The Soret Effect with the D1Q2 and D2Q4 Lattice Boltzmann Model
Bibliographic record
Abstract
Abstract The paper analysis the incorporation of the source term in the advection-diffusion equation for the BGK Lattice Boltzmann Method (LBM). The problem is the coupled energy and species conservation equations with the Soret term. The problem is extremely important for people using LBM in simulating multi-physics, because multi-physics effect added as a source term to LB. A Few BGK LBM models were used, namely D1Q2, D1Q3, D2Q4 and D2Q5 to solve advection-diffusion-reaction problems. The aim of this work is to demonstrate that the lattice Boltzmann method is able to simulate Soret effect, where the source term is the curvature of the temperature field. Theoretical analysis of the force inclusion is also presented in the paper. To insure that the predictions are correct and consistent with the traditional methods, comparison of LBM predictions with the finite difference method (FVM) predictions were illustrated. Also, the results show that prediction of D1Q2 may suffer from oscillation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".