Validation of a procedure for the numerical simulations of gas–liquid stirred tanks by means of a computational fluid dynamics approach
Bibliographic record
Abstract
Abstract Impellers with concave and vertically asymmetric blades proved superior gas dispersion capabilities and power consumption characteristics under gassed turbulent conditions with respect to traditional flat‐blade turbines in aerated fermenters. In this study, a pilot‐size gas–liquid tank stirred with an asymmetric blade disk impeller is numerically investigated by means of a Reynolds averaged two‐fluid model combined with a simplified population balance model without adjustable parameters. This work aims at increasing the predictive capabilities of computational fluid dynamics multiphase modelling by validating a computational approach for the realistic simulation of industrial aerated fermenters and thus allowing for a more reliable scale‐up. A methodology for achieving fully predictive results on fundamental variables for gas–liquid stirred tanks such as gassed power consumption, overall gas hold‐up, and volumetric mass transfer coefficient, with affordable computational requirements at pilot and industrial scale is presented. Two‐phase results are compared with the experimental data collected in a geometry matching the computational domain equipped with 3 planes of 16 sensors to enable electro‐resistance tomography measurements and with suitable correlations from the literature. The limits and strength of the numerical procedure are discussed, starting from the comparison between computational predictions and experimental measurements.
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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".