Effects of grain refiner additions (Zr, Ti–B) and of mould variables on hot tearing susceptibility of recently developed Al–2 wt-%Cu alloy
Bibliographic record
Abstract
The hot tearing susceptibility of the new Al–2 wt-%Cu based alloys prepared using Zr and Ti–B additions was tested using the constrained rod casting mould under different mould variables. The 206 alloy type was used to evaluate the results obtained from this new alloy. It was found that the hot tearing susceptibility of the alloys under investigation decreases proportionally as the mould temperature is increased; thus, the hot tearing susceptibility of the Al–2 wt-%Cu and 206 alloys decreases from 21 for both the alloys to 3 and 9 respectively as the mould temperature is increased from 250 to 450°C. This beneficial effect of elevated mould temperatures may be attributed to a reduction in the contraction strain rate and in the porosity level. Grain refinement additions of Ti–B or Zr–Ti–B enhance the hot tearing resistance of the Al–2 wt-%Cu to a significant level.
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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 | 0.000 | 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) | 0.001 | 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".