Solids flow mapping in a high pressure slurry bubble column

Rados, Novica; Shaikh, Ashfaq; Al‐Dahhan, Muthanna H.

doi:10.1016/j.ces.2005.04.087

Cited by 41 publications

(26 citation statements)

References 5 publications

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“…This time series was utilized for KE analysis. Further details about the CT experimental facility can be found in Rados [23] and Rados et al [24].…”

Section: Methodsmentioning

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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“…This time series was utilized for KE analysis. Further details about the CT experimental facility can be found in Rados [23] and Rados et al [24].…”

Section: Methodsmentioning

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 column design enables easy removal of the distributor chamber and replacement of the sparger. Further details can be found elsewhere [27,28].…”

Section: Methodsmentioning

confidence: 99%

Flow Regime Identification in a Bubble Column Based on Both Statistical and Chaotic Parameters Applied to Computed Tomography Data

2006

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The Kolmogorov entropy (KE) algorithm was applied successfully to single source c-ray Computed Tomography (CT) data measured in a 0.162 m ID bubble column equipped with a perforated plate distributor (163 holes ·˘1.32 mm). Dried air was used as the gas phase and Therminol LT (q L = 886 kg m -3 , l L = 0.88 · 10 -3 Pa s, r = 17 · 10 -3 N m -1 ) was used as a liquid phase. Three different pressures, P, of 0.1, 0.4, and 1.0 MPa were examined. At each pressure the superficial gas velocity, u G , was increased stepwise by steps of 0.01 m s -1 up to 0.2 m s -1 . The average absolute deviation (AAD) was also used as a robust statistical criterion for regime transition. At all three pressures, based on the sudden changes in both the AAD and KE values, the boundaries of the following five regimes were identified: dispersed bubble regime, first and second transition regimes, coalesced bubble regime consisting of four regions (called 4-region flow), and coalesced bubble regime consisting of three regions (called 3-region flow). The existence of these regimes has already been documented. As the pressure increases, the transition velocity between the dispersed bubble and first transition regimes and the transition velocity between coalesced bubble (4-region flow) and coalesced bubble (3-region flow) regimes shift to higher u G values. On the other hand, at P = 0.4 MPa the second transition regime starts earlier. In addition, at P = 1 MPa the transition to coalesced bubble (4-region flow) is delayed.

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“…By assuming ergodicity, that is that a long time average of a single particle is equivalent to a spatial average of many particles, and that the motion of the tracer particle is determined by the motion of the continuous phase, it is then possible to extract a map of the distribution of the velocity of the continuous phase (Chen, Kemoun, et al, 1999;Karim, Varma, Vesvikar, & Al-dahhan, 2004;Rados, Shaikh, & Al-Dahhan, 2005;Upadhyay, Pant, & Roy, 2013;Varma & Al-dahhan, 2007). A benefit of these radioactive particle tracking techniques is that they are capable of measuring the velocity and velocity fluctuations of the continuous phase of opaque flows at high pressure and temperature, and thus are able to probe operations at industrially relevant conditions (Karim et al, 2004;Rados et al, 2005). Such experiments have proven particularly beneficial when combined with CT measurements of the same system, as in this case it is possible to extract both time-averaged density and velocity information.…”

Section: Fluid Velocity Measurementsmentioning

confidence: 99%

Applications of tomography in bubble column and trickle bed reactors

Holland

2015

Industrial Tomography

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Solids flow mapping in a high pressure slurry bubble column

Cited by 41 publications

References 5 publications

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

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

Flow Regime Identification in a Bubble Column Based on Both Statistical and Chaotic Parameters Applied to Computed Tomography Data

Applications of tomography in bubble column and trickle bed reactors

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