Effect of impeller type on continuous‐flow mixing of non‐Newtonian fluids in stirred vessels through dynamic tests
Bibliographic record
Abstract
Abstract Mixing of non‐Newtonian fluids with axial and radial flow impellers is prone to a significant extent of nonideal flows (e.g., dead zones and channelling) within the stirred reactors. To enhance the performance of the continuous‐flow mixing of pseudoplastic fluids with yield stress, close‐clearance impellers were utilised in this study. We explored the effects of various parameters such as the type of close‐clearance impeller (i.e., the double helical ribbon (DHR) and anchor impellers), impeller speed (25–500 rpm), impeller pumping direction, fluid rheology (0.5–1.5% xanthan gum solution), fluid flow rate (3.20–14.17 L min −1 ) and the locations of outlet (configurations: top inlet–top outlet, top inlet–bottom outlet) on the dynamic performance of the mixing vessel. The performance of the DHR impeller was then compared to the performance of various types of impellers such as axial‐flow (Lightnin A320) and radial‐flow (Scaba 6SRGT) impellers. The dynamic tests showed that the DHR impeller was the most efficient impeller for reducing the extent of nonideal flows in the continuous‐flow mixer among the impellers employed in this study. In addition, the mixing quality was further improved by optimising the power input, increasing the mean residence time, decreasing the fluid yield stress, using the up‐pumping impeller mode and using the top inlet–bottom outlet configuration. © 2011 Canadian Society for Chemical Engineering
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".