Effect of Particle Size Distributions and Shapes on the Failure Behavior of Dry Coke Aggregates
Bibliographic record
Abstract
Carbon anodes participate in chemical reactions to reduce alumina in the Hall-Héroult process, of which coke aggregates make up a major part. The failure analysis of coke aggregates not only leads to a better understanding of the deformation mechanisms of anode paste under compressive loading but also can identify potential causes of structural defects in carbon anodes, such as horizontal cracks. The coke aggregates are composed of particles with different size distributions and shapes, which may strongly affect the failure behavior of the anode during compaction. In this paper, the effects of particle size distributions and shapes on the mechanical behavior and the failure of coke aggregates are investigated using the discrete element method modeling technique. The numerical results reveal that, although the mechanical behavior of coke mixtures is generally dependent on larger particles, the presence of fine particles in the coke aggregates reduces fluctuations in the stress-strain diagram. In addition, the rolling resistance model is employed as a parameter representing the effect of particle shape. It is shown that the rolling resistance model can be an alternative to the overlapped spheres model, which has a higher computational cost than the rolling resistance model. The second-order work criterion is used to evaluate the stability of the coke aggregates, the results of which indicate that the addition of fine particles as well as increasing the rolling resistance between the particles increases the stability range of the coke aggregates. Moreover, by using the analysis of micro-strain contour evaluations during the compaction process, it is shown that, both by adding fine particles to the coke mixture and by increasing the rolling resistance between the particles, the possibility of creating a compression band in the coke aggregates is reduced. Since the presence of the compaction bands in the anode paste creates an area prone to horizontal crack generations, the results of this study could lead to the production of carbon anodes with fewer structural defects.
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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 | 0.001 |
| 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) | 0.001 | 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".