Effects of chemical composition on the removability of recovery boiler fireside deposits
Bibliographic record
Abstract
Effective removal of fireside deposits by sootblowers in a kraft recovery boiler is critically important for maintaining stable operation of the boiler. The removability of recovery boiler deposits was studied under simulated conditions in the laboratory using an entrained flow reactor (EFR) coupled with an air jet blow-off apparatus. Synthetic carryover particles were fed into the EFR controlled at 800 C. The resulting deposits, which collected on an air-cooled probe at the EFR exit, were removed with a high-pressure air jet. The results show that the required peak impact pressure (PIP) of the jet to remove a deposit increased markedly with an increase in the chloride content of the deposit, and, to a lesser extent, with an increase in potassium and carbonate content. The combined effect of these components was significantly greater than the sum of the effects of individual components. The results also show that deposits were more difficult to remove as the tube surface temperature increased.
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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) | 0.000 | 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) | 0.001 | 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".