A volume‐based discrete test filter for conducting large eddy simulations with application to physiological flow in a constricted tube
Bibliographic record
Abstract
Abstract A discrete test‐filtering operation that takes advantage of a volume‐averaging procedure, as opposed to the more popular line‐interpolation technique, has been developed to enable mixed‐scale and dynamic LES simulations on general unstructured grids. Simulations of fully developed turbulent flow in a square duct show that the proposed test filter gives the results of similar accuracy to the best modern filters developed for non‐uniform orthogonal grids, but a second‐order correction is required to produce solutions of sufficient accuracy. The discrete filter technique is also used to simulate stationary and pulsatile turbulent flow in a 75% constricted tube, in which the flow undergoes transition to turbulence. Comparisons to previous published results confirm that the results obtained using the proposed discrete test filter are in a good agreement with the existing experimental and numerical results. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".