network

Fan

Yan

2014

IEEE Trans. Instrum. Meas.

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This paper presents a method to obtain gas and liquid flow rates of two-phase air-water slug flow in a horizontal pipe through conductance probes and neural network. Contrary to statistical features commonly used in other works, five characteristic parameters of the mechanistic slug flow model are extracted from conductance signals, i.e., translational velocity, slug holdup, film holdup, slug length, and film length, which are used as the neural network inputs. The translational velocity is obtained through cross correlation of signals from the two ring-type conductance probes that are placed apart at a fixed distance. A feedforward neural network is adopted to correlate the characteristic parameters of slug flow and the gas and liquid flow rates and further used as a prediction tool. The experimental results show that the neural network method is able to learn the implicit correlations between the characteristic parameters of slug flow and the corresponding gas and liquid flow rates. It provides a performance for measurement of gas and liquid flow rates in slug flow regime within ±10% of full scale.Index Terms-Conductance probe, cross correlation, gas flow rate, liquid flow rate, liquid holdup, neural network, slug flow.

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Section: Methodsmentioning

confidence: 99%

Two-Phase Air–Water Slug Flow Measurement in Horizontal Pipe Using Conductance Probes and Neural Network

Fan

Yan

2014

IEEE Trans. Instrum. Meas.

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“…This behavior was interpreted by Besagni and co-authors using the "dual effect of viscosity over the flow regime transition" [11] concept: (a) "moderate/high viscosities" stabilize the homogeneous flow regime, owing to increased coalescence [3,11,56] and the presence of cap-bubbles [11] (as experimentally observed by Wikinson et al [56] and more recently, by Yang et al [57]); (b) "low viscosities" stabilize the homogeneous flow regime, as the reduced coalescence increases the number of small bubbles; For example, Besagni et al [11] (Figure 9a,b) found that µ L , depending on its value, either stabilizes or destabilizes the homogeneous flow regime compared to air-water systems (The Mono-Ethylene Glycol, MEG, concentration, c MEG = 0%: U G,trans = 0.0264 m/s, ε G,trans = 0.09; c MEG = 5%: U G,trans = 0.039 m/s, ε G,trans = 0.18; c MEG = 80%: U G,trans = 0.023 m/s, ε G,trans = 0.07). It is worth noting that the increased coalescence may also suppress the homogeneous flow regime and, for µ L > 8 mPa·s, it may not exist even with a 'fine gas sparger' [8,[58][59][60].…”

Section: Influence Of the Liquid Phase Viscositymentioning

confidence: 99%

“…Generally speaking, high viscous media are characterized by more stable interfaces and thus, promote the formation of large bubbles at the gas sparger [3,259], bubble coalescence [3,56,58,59] and decreases in the bubble breakup rate [24,56]. Viscous liquid phases also change the nucleation process [260] as the bubble detachment in viscous liquid phase ins mainly determined by the viscous forces, rather than the inertial and surface tension forces [261].…”

Section: Influence Of the Liquid Properties Viscous Mediamentioning

confidence: 99%

Two-Phase Bubble Columns: A Comprehensive Review

2018

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We present a comprehensive literature review on the two-phase bubble column; in this review we deeply analyze the flow regimes, the flow regime transitions, the local and global fluid dynamics parameters, and the mass transfer phenomena. First, we discuss the flow regimes, the flow regime transitions, the local and global fluid dynamics parameters, and the mass transfer. We also discuss how the operating parameters (i.e., pressure, temperature, and gas and liquid flow rates), the operating modes (i.e., the co-current, the counter-current and the batch modes), the liquid and gas phase properties, and the design parameters (i.e., gas sparger design, column diameter and aspect ratio) influence the flow regime transitions and the fluid dynamics parameters. Secondly, we present the experimental techniques for studying the global and local fluid dynamic properties. Finally, we present the modeling approaches to study the global and local bubble column fluid dynamics, and we outline the major issues to be solved in future studies.

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“…In a highly viscous liquid, the bubble surface is more stable, larger bubbles form at the injector, 31,32 and the coalescence rate is larger than the breakage rate. 2,[33][34][35] The study of bubble size distribution shows that in viscous liquids the probability density function (PDF) of the BSD exhibits a bimodal shape. 15,21,36,37 In the bubble column literature, scaling of the characteristic bubble length has been broadly approached assuming the sizing is dominated by either a breakage mechanism 38 or bubble formation.…”

Section: Introductionmentioning

confidence: 99%

Effect of operation regime on bubble size and void fraction in a bubble column with porous sparger

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Performance of bubble columns under transport processes is dependent on bubble size distribution and void fraction. These multiphase parameters are sensitive to the operation regime of a bubble column. The current work presents a systematic study of bubble size and void fraction in a batch bubble column within the homogeneous and heterogeneous regimes. Effect of liquid viscosity and gas superficial velocity on bubble size distribution, void fraction, and operation regime was investigated. Results showed that increasing the viscosity accelerates the regime transition. Bubble size distributions were statistically characterized using probability density function and probability plots. It was shown that bubble size distribution shifts from near-Gaussian in the homogenous regime to lognormal (in parts) in the heterogeneous regime. Dimensional reasoning was used to scale the bubble size and void fraction with respect to the operation regime.

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Hydrodynamics of Ionic Liquids in Bubble Columns

Cited by 4 publications

References 34 publications

Two-Phase Air–Water Slug Flow Measurement in Horizontal Pipe Using Conductance Probes and Neural Network

Two-Phase Air–Water Slug Flow Measurement in Horizontal Pipe Using Conductance Probes and Neural Network

Two-Phase Bubble Columns: A Comprehensive Review

Effect of operation regime on bubble size and void fraction in a bubble column with porous sparger

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