An experimental study of smelt-water interaction in the recovery boiler dissolving tank
Bibliographic record
Abstract
A laboratory apparatus was constructed to simulate the operating conditions of recovery boiler smelt dissolving tanks and used to systematically study the interaction between molten smelt droplets and water. Experiments were performed on synthetic smelt made of 80 wt% Na2CO3 and 20 wt% NaCl at 800°C, 900°C, and 1000°C. The results show that upon contact with water, some smelt droplets explode immediately and break into small pieces, some require a delay time to explode, and others solidify without exploding. The probability of explosion strongly depends on water temperature and to some extent, smelt temperature. At a given smelt temperature, there exists a water temperature range below which explosion always occurs (the lower critical water temperature) and above which there is no explosion (the upper critical water temperature). The lower critical water temperature decreases with increasing smelt temperature, while the upper critical water temperature remains the same at 82°C in all cases. Up to this upper critical water temperature, both the explosion delay time and explosion intensity increase with increasing water temperature. The data was used to construct a Smelt-Water Interaction Temperature (SWIT) diagram that can predict if a molten synthetic smelt droplet will explode in water at different smelt and water temperatures.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".