MODIFIED TRANSPORT EQUATIONS FOR THE THREE-PHASE FLOW OF IMMISCIBLE, INCOMPRESSIBLE FLUIDS THROUGH WATER-WET POROUS MEDIA
Bibliographic record
Abstract
In this study, generalized transport equations are combined with partition concepts to construct modified transport equations for the immiscible, incompressible, and vertical three-phase flow of fluids. These equations are used to demonstrate that failure to include interfacial coupling in the mathematical description of such flow can introduce significant amounts of model error into the equations used to describe vertical three-phase flow through porous media. It was found that when the magnitudes of the potential gradient and the net buoyant force for the wetting phase were of the same order, failure to account for interfacial coupling introduced a significant amount of model error into the analysis. The model error for the wetting phase was found to be larger than that for the two nonwetting phases. If the potential gradient for the wetting phase was an order of magnitude larger than the net buoyant force, neglect ofinterfacial coupling effects introduced smaller amounts of model error into the analysis. Also, it was found that a failure to take proper account of interfacial coupling in the mathematical description of three-phase countercurrent flow resulted in the introduction of more model error than was the case for cocurrent flow. Finally, it was determined that the modified transport equations describing three-phase countercurrent flow were case dependent.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".