Effect of Dispersing In Situ Al-Cu Intermetallic Compounds on Joint Strength in Friction Stir Welding of AA3003-H18 Sheets
Bibliographic record
Abstract
In this study, friction stir welding (FSW) was employed to join AA3003-H18 sheets by incorporating in situ Al-Cu intermetallic compounds within the stir zone. The FSW process was carried out under three distinct conditions: (I) without applying powder, (II) by introducing Cu powder, and (III) by incorporating Cu-Al mixed powder (50 vol.% Cu, 50 vol.% Al). The powder was embedded into the gap between two sheets. Subsequently, two-pass FSW, involving both forward and backward movements, was conducted with a rotational speed of 1200 rpm and traverse speed of 100 mm/min across all three experimental conditions. In the second and third conditions, the formation of in situ intermetallic compounds occurred through a solid-state reaction between Cu particles and Al within the stir zone. Examination of the stir zone through optical and electron microscopic studies revealed that the utilization of Cu-Al mixed powder resulted in finer and more uniformly distributed Cu clusters and Al-Cu intermetallics than samples welded with Cu powder alone. Notably, the stir zone of samples incorporating Cu-Al mixed powder exhibited finely dispersed, completely gray Al-Cu intermetallic particles, whereas those with only Cu powder displayed predominantly coarse core-shell particles in the microstructure. The introduction of Cu-Al mixed powder during FSW resulted in a stir zone with an average hardness of 74 HB, showing a 14% increase compared to the cases where Cu powder alone was added (65 HB). Tensile tests, conducted in both transverse and longitudinal directions on the FSWed samples, did not exhibit a consistent trend across the three mentioned conditions. Transverse tensile strength consistently ranged between 107 and 110 MPa, with joint efficiency varying from 52% to 54%. However, the longitudinal tensile strength of the joint with added Cu-Al mixed powder (158 MPa) surpassed those welded with Cu powder alone (134 MPa).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".