Prediction of Gas Holdup in an Aerated Coaxial Mixer Containing Yield Stress Fluids for Mixing Process System Development
Bibliographic record
Abstract
The development of effective gas-liquid mixing systems in mechanically agitated vessels is typically evaluated in terms of the degree of bubbles dispersion. For instance, adequate gas distribution reduces the formation of oxygen-deficient regions and ensures suitable metabolic pathways in bioreactors. In this regard, the gas holdup is a direct measurement of the process performance because the bubbles’ characteristics determines the gas volume fraction inside the vessel. The accurate estimation of this parameter using empirical correlations provides a better insight and a rapid prediction of the mixing process characteristics, which is crucial for designing stirred tanks. However, a challenge in obtaining empirical correlations is related to the experimental ranges of geometrical and process system conditions. In fact, the existing gas holdup correlations have not considered gas dispersion in yield pseudoplastic fluids using a coaxial mixer that comprises concentric shafts rotating independently. As an opportunity in mixing process system design, this study aims to develop empirical gas holdup correlations for an aerated anchor-PBT coaxial mixing system containing a xanthan gum solution, which behaves as a yield stress fluid. The electrical resistance tomography technique was employed to measure the gas holdup based on the conductivity variation throughout the vessel. A central composite design of experiments was conducted to account for the effect of central impeller speed, anchor speed, and gas flow rate on the mixing performance. The results demonstrated a non-monotonic effect of the central impeller speed on the gas holdup, which indicates a variation in the flow regime. Furthermore, the results showed that the gas holdup was increased by decreasing the anchor speed or increasing the aeration rate applied to the system. The developed correlations were statistically assessed and a good agreement with the experimental data was verified, which enabled us to accurately estimate the gas holdup within the range of operating variables investigated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".