A systematic analysis of foam drainage: Experiment and model
Bibliographic record
Abstract
Foam drainage describes the flow of a liquid through a foam, driven by gravity and capillarity. This is an important factor for foam stability, and thus of great relevance to many sectors including the oil and gas industries. We are proposing a generalized version of the drainage equation along with an exponential equation to predict the foam life at the later time. The models yield the foam height values as a function of time. It was observed that in early times foam volume, V(t), varies linearly with time and that at later times, it displays power or exponential asymptotes with the exponents depending on the dissipation mechanism. The models were tested through foam experiments in static conditions where the ascending and descending foam heights were monitored as a function of time. Conventional and nanoparticle fortified foams stability under static conditions were tested up to 115 °C and 2.8 MPa. Furthermore, the effect of nanoparticle concentration and different surfactants on foam drainage rate were investigated systematically. Subsequently, measurements were fitted to the empirical expressions. The model coefficients relate to film properties, which vary with pressure, temperature and chemical composition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".