Modelling Induction Heating of Aluminium Sheets for Hot Stamping
Bibliographic record
Abstract
Hot forming of aluminium sheets enables the forming of complex shapes with high-strength alloys due to increased formability at elevated temperatures. A fast, uniform and accurate heating method is required to meet the narrow solution heat treatment window from 460 to 490 °C for AA7xxx alloys before forming. Heated plates and convection furnaces are commonly used in hot forming, but require large equipment and can have medium to long cycle times. Induction heating, which uses an alternating current in a coil surrounding the workpiece, could provide shorter heating times. However, induction heating requires a part-specific coil and can exhibit significant temperature gradients over the blank. Multi-physics electromagnetic and thermal simulation can be used as a design tool to help achieve the target temperature uniformity. In this study, induction heating of an irregular aluminium blank was modelled and validated with experimental data. Methods to improve the temperature uniformity were also tested numerically.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".