Characterization of Heat Transfer Coefficient of Lightweight Alloys in Kirksite Dies
Bibliographic record
Abstract
Abstract The heat transfer coefficient (HTC) is an important parameter in the finite element (FE) modelling of warm and hot forming operations. The HTC, among other parameters, governs the FE model predictions for the cooling rate within the blank and the resulting constitutive behaviour and formability. In the current work, the HTC of two aluminum alloys (AA5182-O and AA7075-T6) and one magnesium alloy (ZEK100) is characterized. Blanks were heated in a convection furnace and subsequently quenched in a set of kirksite dies under various contact pressures. Kirksite is a zinc-based alloy commonly used in prototype tooling. The temperature-time (T-t) profile of the blanks and die were measured during each quenching experiment. The resulting T-t profiles were input into a Matlab script, which calculated the HTC using an iterative regression technique.
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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 | 0.001 | 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".