Microstructure and Mechanical Properties of an Ultrasonic Spot Welded Aluminum Alloy: The Effect of Welding Energy
Bibliographic record
Abstract
The aim of this study is to evaluate the microstructures, tensile lap shear strength, and fatigue resistance of 6022-T43 aluminum alloy joints welded via a solid-state welding technique-ultrasonic spot welding (USW)-at different energy levels. An ultra-fine necklace-like equiaxed grain structure is observed along the weld line due to the occurrence of dynamic crystallization, with smaller grain sizes at lower levels of welding energy. The tensile lap shear strength, failure energy, and critical stress intensity of the welded joints first increase, reach their maximum values, and then decrease with increasing welding energy. The tensile lap shear failure mode changes from interfacial fracture at lower energy levels, to nugget pull-out at intermediate optimal energy levels, and to transverse through-thickness (TTT) crack growth at higher energy levels. The fatigue life is longer for the joints welded at an energy of 1400 J than 2000 J at higher cyclic loading levels. The fatigue failure mode changes from nugget pull-out to TTT crack growth with decreasing cyclic loading for the joints welded at 1400 J, while TTT crack growth mode remains at all cyclic loading levels for the joints welded at 2000 J. Fatigue crack basically initiates from the nugget edge, and propagates with "river-flow" patterns and characteristic fatigue striations.
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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".