Overlap laser welding of 5052-H36 aluminum alloy: experimental investigation of process parameters and mechanical designs
Bibliographic record
Abstract
Abstract In this study, the laser welding process is used to join 1.6-mm-thick AA5052-H36 sheets in an overlap joint configuration. Both pulse and oscillation laser beam welding were investigated for the first laser pass. Oscillation beam laser welding in continuous-wave mode show more stable and sound weld with no porosity defects compare to pulse wave (PW) mode. The adopted welding power, speed, frequency, and defocus are 8 kW, 6.5 m/min, 150 Hz, and + 8 mm, respectively. The obtained stitch welds are defects free (blowholes, micro-cracks, or porosities). A circular oscillation ramp-up/ramp-down PW mode is adopted for a second laser surface re-melting (LSR) pass. The corresponding welding power, speed, frequency, and defocus are 5 kW, 2.5 m/min, 500 Hz, and + 15 mm, respectively. Shear tests are then performed to evaluate the mechanical properties of single lap joints (SLJ) for different stitch weld shapes, 2 gap tolerances (0 and 0.5 mm), as well as with/without LSR pass. The best tests’ reproducibility and highest dissipated energies (~ + 42% when compared to the perpendicular direction) are obtained when the stitch weld direction corresponds to the loading direction. The second LSR pass provides more aesthetic joints with higher shear resistance (~ + 1% to + 3%) due to a decrease in the weld surface underfill and undercut imperfections of the stitch weld. The part-to-part gap leads to higher shear resistance (~ + 20%) owing to 2 main reasons: larger welding surfaces at the joint interface and higher hardness of the fusion zone. These findings are of great value for including laser welding technology in the automotive and surface transportation industries. Graphic abstract
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".