Numerical simulation and optimization of the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers
Bibliographic record
Abstract
3-D numerical simulations based on diffusion combustion technology were employed to optimize the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers. In the heating flues, the Eddy-Dissipation Concept (EDC) model and the ideal gas model were utilized to numerically investigate diffusion combustion. What is more, the radiation between the flue gas and the silicon brick was calculated using the Discrete Ordinates (DO) model. After validating the reliability of the model with field-measured data, insights into the temperature field and gas flow in the heating flue, and heat flux distribution over the heating wall were obtained. To characterize the vertical heating uniformity, an index of the standard deviation of the heat flux over the vertical heating walls was proposed. By optimizing the multi-stage air/gas supply design of heating flues, the vertical heating uniformity was improved by 60% according to the index values. The approach developed in this work can be a useful tool for the design of large-capacity coke oven batteries at different scales.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".