The onset of instabilities and finite amplitude waves in a model of aluminum reduction cells with nonuniform cathode current
Bibliographic record
Abstract
In aluminum reduction cells, the electric current density at the cathode is seldom uniform. This may be due to a variety of reasons. One of the reasons is that a mass of undissolved alumina may get enrobed by the cryolitic bath, and this mix freezes due to the decrease in temperature below the liquidus point. Thus, an electrically resistive solid layer (“mud”) is formed at a part of the cathode. This leads to horizontal electric currents in the liquid aluminum layer, and their magnetohydrodynamic (MHD) interaction with the vertical magnetic field induces a rotating flow of aluminum. This may cause undesirable MHD instabilities. A quasi-two-dimensional model for the laboratory facility has been presented. The results show that the dominating feature of the flow is a depression of the free surface of the liquid metal above the mud spot. This is due to strong rotation of the liquid metal around the mud spot, which causes the centrifugal force. Other effects may include superimposed conventional MHD instability, which manifests itself in a rotating interface, modulated waves, reflection of the waves from the corners of the domain, sloshing, etc. It has been shown that small mud spots do not affect the cell stability, while the large ones may cause such deep depressions that the centrifugal force completely removes the liquid metal above the spot.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".