Modulation of suspension electrical conductivity to counter fines plugging in trickle‐bed reactors
Bibliographic record
Abstract
Abstract Modulation of electrical conductivity in kaolin/kerosene suspensions was examined as a means for the attenuation of fines retention in trickle‐bed reactors. The suspension stability was remarkably enhanced through ON‐OFF concentration modulation of an electrolyte‐based kerosene conductivity improver and resulted in an efficient bed‐cleaning strategy under operating conditions. Periodic additions of the conductivity improver enabled fines and deposits to gain momentarily large and similar electrical charges undoing, or impeding, multilayer deposition. The time evolution of the two‐phase pressure drop and specific deposit with/without conductivity improver was monitored, as well as the corresponding local deposition structure via electrical capacitance tomography (ECT). Electrical conductivity modulation was found to reduce the bed‐specific deposit by an order of magnitude and the bed pressure drop increment by a factor 14. ECT imaging evaluated the efficacy of this modulation strategy in mitigating deposition and in preventing filtration‐induced flow maldistribution. © 2010 American Institute of Chemical Engineers AIChE J, 2011
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.
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 | 0.001 |
| 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 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".