Fracture Characteristics and Analysis in Dissimilar Cu-Al Alloy Joints Formed via Electromagnetic Pulse Welding
Bibliographic record
Abstract
The aim of this study was to identify and analyze the fatigue fracture characteristics of dissimilar Al 6061 to Cu (UNS C11000) lap joints made with ultrafast electromagnetic pulse welding (EMPW) via fractography, stress analysis and finite element simulation. It was observed that EMPW generated an annular (or ring-shaped) bonding area, with weld zones and a central non-weld zone when viewed from the cross section. Two types of failure modes occurred in relation to the cyclic loading levels: base metal fracture or transverse through-thickness (TTT) crack growth at a higher loading level, and joint interfacial failure at a lower loading level. In the interfacial failure, fatigue crack initiated from the outer edge of annular welding area, and propagated to form an approximate elliptical boundary. Fatigue crack propagation was characterized by fatigue striations existing in discrete areas on the fracture surface. This was attributed to a coupled role of shear and normal stresses present in a tensile lap shear sample due to the bending moment caused by the inherent misalignment. The final rapid fracture started from elliptical boundary with elongated shear dimples. Both theoretical stress analysis and finite element model revealed the maximum stress and stress concentration along the outer edge, where fatigue crack initiation occurred.
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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 | 0.000 | 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".