Measurements of the size, rise velocity, and specific interfacial area of bubbles in an impinging-jet bubble column
Bibliographic record
Abstract
A 2-D laser particle dynamics analyzer was used to simultaneously measure the bubble size, bubble rise velocity, bubble size distribution, and gas-phase turbulence intensities in an impinging-jet bubble column that utilized two venturi injectors to create turbulent gasliquid jets in the ambient fluid. These measurements were conducted in clean deionized water and in a Kraft pulp mill effluent that was ozonated using a wide range of utilized ozone doses. The intersecting of the gasliquid jets caused an increase in the turbulence produced in the ambient fluid and as a result, the count mean bubble diameter (dB) and the Sauter mean bubble diameter (dS) were smaller than those obtained in conventional bubble columns. This has led to a significant increase in the specific gas bubble interfacial area (a) compared to that in conventional bubble columns. The count mean bubble and Sauter mean bubble diameters were found to be dependent on the superficial gas and liquid velocities (uG and uL, respectively). The count and Sauter mean bubble diameters were smaller in the raw Kraft pulp mill effluent compared to those in the deionized water. This has led to a significant increase in the specific gas bubble interfacial area and gas hold-up (εεG) compared to those in the deionized water. As the raw Kraft pulp mill effluent was ozonated and the amount of utilized ozone increased, the count mean and Sauter mean bubble diameters increased. The bubble size distributions exhibited different trends depending on the type of the test liquid and on the operating conditions in terms of uG and uL. Generally, those distributions could be well described using normal, gamma, or log-normal density functions. Key words: laser, phase, Doppler, impinging-jet, bubble column, bubble, size, gas hold-up, interfacial area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".