Pressure-Driven Suspension Flow near Jamming
Bibliographic record
Abstract
We report here magnetic resonance imaging measurements performed on suspensions with a bulk solid volume fraction (${\ensuremath{\phi}}_{0}$) up to 0.55 flowing in a pipe. We visualize and quantify spatial distributions of $\ensuremath{\phi}$ and velocity across the pipe at different axial positions. For dense suspensions (${\ensuremath{\phi}}_{0}>0.5$), we found a different behavior compared to the known cases of lower ${\ensuremath{\phi}}_{0}$. Our experimental results demonstrate compaction within the jammed region (characterized by a zero macroscopic shear rate) from the jamming limit ${\ensuremath{\phi}}_{m}\ensuremath{\approx}0.58$ at its outer boundary to the random close packing limit ${\ensuremath{\phi}}_{\text{rcp}}\ensuremath{\approx}0.64$ at the center. Additionally, we show that $\ensuremath{\phi}$ and velocity profiles can be fairly well captured by a frictional rheology accounting for both further compaction of jammed regions as well as normal stress differences.
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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 | 0.001 |
| 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 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".