TOWARDS UNDERSTANDING THE INFLUENCE OF GRADIENT RECONSTRUCTION METHODS ON UNSTRUCTURED FLOWSIMULATIONS
Bibliographic record
Abstract
In this paper, the formal order of accuracy of three commonly used gradient reconstruction methods is derived. The analysis showed that the Green–Gauss cell based (GGCB) method is intrinsically inconsistent, due to the leading error term that is independent of the mesh spacing. On the other hand, the Green–Gauss node based (GGNB) and the Least Squares cell based (LSCB) methods achieved a minimum of 1st order accuracy regardless of the mesh geometric properties. Implications of the former results were practically tested on four CFD applications to show that in three out of four cases, the LSCB method achieved the highest order of accuracy. In terms of the computational expenses, the GGNB method consumed 9–34% additional time when compared to the fastest converging method in each test case. Both the GGCB and the LSCB methods consumed nearly the same computational time to reach convergence.
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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 | 0.001 | 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".