FRACTIONAL GAS HOLD-UP PERFORMANCE AND CORRELATION METHODS IN MECHANICALLY AGITATED REACTORS WITH MIXED HYDROFOIL IMPELLER 6k5 AND RUSHTON TURBINE
Jiating Zhang
Abstract
Jiating Zhang
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.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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