Case Study: Engine Bracket Made by Rheocasting Using the SEED Process
Bibliographic record
Abstract
In the context of increasing needs for lightweighting vehicles, semisolid casting of aluminium components is a proven route that can be efficiently applied for automotive parts. Although semisolid forming has not yet reached the market penetration that suits its actual potential, it is currently and efficiently used in many applications around the world on a daily basis. An example of such will be shown. This paper presents a case study on the application of the SEED rheocasting technology for the casting of an engine bracket. The part is made of the widely used AlSi7Mg0.3 alloy and is heat treated in T6 condition to benefit from the enhanced mechanical properties made possible by semi-solid forming. Throughout the development phase, different aspects associated with semisolid casting, such as slurry condition, gate design, mold filling behaviour, lubrication, blistering and others, were addressed successfully. In the final, the combination of the SEED technology with a thorough development process and the specific casting rules for semi-solid forming led to actual commercial production and contributed to weightsaving on the actual part as compared to a former design made from high pressure die casting.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".