Static Mechanical Property Criterion Determined under Different Extent of Hot Crack Index of High-Strength Aluminium Autogenous Laser Welds
Bibliographic record
Abstract
Nowadays, vehicle electrification is growing at a fast pace due to stringent environmental regulations on carbon emissions in North America. The manufacturing of E-mobility battery components such as enclosures evolves at the same trend and many new design concepts are put in place. As health and safety in electric vehicles are taken very seriously by OEMs, the enclosures are still heavy but are likely to become more lightweight in years to come, using high-strength aluminium alloys as one of the potential solutions, as weight directly affects the admissible range. In this paper, four (4) different aluminium wrought alloys (AA6061, AA6010, AA7020 S and AA7075) were autogenously laser-welded using various parameters and inspected through 2D X-ray tomography. A hot crack index (HCI), using optical microscopy, was defined in order to quantify the internal extent of hot cracks. Static mechanical butt joint tensile tests were provided to dictate a mechanical property criterion regarding the extent of HCI. This revealed that uniform elongation is a good predictor of the extent of HCI in terms of static mechanical behavior. These findings could eventually be used to define a threshold value toward a safe number of hot cracks in laser welds.
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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 | 0.001 |
| 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) | 0.001 | 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".