Microstructural and Mechanical Aspects of AlSi7Mg0.6 Alloy Related to Scanning Strategies in L-PBF
Bibliographic record
Abstract
Abstract AlSi7Mg0.6 alloy is the most widely used cast alloy for aerospace and automotive applications. Therefore, it is essential to explore the effect of scanning strategies parameters on the final part properties in the L-PBF process. The effect of stripes and chessboard strategies parameters such as stripes length, rotation angle, and chessboard island size on mechanical and microstructural properties of L-PBF processed AlSi7Mg0.6 alloy is studied. The evolution of the residual stresses is also investigated in the longitudinal and transverse directions. Cooling rates are also estimated using the cell size within the melt pool. Three distinct regions (i.e., fine, coarse, and heat affected zone) within the melt pool corresponding to different cooling rates could be identified based on Si morphology. The texture of the final material can be tailored by changing the scanning strategies. This study comprehensively presents the results concerning porosity, mechanical properties, crystallographic texture, cooling rates, grain morphology, and residual stresses for additively manufactured AlSi7Mg0.6 alloy.
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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 | 0.000 | 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".