Flow Regime Identification in a Bubble Column Based on both Kolmogorov Entropy and Quality of Mixedness Derived from CAERPT Data

Nedeltchev, Stoyan; Kumar, Sailesh B.; Duduković, Milorad P.

doi:10.1002/cjce.5450810305

Cited by 36 publications

(29 citation statements)

References 60 publications

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“…These methods are based on the analysis of ε G data. Other flow regime identification methods are the fractal [319], wavelet [320,321], Hurst's [322,323], spectral and nonlinear chaos [93,320,[324][325][326][327][328][329][330][331][332][333] and Kolmogorov entropy [332][333][334] approaches. Some authors have used methods based on the Shannon entropy, which measures the degree of indeterminacy in a system [335,336].…”

Section: The Flow Regimesmentioning

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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Section: The Flow Regimesmentioning

confidence: 99%

Two-Phase Bubble Columns: A Comprehensive Review

2018

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“…This chaotic parameter takes different values under the different flow regimes and this fact should be taken into account in every theoretical model. Nedeltchev et al [19] developed models for the prediction of the KE values derived from CARPT data obtained in both bubbly and transition flow regimes. Nedeltchev [25] modeled the KE values derived from pressure fluctuations measured under the fully developed churn-turbulent regime.…”

Section: Kolmogorov Entropy (Ke) Prediction In the First Transition Rmentioning

confidence: 99%

“…For instance, chaos analysis was applied to gas holdup fluctuations [9], pressure fluctuation time series [13][14][15][16][17], Computer-Automated Radioactive Particle Tracking (CARPT) data [18,19], bubbling frequency [20], etc. All of these studies demonstrated that the chaos methodology can provide us with important insights into the complex hydrodynamics of gas-liquid bubble columns.…”

Section: Introductionmentioning

confidence: 99%

Prediction of The Kolmogorov Entropy Derived from CT Data in a Bubble Column Operated under The Transition Regime and Ambient Pressure

2007

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The Kolmogorov entropy (KE) algorithm was successfully applied to single source γ‐ray Computed Tomography (CT) data measured by three scintillation detectors in a 0.162 m‐ID bubble column equipped with a perforated plate distributor (163 holes × ∅︁ 1.32 · 10–3 m). The aerated liquid height was set at 1.8 m. Dried air was used as a gas phase, while Therminol LT (ρL = 886 kg m–3, μL = 0.88 · 10–3 Pa s, σ = 17 · 10–3 N m–1) was used as a liquid phase. At ambient pressure, the superficial gas velocity, uG, was increased stepwise with an increment of 0.01 m s–1 up to 0.2 m s–1. Based on the sudden changes in the KE values, the boundaries of the following five regimes were successfully identified: dispersed bubble regime (uG < 0.02 m s–1), first transition regime (0.02 ≤ uG < 0.08 m s–1), second transition regime (0.08 ≤ uG < 0.1 m s–1), coalesced bubble regime consisting of four regions (called 4‐region flow; 0.1 ≤ uG < 0.12 m s–1), and coalesced bubble regime consisting of three regions (called 3‐region flow; uG > 0.12 m s–1). The KE values derived from three scintillation detectors in the first transition regime were successfully correlated to both bubble frequency and bubble impact. The latter was found to be inversely proportional to the bubble Froude number. The KE model implies that the bubble size in this particular flow regime is a weak function of the orifice Reynolds number (db = 7.1 · 10–3Re0–0.05).

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“…Nonlinear chaos analysis is a powerful diagnostic tool for flow regime identification. It has already been found that the bubbling process exhibits a chaotic behavior [7,[10][11][12][13]. Nonlinear chaos analysis is invaluable for enhancing the physical understanding of the complex bubble column hydrodynamics.…”

Section: Kolmogorov Entropymentioning

confidence: 99%

“…The number of elements in each state vector is equal to the embedding dimension. Following Letzel et al [10] and Nedeltchev et al [1,13], the embedding dimension was set to 50. The maximum interpoint distance (cut-off length) was set equal to four times the average absolute deviation from the data average.…”

Section: Kolmogorov Entropymentioning

confidence: 99%

Identification of Various Transition Velocities in a Bubble Column Based on Kolmogorov Entropy

et al. 2007

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The Kolmogorov entropy (KE) algorithm was applied successfully to gas holdup fluctuations measured in a 0.102 m I.D. stainless steel bubble column equipped with a perforated plate distributor (19 holes˘1 mm). Nitrogen was used as the gas, while both 1-butanol and gasoline were used as liquids. 1-Butanol was aerated at pressures, P = 0.1 and 0.5 MPa, whereas gasoline was aerated at P = 0.1 and 0.2 MPa. Based on the peaks in the KE values under the pressures examined in both liquids, the boundaries of the following five regimes were identified: bubbly flow, first transition, second transition, coalesced bubble (4-region flow) and coalesced bubble (3-region flow). As the pressure increases to P = 0.5 MPa in 1-butanol, all four transition velocities shift to higher superficial gas velocity, u G . In addition, in gasoline at P = 0.2 MPa and u G £ 0.017 m s -1 , the existence of a chain bubbling regime was detected, whereas in 1-butanol at P = 0.5 MPa and u G £ 0.02 m s -1 , both laminar and turbulent chain bubbling subregimes were identified. It was found that in 1-butanol under ambient pressure, the second and fourth transition velocities occur earlier than in gasoline.

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Flow Regime Identification in a Bubble Column Based on both Kolmogorov Entropy and Quality of Mixedness Derived from CAERPT Data

Cited by 36 publications

References 60 publications

Two-Phase Bubble Columns: A Comprehensive Review

Two-Phase Bubble Columns: A Comprehensive Review

Prediction of The Kolmogorov Entropy Derived from CT Data in a Bubble Column Operated under The Transition Regime and Ambient Pressure

Identification of Various Transition Velocities in a Bubble Column Based on Kolmogorov Entropy

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