A dynamic forcing scheme incorporating backscatter for hybrid simulation
Bibliographic record
Abstract
In this paper, a dynamic forcing scheme incorporating backscatter is proposed in order to remove the artificial buffer layer in a hybrid Reynolds-averaged Navier-Stokes (RANS)/large-eddy simulation (LES) approach. In contrast to previous forcing techniques, the proposed forcing is determined dynamically from the flow field itself, and does not require any extraction of turbulent fields from reference direct numerical simulation (DNS) or high-resolution LES databases. Transport equations for the resolved turbulent stresses and kinetic energy are introduced to investigate the effects of dynamic forcing on reduction of the thickness and impact of the artificial buffer layer. The proposed forcing model has been tested in the context of turbulent channel flows with Reynolds numbers Reτ = 650 and 1020 (based on the wall friction velocity and half channel height). In order to validate the hybrid RANS/LES approach, flow statistics obtained from the simulations have been thoroughly compared against the available DNS data.
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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".