Friction Stir Welding on Light-Weight Metal - Aluminum Alloy Al6061
Bibliographic record
Abstract
Friction stir welding (FSW) is a solid state joining process in which metals are joined together using frictional heat and severe plastic deformation. The heating and the mixing of the metals is performed using a hardened tool with a shoulder and pin. FSW of lightweight metal alloy Al6061 has been carried out in the present study. For welding aluminum the parameters used were a constant tool rotation speed of 1600 rpm and varying tool translation speeds of 250, 500, 750 and 1000 mm/min. The welded coupons were characterized for microstructural observations and mechanical properties such as tensile and Charpy impact properties. The tensile and impact properties were studied at two different temperature namely, room temperature (RT) and 300°C. The FS welded aluminum specimens showed 86% – 98% tensile yield strength, in comparison to the base material at RT. At 300°C, the yield strength was observed to be 85% to 93% of the base material value. For the impact properties, the Al specimens showed 60% – 140% specific impact energy, in comparison to their respective base materials. Based on the mechanical properties and microstructural examination, the optimal weld parameter was identified as 1600 rpm and 250 mm/min which is dependent on the tool pin and shoulder design utilized in the study.
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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) | 0.002 | 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".