Modeling Three-dimensional Flow and Heat Transfer in Variable Surface Tension Two-phase Flows
Bibliographic record
Abstract
In the present study a parallel three dimensional Volume of Fluid (VOF) method is developed to simulate Marangoni force in immiscible fluids with variable surface tension. Conservation equations are solved based on cell-averaged one-field volume tracking scheme. Evaluating the convective term in the energy equation along the boundary between the fluids highly depends on the position and orientation of the interface; hence, using average cell values simply ignores the interface shape and leads to computational uncertainty. As a remedy to this issue, the original idea behind the volume tracking method is used not only to advect mass and momentum but also energy across cells. To verify the proposed algorithm, results are compared against theoretically predicted thermocapillary migration velocity of a droplet at the limit of zero Marangoni number. However, at relatively high Marangoni numbers, thermal boundary layers are very thin and challenging to resolve. To demonstrate the capabilities of the heat transfer module, simulations of a Fluorinert droplet moving in silicon oil under applied temperature gradient in microgravity are compared against the available experimental results and the migration velocity of the droplet are reported.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".