Microstructure, texture and fatigue performance of friction stir welded dissimilar magnesium alloy joints
Bibliographic record
Abstract
The stress-controlled fatigue of dissimilar friction stir welded AZ80/AZ61 and AZ80/AZ31 magnesium alloy joints was studied. Fatigue testing targeting the critical stir zone — base metal interface revealed endurance limits of 90 MPa for AZ80/AZ61 welds and 70 MPa for AZ80/AZ31 welds. Within the range 60–90 mm/min, welding speed did not affect the endurance limits, though lower speeds produced more homogeneous microstructures and reduced data scatter in AZ80/AZ61 joints. The superior fatigue resistance of AZ80/AZ61 welds is attributed to their stronger and more plastically uniform microstructure, which supports higher stress levels and sustains more cycles before crack nucleation. Cyclic stress–strain analysis shows that AZ80/AZ31 joints exhibit higher hardening rates under cyclic loading compared to AZ80/AZ61 joints, however, both joint types demonstrate significantly reduced hardening compared to monotonic tensile deformation. This behaviour is attributed to low plastic strains during cycling, texture effects inhibiting basal slip, and reversible twinning–detwinning mechanisms. Electron backscatter diffraction analysis revealed substantial texture evolution in the stir zone (SZ), thermomechanically affected (TMAZ) and heat-affected zones (HAZ), with mechanical twinning contributing to grain refinement and mechanical anisotropy. Transmission electron microscopy revealed a complex fatigue dislocation microstructure characterized by networks of basal and non-basal dislocations, with fine dislocation loops and debris present at all stress amplitudes. The density of these defects increased systematically with stress amplitude, providing insight into the cyclic deformation mechanisms governing fatigue life. • Alloy compatibility across dissimilar joints dictates fatigue mechanisms. • Cyclic hardening lower than monotonic due to twinning–detwinning influence. • Microstructure analysis and modelling reveal divergent evolution pathways in joints. • Dislocation networks scale with stress, representing a novel fatigue damage metric.
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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) | 0.000 | 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 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".