Measurement of Solids Distribution in Suspension Flows using Electrical Resistance Tomography
Bibliographic record
Abstract
Neutrally buoyant particles in low Reynolds number, pressure-driven suspension flows migrate from regions of high to low shear. When the particle density differs from the suspending fluid, buoyancy forces affect this particle migration. The ratio between the buoyancy and viscous forces, as quantified by a dimensionless buoyancy number, determines the phase distribution of the fully developed suspension. Electrical resistance tomography (ERT) was used to visualize and quantify particle migration in low Reynolds number pressure-driven pipe flows of dense and light particles suspended in a viscous fluid. The measured phase distributions are compared to the predictions of a modified suspension balance model. Les particules à flottabilité nulle dans les écoulements de suspensions entraînées par la pression et à faible nombre de Reynolds, migrent des régions de cisaillement élevé à celles de cisaillement faible. Lorsque la masse volumique des particules diffère de celle du fluide en suspension, les forces de flottabilité influent sur cette migration des particules. Le rapport entre la flottabilité et les forces visqueuses, tel que quantifié par un nombre de flottabilité adimensionnel, détermine la distribution de phase de la suspension pleinement développée. On a fait appel à la tomographie à résistance électrique (ERT) pour visualiser et quantifier la migration des particules dans les écoulements en conduites induits par la pression et à faible nombre de Reynolds pour des particules denses et légères suspendues dans un fluide visqueux. Les distributions de phases mesurées sont comparées aux prédictions d'un modèle d'équilibre de suspension modifié.
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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 | 0.001 |
| 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 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".