Evaluation of Small-Scale Thin Wall AlSi7Mg Alloys LPBF Coupons under Extreme Low Cycle Fatigue Regime
Bibliographic record
Abstract
The recently developed process of additive manufacturing of aluminum alloys via laser powder bed fusion (LPBF) has the capability to build parts with complex geometries, which can lead to potential benefits in manufacturing industries. The adoption of intricate thin wall structures is restrained by the lack of reliable mechanical property data and understanding of the failure sequence in extreme cyclic loading conditions. The results show that the LPBF AlSi7Mg thin-walled specimens under an Extreme Low Cycle Fatigue (ELCF) regime for 0.1 mm to 0.8 mm design thin wall thickness variation attained results of 1 to 20 number of cycles to failure (Nf) in as-built, stress-relieved annealing and T5 heat treatment conditions. The present work also explores the factors linking GD&T, and heterogeneity of the thin-walled alternate cyclic bend fatigue-tested specimens.
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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".