An inverse approach for the prediction of the temperature evolution during induction heating of a semi-solid casting billet
Why this work is in the frame
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Bibliographic record
Abstract
An inversion technique is developed to recover the temperature distribution along the radius of a cylindrical billet at the end of the induction heating phase in a semi-solid process using the surface temperature measurement. In the process, a metallic billet is first heated in an induction furnace until it reaches a semi-solid state (partially liquid and partially solid). Then, it is injected into a die and kept there until it solidifies. Subsequently, the die opens, the part is ejected and the cycle starts again. The temperature distribution within the billet at the end of the heating phase is of prime importance for the success of the process and the quality of the product. The inverse algorithm is applied to experimental data recorded by an infrared camera on the side of an aluminium billet heated in an IHS induction heating station. The temperature distribution in the billet is predicted for different heating power levels.
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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 it