Bibliographic record
Abstract
In this paper, a dynamic subgrid scale (SGS) stress model based on Speziale’s quadratic nonlinear constitutive relation [C. G. Speziale, J. Fluid Mech. 178, 459 (1987); T. B. Gatski and C. G. Speziale, J. Fluid Mech. 254, 59 (1993)] is proposed, which includes the conventional dynamic SGS model as its first-order approximation. The closure method utilizes both the symmetric and antisymmetric parts of the resolved velocity gradient, and allows for a nonlinear anisotropic representation of the SGS stress tensor. Unlike the conventional Smagorinsky type modeling approaches, the proposed model does not require an alignment between the SGS stress tensor and the resolved strain rate tensor. It exhibits significant flexibility in self-calibration of the model coefficients, and local stability without the need for plane averaging to avoid excessive backscatter of SGS turbulence kinetic energy and potential modeling singularity problems. It also allows for variable tensorial geometric relations between the SGS stress and its constituent terms, and reflects both forward and backward scatters of SGS turbulence kinetic energy between the filtered and subgrid scales of motions. Turbulent Couette flow for Reynolds numbers (based on channel height and one half the velocity difference between the two plates) of 2600 and 4762 was used in numerical simulations to validate the proposed approach.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".