Three-Dimensional Distributed Mass Weighting for Noninverted Convective Skew Upwinding
Bibliographic record
Abstract
Numerical studies of skew upstream differencing are presented for three-dimensional convective heat transfer problems. Two new types of noninverted skew upwind schemes are developed and compared, so that local inversion of influence coefficient matrices is not required. Unlike previous schemes, skew upwind values of temperature are expressed explicitly in terms of surrounding nodal variables. Different mass weighting alternatives, including 3-node/3-point and 4-node/8-point formulations are developed and evaluated. Results are presented for three application problems, that is, convective step change of temperature, tank inflow/outflow, and radial heat flow in ar otating hollow sphere. Although the effects of upwind nodal asymmetry appear minor in the first and second problems, noticeable improvement with 4-node/8-point interpolation is observed in the rotating sphere problem. Additional reduction of CPU time due to noninverted convective upwinding is reported.
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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 | 0.000 | 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".