کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4752173 | 1415997 | 2017 | 11 صفحه PDF | دانلود رایگان |
- Gas throughput and induced liquid circulation were driving the impellers to rotate.
- Selfâagitated impellers increased kLa up to 82%.
- Higher improvement of kLa occurred in more viscous CMC solutions.
- Artificial neural network was successfully developed to predict kLa.
In the present study a novel type of internals, selfâagitated impellers, were inserted in the riser section of an externalâloop airlift reactor to intensify mass transfer rates. The performance of selfâagitated impellers was evaluated through comparative analysis of the obtained volumetric mass transfer coefficient values with regard to liquid phase properties and sparger types. Compared to the configuration without impellers, selfâagitated impellers considerably improved reactor characteristics by increasing volumetric mass transfer coefficient up to 82% at smaller superficial gas velocities. At higher gas velocities, corresponding to aeration conditions operated in most cultivation, values of volumetric mass transfer coefficient were 20-30% higher with the insertion of impellers. The effective viscosity played a key role in defining the magnitude of the impellers' effect on the improvement of volumetric mass transfer coefficient. Superficial gas velocity and sparger design influenced impellers efficiency as well. The highest improvements of volumetric mass transfer coefficient were achieved in the most viscous carboxylmethylcellulose solution by using the least effective type of sparger. Besides proposed empirical correlations, which gave an average relative error of 9.1%, an artificial neural network was also successfully developed to estimate the volumetric mass transfer coefficient. The results showed that neural network model was able to predict volumetric mass transfer coefficient with an average relative error of 4.8%.
176
Journal: Biochemical Engineering Journal - Volume 118, 15 February 2017, Pages 53-63