Effect of material inhomogeneity on fracture modes in aluminium–steel resistance spot welds
Bibliographic record
Abstract
Abstract Resistance spot welding (RSW) is attractive for joining dissimilar materials, especially, aluminium to steel in automotive body. The direct joining of aluminium to steel forms an intermetallic compound (IMC) layer at their interface that dominates mechanical behaviour of the joint. A new formula was developed that considers material inhomogeneities such as the different mechanical properties in the weld such as base metal, heat affected zone (HAZ) and the weld nugget to accurately calculate the minimum weld nugget diameter required to enable pull‐out fracture. The shear strengths of weld regions such as the HAZ and IMC were directly measured and used as inputs to this new formula. The new formula was validated using experimental measurements from six combinations of aluminium–steel welds in comparison with analogous aluminium–aluminium welds. The new derivation was able to accurately predict fracture modes for all material combinations.
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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 | 0.001 | 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".