Stable Triple-Layer Lubricated Pipeline Flow
Bibliographic record
Abstract
Abstract Recently we have introduced a novel methodology for efficient transport of heavy oil via a triple-layer core-annular flow [1]. Pumping pressures are significantly reduced by concentrating high shear rates to a lubricating layer, while ideas from visco-plastic lubrication were used to eliminate interfacial instabilities. We purposefully position a shaped unyielded skin of a visco-plastic fluid between the transported oil and the lubricating fluid layer. The shaping of the skin layer allows for lubrication forces to develop and balance the density difference between the fluids. Here we show an explicit advantage of the proposed method. Essentially the method can give stable flows for a very wide range of fluid input ratio, although not all will produce the desired reduction in frictional pressure losses. Additionally, we use the extensional flow method derived in [2] to estimate the required yield stress to maintain the skin completely unyielded.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".