Predicting the Curvature of the Interface for an Oil/Water Flow and Its Effects on Corrosion
Bibliographic record
Abstract
Abstract Previous works on the oil/water flow corrosion have focused on the determination of the transition criteria from water-wetting to oil-wetting. In many situations, the criteria need to be properly applied along with the calculations of the two phase flow mass and momentum conservation. In this paper, a unified oil/water flow model was employed to simulate the transitions from stratified types of flow to dispersed types of flow. In addition, for stratified types of flows, the curvature of the interface is determined from the minimum of the total system energy. The predicted curved interface results in different clock positions of corrosion compared to a flat interface. An example study is given to show how this flow model can be employed to grade different types of oils in terms of susceptibility to corrosion and to study the effects of terrain on the corrosion clock positions and how it can be integrated with a corrosion model for corrosion predictions.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".