Finite Element Analysis of Vane Geometry for Shear Thinning Materials
Bibliographic record
Abstract
Various materials such as cellulose nanofibers (CNF) suspensions contain non-isotropic structures that can lead to strong shear thinning behaviour in parallel-plate geometries; a slip layer seems to form between the plate and the material in such standard geometries.The link between parallel-plate results and data from vane geometries is not clear in the literature.The power-law viscosity model was used to fit the steady-shear results from parallel-plate geometry.The torquerotation rate results were also obtained from a vane geometry for CNF suspensions at three solids levels (2-4 wt%).A finite element method was used to solve the flow equations for calculating the torque applied on the solid surfaces in the vane geometry.The power-law model gave reasonable results for the prediction of torque.It was shown by shear rate distributions that the shearing layers of the fluid existed predominately at radial positions close to the vane radius and the viscosity value at this shear rate becomes important in determination of the torque.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".