CFD Simulations of Gas Holdup in a Bubble Column at High Gas Temperature of a Helium-Water System
Bibliographic record
Abstract
Bubble columns (BCs) are systems that contain two-phases; gas, and liquid, in which gaseous bubbles are dispersed through a liquid in a vertical column. They have a wide range of applications because of their many advantages. The hydrodynamics of the BCs have a significant effect on its scale up analysis. The most important parameter that can be used for describing the performance of the BCs is the gas holdup. In this paper, the overall gas holdup was predicted by developing computational fluid dynamics (CFD) simulations for a helium-water bubble column, where helium gas is injected at 90 o C through a liquid of water at 22 o C. The approaches used to model the bubble column by CFD is 2D plane. From the CFD simulations, it was found that the overall gas holdup increases by increasing the superficial gas velocity at any specific static liquid height. In addition, the overall gas holdup decreases by increasing the static liquid height at any given superficial gas velocity. All CFD simulation results of gas holdup were validated by experimental results of helium-water BCs from previous literature with good agreement, which demonstrates the applicability of the simulations for this kind of BC systems. The CFD results were validated for superficial gas velocities up to 0.15 m/s, and aspect ratios up to 4. From the comparison with the experimental results, it was found that in general, the profiles of gas holdup determined from CFD simulations, under-predicted the experimental data. Also, it was shown that the experimental effects of the static liquid height on gas holdup were correctly predicted by CFD simulations. Moreover, it was observed that the distribution of gas holdup along the cross-section of the column is unequal, where the gas holdup is higher at the center of the column and lower near the wall region.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".