Chemistry optimisation to improve casting durability of engine blocks
Bibliographic record
Abstract
The research contained herein reviews an alternative Al–Si–Cu alloy that provides the fatigue durability that would be nearly comparable to the 356 or the 319 alloys (having integrated chill), while having comparable or lower associated raw material and processing costs. A total of forty-three V8 engine blocks were produced with an Al–9Si–1Cu alloy, assessed and compared to the production version of the same engine block casting that uses the 319 alloy (Al–7Si–3·5Cu). The casting process used to manufacture the engine blocks was the Cosworth Precision Sand Process. This comparison to the production variant of the V8 engine block includes a detailed microstructure assessment (secondary dendrite arm spacing λ 2, secondary phase distribution/type and porosity), room temperature tensile testing, elevated temperature fatigue staircase plots and hardness measurements. The observation found from the aforementioned analysis was that the Al–9Si–1Cu alloy has lower porosity and, as a consequence, was able to show a 40% increase in the elevated temperature fatigue staircase plot when compared to the same plots made from regular production.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".