Modeling of Thermo-Chemo-Mechanical Properties of Anode Mixture during the Baking Process
Bibliographic record
Abstract
In the Hall-Héroult process, prebaked carbon anodes are utilized to produce primary aluminium. The quality of the anode plays a crucial role in the efficiency of electrowinning primary aluminium. In the production of anodes, the anode baking is considered as the stage most frequently causing anode problems. During the baking process, the anode undergoes complex physicochemical transformations. Moreover, the anode at a lower position, imposed by loading pressures from upper anodes, will creep during this process. Thus, the production of high-quality anodes demands efficient control of their baking process. This paper aims to investigate the thermo-chemo-mechanical properties of the anode paste mixture at high temperatures. These properties include kinetic parameters of pitch pyrolysis such as the activation energy and the pre-exponential factor, the thermal expansion coefficient (TEC) and relevant mechanical parameters related to the elastic, the viscoelastic and the viscoplastic behaviours of the anode. For this purpose, experiments consisting of the thermogravimetric analysis, the dilatometry and the creep test were carried out. Based on the obtained results, the forementioned parameters were identified. Relevant mechanical parameters were expressed as a function of a new variable, called the shrinking index, which is related to the volatile released in open and closed pores of the anode. This variable would be used to highlight the chemo-mechanical coupling effect of the anode mixture. New insights into the phenomena such as the expansion due to the increase of the pore pressure and the chemical shrinkage of the anode during the baking process were also gained in this work. These investigations pave the way for modeling the thermo-chemo-poromechanical behaviour of the anode during the baking process.
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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".