Apparent Entropy Production Difference for Numerical Error Characterization
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Bibliographic record
Abstract
An entropy-based error indicator is presented to evaluate the solution accuracy in fluid flow problems with heat transfer using the Second Law of Thermodynamics. This article presents a new approach for the characterization of numerical error using a newly developed parameter called an “apparent entropy production difference”. A control-volume-based finite-element method (CVFEM) is used to discretize the governing conservation equations and the Second Law. The procedure involves the computation and comparison of local entropy production rates obtained from two forms of the discretized entropy production equations – transport and positive-definite forms of the entropy generation equation. The computed local entropy generation for two problems involving heat transfer in fluid flow agrees well with benchmark solutions. The results of the numerical studies indicated that there is a correlation between the solution error in the computed scalar variable value in each control volume and the apparent entropy production difference.
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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.
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