Simulating anisotropic flows with isotropic lattice models via coordinate and velocity transformation
Bibliographic record
Abstract
We propose a rectangular lattice Boltzmann model for anisotropic flows based on coordinate and velocity transformation. Unlike other existing rectangular models which tuned the lattice Boltzmann algorithm to fit the rectangular or cuboid lattice grids, here we apply the general lattice Boltzmann method to solve the transformed system over regular square lattice grids. The method is tested with simulations of representative anisotropic flows, including flows in narrow straight and wavy channels, the Taylor–Green vortex flow, and the flow through an elliptical particle array. These simulations show that in general our method produces satisfactory results; however, the aspect ratio [Formula: see text] is limited to relatively large values ([Formula: see text]). The effects of [Formula: see text] on simulation accuracy and stability have been carefully examined, and a possible remedy to improve these concerns has been proposed. The method and analysis could be useful for future development of more robust and practical anisotropic lattice Boltzmann models for realistic simulations.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".