Vortex Identification in Large Eddy Simulations Under the Lattice Boltzmann Framework With a Smagorinsky Subgrid Model
Bibliographic record
Abstract
Abstract The recent emergence of turbulence modeling strategies under the Lattice Boltzmann Method (LBM) framework has opened the door towards highly efficient numerical solutions for the governing fluids equations with potential application to industry. Advantages of the LBM over traditional Navier-Stokes (NS) based methods include its straightforward parallelization and its ability to recover flow dynamics without explicit treatment for pressure. In the present work, Large Eddy Simulation within a Lattice Boltzmann framework is used to study a lid-driven cavity. In particular, a Smagorinsky subgrid scale model is chosen for the unresolved scales within a single-relaxation-time LBM. Simulations are performed in three dimensions at a Reynolds number of 105. One-dimensional energy spectra are computed and the range of energy scales in the numerical solutions are inspected to ensure that turbulence has been captured. Isosurfaces of various vortex identification criteria are examined and compared to the vorticity magnitude and pressure minima.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".