Numerical Modelling of the Flow of Fibre Suspensions through a Planar Contraction
Bibliographic record
Abstract
Abstract This study presents results of numerical simulations of the flow of fibre suspensions in a Newtonian fluid through a 4:1 planar contraction. Two approaches are adopted to determine the fibre orientation. The first one uses orientation tensors defined as dyadic products of the orientation vector, while the second one is based on the fibre aligned assumption. An implicit time discretization scheme and a mixed finite element method based on the introduction of the rate of deformation tensor as an additional unknown are used to obtain the steady‐state flow. The numerical technique we use allows us to examine the flow of fibre suspensions in both dilute and semi‐dilute regimes at high values of the parameters controlling inertial and fibre effects. The predicted flow patterns and fibre orientation are discussed, and a systematic comparison between the predictions of the two approaches is presented.
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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) | 0.000 | 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".