Empirical models of mechanical behaviour of Al-Si-Mg cast alloys for high performance engine applications
Why this work is in the frame
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Bibliographic record
Abstract
Substructure characteristics in hot worked Al alloys are very important for modeling mechanical properties during hot forming, and also in the product. In contrast to simple grain shape in etched-optical microscopy (EOM), polarized optical microscopy (POM) significantly confirmed subgrain presence in better detail than x-ray diffraction (XRD). Transmission electron microscopy (TEM) revealed the dislocations forming subgrain boundaries (SGB) and dispersed between them; TEM in scanning mode (STEM) could provide microtextures substantiating XRD. Scanning electron microscopy with backscattered image (SEM-EBSI) exhibited substructures more accurately than POM but much less detailed than TEM. Finally, orientation-imaging microscopy (OIM) provided microstructures as in SEM-EBSI and also detailed misorientations; however, omission of very-low angle SGB seen in TEM gave rise to estimates of larger subgrain sizes and misorientations. The field of view is very limited in TEM, but fairly similar in POM, SEM-EBSI and OIM although higher magnifications are possible in the last two. The various techniques are also affected differently by substructure scale (temperature, strain and rate) and composition that also influence specimen preparation. Examination by several techniques is best assurance of correct interpretation of microstructural characteristics.
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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) | 0.001 | 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