Flow Loop for X-Ray CT Imaging of Sand Transport
Bibliographic record
Abstract
Abstract Two closed circuit flow loops have been constructed for X-ray CT imaging of multiphase flows. A 3rd generation helical scanner provides 3D images with a voxel size as small as 0.35×0.35×0.30mm. By "folding" the loops, flows have been imaged over a 16m section of 3.8 cm (1-1/2") pipe. In future, larger bores could be accommodated with a shorter overall length, dictated by the aperture and weight limit of the scanner. Sand slurry flows have been imaged in both laminar and turbulent regimes (using silicone oil and water, respectively) over a range of velocities reflective of typical in situ pressure gradients. Flowing sand concentrations up to 20% by volume were achieved by adjusting the total sand content in the loop. With proper calibration the CT images provide detailed, quantitative measures of sand concentration and, indirectly, the partitioning between moving and settled regions of the flow. The flowing density profiles vary significantly with the sand content and flow velocity, indicative of changing sand transport mechanisms. Fluctuations over the observable length of the loop show evidence of settling overlaid on the flow-induced resuspension. The effects of the end loops on both aspects of sand transport are considered.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".