Lap joint dissimilar welding of aluminium AA6061 and galvanized iron using TIG welding
Bibliographic record
Abstract
In this paper, aluminium AA6061-O and galvanized iron were lap-joined using tungsten inert gas (TIG) welding. The experiments were conducted using Si-rich filler metals ER4043 (Si 5 wt.%) and ER4047 (Si 12 wt.%). The mechanical properties and the microstructure of the samples were analysed using dye penetrant non-destructive tests (NDT), optical microscope observation and shear tests. All samples showed good quality joints, with Al-GI specimens showing better quality. Through optical microscope observation, the intermetallic compounds (IMC) of specimens using ER4043 fillers show a thin IMC layer ranging from 4 μm to 7 μm, compared to ER4047 samples which ranged between 20 μm and 40 μm. The shear tests show that the GI-Al group fractured at the IMC layer, while the Al-GI group fractured at the FZ-HAZ aluminium matrix. The highest shear strength value obtained was 89.82 MPa and 76.59 MPa for the Al-GI and GI-Al positions, respectively. It can be concluded that the GI-Al (galvanized iron on top and aluminium at the bottom) configuration with filler type ER4043 (Si 5 wt.%) has the optimum mechanical properties with a thin IMC layer and tensile strength of 76.59 MPa.
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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 | 0.001 | 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".