Effect of Black Liquor Burning on the Settling and Filtering Behaviour of Green Liquor Dregs
Why this work is in the frame
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Bibliographic record
Abstract
In kraft pulp mills, the burning of black liquor in recovery boilers results in unburned carbon, or char particles, that along with other types of particles form the suspended solids in green liquor called dregs. Poor dregs settling and filterability are a persistent problem at many mills that can result in substantial production losses. A systematic study was conducted to investigate the effect of black liquor burning conditions on the settling and filtering behaviour of dregs using a combination of experimental work and multivariate data analysis (MVDA), with a focus on the char component of dregs. The experimental results show that char is easier to settle and filter when i) black liquor is burned at higher temperatures or for longer amounts of time, ii) char concentration is low, and iii) lime mud is added to char. The results also imply that larger char particles tend to settle faster. MVDA was carried out on operating data from three kraft pulp mills to examine the correlations between recovery boiler operation and the dregs behaviour observed at each mill. The results suggest that low firing load to the recovery boiler, a low extent of char burning, and an unstable or cold char bed could lead to larger amounts of char (dregs) in green liquor.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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