Performance of Four Axial Flow Impellers for Agitation of Pulp Suspensions in a Laboratory-Scale Cylindrical Stock Chest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Axial flow impellers are commonly used for pulp suspension agitation. Pulp fiber suspensions are non-Newtonian and exhibit a yield stress. In mixing operations, a ‘cavern’ (region of active motion) is created around the impeller, with the size of the cavern affecting the quality of mixing attained. In this work, the cavern size produced by four different axial flow impellers in a C m = 3% (mass concentration) hardwood pulp suspension was measured using electrical resistance tomography (ERT) and by analysis of dynamic mixing tests. Cavern size is shown to depend on impeller performance as characterized by power number, N P, and axial force number, N f . At an equal power consumption of 0.53 kW/m 3 the largest cavern was produced by the impeller having the largest values of N P and N f . The measured cavern volumes compared well with predictions of the axial force model developed by Hui et al. [Hui, L. K.; Bennington, C. P. J.; Dumont, G. A. Cavern formation in pulp suspensions using side-entering axial-flow impellers. Chem. Eng. Sci. 2009, 64, 509], which accounted for interaction between the cavern and the vessel walls. When the cavern just filled the vessel volume, the time constants determined using the dynamic mixing test data reached 90% of their theoretical values (with the estimated standard deviation of ±10%), indicating that the chest approached an ideal dynamic response (complete mixing) with the onset of complete motion in the chest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it