Effects of NO Models on the Prediction of NO Formation in a Regenerative Furnace
Why this work is in the frame
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Bibliographic record
Abstract
A study of the effects of nitric oxide (NO) models on the prediction of NO formation in a gas-fired regenerative furnace with highly preheated air was undertaken. Three chemical kinetic processes for NO formation/depletion, i.e., thermal NO, prompt NO, and NO reburning, are included. In the thermal NO model, the sensitivity encountered when using two different approaches, namely the equilibrium approach and the partial equilibrium approach, for determining the O radical concentration was studied. The effects of the third reaction in the thermal NO mechanism, NO reduction (reburning) mechanism, and different types of probability density functions (PDFs) on the NO predictions have also been tested. The sensitivity of the excess air ratio on the NO generation rate in the furnace has been investigated. Finally, the impact of the temperature on the NO formation rate in the regenerative furnace was discussed. [S0195-0738(00)00304-6]
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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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it