Understanding T-Ingot Horizontal DC Casting Using Process Modelling
Bibliographic record
Abstract
Horizontal continuous casting process has been successfully implemented in Alcan for the production of T-ingots of primary aluminium and foundry alloys. Ability to achieve increased productivity targets and reduce production costs relies on a fundamental understanding of key process characteristics and operating parameters. Thanks to the long-standing experience in vertical DC Casting, numerical modelling appeared as a powerful approach to understand phenomena related to metal flow, solidification and ultimately defect formation. As part of a collaborative R&D program, a global model of horizontal casting process, integrating specialized sub-models on critical aspects of the process such as meniscus dynamics, is being developed. Experimental characterization of primary and secondary cooling is performed in parallel with modelling work to provide the information necessary to properly characterize mould heat transfer. This paper will present the development of a 3D process model of T-ingot casting along with its application to solve specific process challenges that have emerged during the first years of production in the plant.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".