The Semi-Solid Forming of an Improved AA6061 Wrought Aluminum Alloy Composition
Bibliographic record
Abstract
The semi-solid forming (SSF) of aluminum alloys offers many advantages over conventional casting processes. Nevertheless, the semi-solid forming is still far from its full commercial potential and mainly used in specific niche markets. The market positioning requires simple, low cost, and versatile SSF processes that are capable of processing a wide range of alloy composition including wrought alloy compositions. However, wrought alloys must be adapted to obtain the desired semi-solid processing ability and proper mechanical properties. The processing of these attractive alloys with the SEED process offers the possibility to better target specific applications and customers’ needs. In the present paper, the alloy development of AA-6061 aiming to minimize the hot tearing propensity during forming process is reported. An overview of the industrial SEED process used to produce the semi-solid AA-6061 feedstock is presented. The mechanical properties of the cast parts subjected to a specific heat treatment were evaluated. As part of the joint effort between Alcan International Limited and the National Research Council of Canada (NRC), the fatigue results obtained from the semi-solid AA-6061 die cast parts will be also reported.
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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 | 0.000 |
| 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 | 0.001 |
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".