2004•Journal of Chemical Industry and EngineeringRequires access

FRACTIONAL GAS HOLD-UP PERFORMANCE AND CORRELATION METHODS IN MECHANICALLY AGITATED REACTORS WITH MIXED HYDROFOIL IMPELLER 6k5 AND RUSHTON TURBINE

Jiating Zhang

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Abstract

A fractional gas hold-up performance in mechanically agitated reactor (i.d. range is 0.382m to 1.16m) with mixed hydrofoil impeller 6k5 and Rushton turbine was presented. The effects of geometrical variables,including the ratio of impeller diameter,the distance between impellers,the clearance of lower impeller, gas sparger position, the baffle type,and the operating conditions such as agitator speed, the rate of gas, and the pumping mode of axial impeller 6k5 on fractional gas hold-up were investigated. With the dimensionless and dimensional methods, two correlations were proposed, but their prediction ability was not satisfactory.The correlation based on artificial neural network was established.It was able to predict fractional gas hold-up reasonably well and the relative mean error of generalization by this neural network model was within ±10%, if the parameters were in the trained range. The neural network model could be used for offline prediction and parameter optimization, and could be useful for scale-up because dimensionless parameters were used.

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A fractional gas hold-up performance in mechanically agitated reactor (i.d. range is 0.382m to 1.16m) with mixed hydrofoil impeller 6k5 and Rushton turbine was presented. The effects of geometrical variables,including the ratio of impeller diameter,the distance between impellers,the clearance of lower impeller, gas sparger position, the baffle type,and the operating conditions such as agitator speed, the rate of gas, and the pumping mode of axial impeller 6k5 on fractional gas hold-up were investigated. With the dimensionless and dimensional methods, two correlations were proposed, but their prediction ability was not satisfactory.The correlation based on artificial neural network was established.It was able to predict fractional gas hold-up reasonably well and the relative mean error of generalization by this neural network model was within ±10%, if the parameters were in the trained range. The neural network model could be used for offline prediction and parameter optimization, and could be useful for scale-up because dimensionless parameters were used.

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Available abstract

A fractional gas hold-up performance in mechanically agitated reactor (i.d. range is 0.382m to 1.16m) with mixed hydrofoil impeller 6k5 and Rushton turbine was presented. The effects of geometrical variables,including the ratio of impeller diameter,the distance between impellers,the clearance of lower impeller, gas sparger position, the baffle type,and the operating conditions such as agitator speed, the rate of gas, and the pumping mode of axial impeller 6k5 on fractional gas hold-up were investigated. With the dimensionless and dimensional methods, two correlations were proposed, but their prediction ability was not satisfactory.The correlation based on artificial neural network was established.It was able to predict fractional gas hold-up reasonably well and the relative mean error of generalization by this neural network model was within ±10%, if the parameters were in the trained range. The neural network model could be used for offline prediction and parameter optimization, and could be useful for scale-up because dimensionless parameters were used.

Key concepts: Impeller, Rushton turbine, Agitator, Dimensionless quantity, Sparging, Baffle, Mechanics, Turbine

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