Characterisation of welded joints produced by FSW in AA 1100–B<sub>4</sub>C metal matrix composites
Bibliographic record
Abstract
The feasibility of friction stir welding for joining AA 1100 based metal matrix composites reinforced with B4C particulate is studied for 16 and 30%B4C volume concentrations. For both composites, friction stir welding has a significant influence on the particle size distribution and the matrix grain size. For the 16% composite, the average particle size decreases after welding by ∼20% and the grain size from 15 to 5 μm as measured in the weld nugget. Tensile testing of welded joints showed up to 100% joint efficiency for both annealed AA 1100–16%B4C and AA 1100–30%B4C composite materials. However, if the ultimate tensile strength values of all the studied composites are similar at ∼130 MPa, then the weld ductility is higher for the annealed materials. Furthermore, it was observed that varying the welding speed between 100 and 275 mm min−1 does not influence the tensile properties and the particle size distribution in the nugget.
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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".