Measuring Flow Velocity and Uniformity in a Model Batch Digester Using Electrical Resistance Tomography
Bibliographic record
Abstract
Abstract The literature shows that the extent of delignification in batch digesters varies as a function of chip location in the vessel. This non‐uniformity may be exacerbated by a number of factors but is commonly attributed to poor and/or non‐uniform liquor flow through the reactor (which causes poor chemical and heat distribution to the chip mass during the cook). Electrical resistance tomography (ERT) was used to evaluate the uniformity of liquor flow in a laboratory model digester under scaled industrial conditions (a 1:15 geometrically scaled vessel, a vessel to particle diameter ratio of 93:1 to minimize wall effects, and close approximation of liquor superficial velocity and pore Reynolds number). Local interstitial flow velocities were measured using pixel‐pixel cross correlation techniques. It was possible to create uniform zones in the digester, but a stagnation point was observed in the centre of the vessel at the screen level. This point coincides with the location of highest kappa numbers (lowest degree of cooking) reported in industrial tests.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".