Effect of Particle Size and Surface Properties on the Sandbed Erosion with Water Flow in a Horizontal Pipe
Bibliographic record
Abstract
Summary An experimental study was conducted to investigate the transport of sand particles over the sand bed deposited in a horizontal conduit by using turbulent flow of water. The main objectives were to determine the near-wall turbulence characteristics at the onset of bed erosion (i.e., near-wall velocity profile, Reynolds shear stresses, and axial-turbulent intensity); to determine critical velocity required for particle removal from the bed deposits; and more specifically, to determine how the sand-particle size and surface characteristics would influence the critical velocity required for the onset of bed erosion and the near-wall turbulence characteristics. A large-scale horizontal flow loop equipped with a nonintrusive laser-based particle-image velocimetry (PIV) system has been used for the experiments. The effect of sand-particle surface characteristics (i.e., wettability) on the critical velocity and the near-wall turbulence characteristics were investigated by using treated and untreated industrial sands of four different mesh sizes (i.e., 20/40, 30/50, 40/70, 100). The PIV technique was used to determine instantaneous local velocity distribution near the stationary sandbed fluid interface under subcritical and critical flow conditions. The near-wall velocity distribution measured directly at the sand bed/fluid interface together with the measured frictional pressure-loss values were then used for the evaluation of the Reynolds shear stresses and axial turbulent intensities acting at the bed/fluid interface. The results indicated that critical velocity for the onset of particle removal from sand beds increased with the increasing particle size. When sands with special surface treatment were used, it was observed that the critical velocity required for the onset of the bed erosion was significantly lower than that of required for the untreated sands. The degree of reduction in critical velocity varied between 14 and 40% depending on the particle size. In this study, by conducting experiments under controlled conditions, we provided much-needed fundamental data that can be used for the development of improved solid-transport design criteria and suitable mitigation technologies. In particular, we have shown the proof of concept that the surface-treated sand particles might have great potential for improving the transport efficiency of proppants used for hydraulic-fracturing operations.
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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 | 0.000 |
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 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".