Influence of rheological parameters on the performance of the aerated coaxial mixer containing a pseudoplastic fluid
Bibliographic record
Abstract
Gas dispersion in non-Newtonian fluids has numerous applications in many chemical and biochemical applications. However, the effect of the power-law model constants describing the rheological behavior of the pseudoplastic fluid has never been investigated. Thus, a numerical model was developed to simulate the hydrodynamics of gas dispersion in non-Newtonian fluids with a coaxial mixer. Then, a set of experiments was conducted to assess the mass transfer efficacy of a coaxial mixer to benchmark the numerical model. In this regard, various methods, including dynamic gassing-in and electrical resistance tomography methods, were used to quantify the mass transfer and gas hold-up profiles. The influence of fluid rheological properties, gas flow number, and rotating mode on the power consumption, mass transfer coefficient, bubble size profile, and hydrodynamics were examined both experimentally and numerically. The response surface model (RSM) was employed to explore the individual effects of power-law model constants on mass transfer. The RSM model utilized five levels for the consistency index (k), five levels for the flow index (n), and three levels for the gas flow number. The statistical model proposed that the absolute model constants for the flow and consistency indices were 0.0012 and 0.0010, respectively, for the co-rotating mixer. Conversely, for the counter-rotating mixer, these constants were 0.0010 and 0.0013, respectively. Therefore, this study revealed that the co-rotating coaxial mixer was well-suited for dispersing gas within a fluid with high consistency. In contrast, the counter-rotating mixer proved effective in enhancing gas dispersion within a fluid with a lower flow index.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".