Mixing characteristics of draft tube airlift bioreactor using the electrical resistance tomography
Bibliographic record
Abstract
In this work, mixing characteristics in terms of mixing time, hydrodynamics (liquid circulation velocity and gas hold up) and shear rate were performed in the downcomer of a draft tube airlift bioreactor with different geometries (i.e., Ad/Ar between 0.38 – 2.31 and bottom clearances between 0.003-0.00 m). Newtonian (water and 34.5% coalescing sugar solution) and on Newtonian (0.2% and 0.5% xanthan gum solutions) with different viscosities were used as the liquid phase. Compressed air was used as the gas phase which was introduced through cross and circular shaped sparger configurations at superficial velocities Ugr = 0.00165-0.00807 m/s. The combined effects of geometric parameters (Ad/Ar, bottom clearances), sparger configuration, and liquid viscosity on mixing characteristics have been presented. Results showed that the increase in superficial gas velocity (Ugr) corresponds to an increase in energy generated, and thus decreases in mixing time. However, the increase in Ugr corresponds to the increase in liquid circulation velocity, gas holdup and shear rate values. Moreover, bottom clearances and draft tube diameters show effects on flow resistance frictional losses which affect results of mixing parameters investigated. The influence of sparger configurations on mixing time and liquid circulation velocity is significant due to their effect on gas distribution. Mixing time decreased to about 40% in air-water media using the cross shaped sparger. Results obtained with cross shaped sparger showed even and uniform distribution of gas, which provided better mixing as compared to the circular shaped sparger configuration. However, the sparger configuration effect on shear rate is not as significant (about 20% reduction in shear rate values using the cross shaped sparger). The effect of fluid viscosity had a significant influence on both mixing times and circulation velocity, especially in the coalescing media of sugar and xanthan gum solutions. Results from this work will help to develop a clear pattern for operation and mixing that can help improving [sic] several industrial processes, especially the ones related to emerging fields of technology such as the biotechnology industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".