International Journal of Chemical Reactor Engineering
Ed. by de Lasa, Hugo / Xu, Charles Chunbao
12 Issues per year
IMPACT FACTOR 2016: 0.623
5-year IMPACT FACTOR: 0.761
CiteScore 2016: 0.58
SCImago Journal Rank (SJR) 2016: 0.224
Source Normalized Impact per Paper (SNIP) 2016: 0.297
Hydrodynamic and Mass Transfer Parameters in Agitated Reactors Part I: Critical Mixing Speed, Induced Gas Flow Rate, and Wavy Surface in SARs and GIRs
The critical mixing speed for gas entrainment (NCRE), for gas induction (NCRI), induced gas flow rate (QGI) as well as the wavy gas-liquid interfacial area (aWave) of N2 and air were measured in pure toluene and three mixtures of organic liquids (toluene-benzoic acid-benzaldehyde mixtures) under wide ranges of temperatures, T (300-453K), pressures, P (1-15 bar), mixing speeds, N (13.3-23.3Hz) and liquid heights, H (0.171-0.268m) using a 4-liter, see-through agitated autoclave operating as a surface-aeration reactor (SAR) and gas-inducing reactor (GIR).NCRE and NCRI as well as aWave were estimated by analyzing the videos taken with an on-line high-speed Phantom camera through the reactors Jerguson windows. In the GIR, QGI was determined using a highly sensitive Coriolis mass flow meter. The Central Composite Statistical Design and analysis technique was used to study the effect of operating conditions on these hydrodynamic parameters.NCRE and NCRI appeared to increase with liquid height and decrease with temperature, whereas, the pressure and gas nature did not significantly affect both parameters. The liquid physicochemical properties were found to strongly affect NCRE and NCRI, and QGI. Increasing mixing speed or decreasing liquid height increased QGI. Increasing temperature or decreasing liquid viscosity initially increased and then decreased QGI. Increasing pressure or gas density on the other hand decreased QGI. Increasing mixing speed and temperature or decreasing liquid height significantly enhanced aWave, as compared to the flat liquid surface. At high pressures, however, lower values of aWave were obtained. Empirical and statistical correlations were also developed to accurately predict NCRE, NCRI, QGI and aWave.
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