An additive approach toward determination of liquid-phase mass transfer coefficients in sandwich packings
Bibliographic record
Abstract
• New additive method to process measured mass transfer data in sandwich packings. • Novel liquid-side mass transfer coefficient correlations for structured and sandwich packings. • Liquid-side mass transfer is up to 4.5 times faster in froth flow compared to film flow. Sandwich packings are innovative separating column internals based on a periodic arrangement of two conventional structured packings with different geometrical surface areas. They are operated with partially flooded layers to intensify phase interactions and enhance mass transfer. The application of sandwich packings in absorption and distillation processes requires detailed understanding of the gas–liquid mass transfer phenomena in the individual layers. For this reason, we carried out an experimental investigation of CO 2 desorption and developed an additive approach to process the measured data. On this basis, liquid-side mass transfer correlations for the flow patterns in the flooded packings sections were derived. The novel additive approach together with the developed correlations allows accurate prediction of the liquid-side mass transfer in sandwich packings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".