Occurrence of Naturally Shaped Lenticular Bed Deposit and Its Influence on the Frictional Pressure Drop during Pipeline Transportation of Low Concentration Slurries
Bibliographic record
Abstract
Solid particles can be transported along a pipeline in the form of trains of individually shaped lenticular deposits (LDs) when the concentration of solids is less than 1 vol% and the transport velocity is below the critical value required for full suspension. Such special bed transport, observed as rippled sand dune patterns, may occur in petroleum production lines transporting oil and gas produced from unconsolidated sand reservoirs under turbulent flow conditions, and during sediment transport by rivers and winds. The primary objective of this study was to investigate how the occurrence of lenticular bed deposits affects near-wall turbulent activities at the sand/fluid (“wave-like”) interface and frictional pressure drop during pipeline transportation of solids. Particle image velocimetry (PIV) measurements were used to quantify the velocity field, the turbulence kinetic energy (TKE), and the coherent structures associated with surface morphology change and LD formation near the bed deposits/fluid interface. A 7–8% reduction in frictional pressure drop was consistently observed during the transition from continuous sand bed to LDs. Results also indicate that the formation of naturally shaped LDs reduces the intensity and frequency of near-wall turbulent coherent structures (burst-sweep events). Moreover, TKE associated with flow over the LDs was found to be lower than that of continuous bed and water (only) flow.
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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 | 0.000 |
| 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) | 0.000 | 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".