Comparative analysis of the high-temperature tensile properties of laser-welded AA5052 and AA6061 for automotive applications
Bibliographic record
Abstract
This study investigates the high-temperature tensile properties of laser-welded AA5052-H36 and AA6061-T6 aluminum alloys, utilizing experimental and statistical analysis. Tensile tests were conducted at temperatures ranging from 25°C to 300°C at corresponding strain rates of 0.01 and 0.1 s −1 . The results indicate that AA5052-H36 exhibits superior mechanical strength compared to AA6061-T6, with a near-linear decrease in ultimate tensile strength, showing a reduction of approximately 60% from 273 MPa at 100°C to 108 MPa at 300°C. AA5052-H36 also shows consistent increases in fracture strain across the tested conditions, with fracture strain rising from 0.14 at 100°C to 0.37 at 300°C. In contrast, AA6061-T6 displays a non-linear decline in UTS, dropping by 51%, from 220 MPa at 100°C to 110 MPa at 300°C, and an increase in fracture strain from 0.05 at 100°C to 0.07 at 300°C. This non-linear behavior is linked to the dissolution of β ″ phases and the subsequent precipitation of β ′ phases, as revealed by the differential scanning calorimetry curve. Statistical analysis confirms that temperature is the dominant factor influencing tensile performance, with notable contributions from phase transformations observed in the DSC curve. Energy absorption analysis highlights the advantages of AA5052-H36, which absorbs considerably more energy before failure compared to AA6061-T6, due to its greater plastic deformation capacity. AA5052-H36 absorbs up to 13.3 J at 250°C, while AA6061-T6 absorbs a maximum of 3.3 J at the same temperature. Both alloys show maximum energy absorption at 250°C, with increasing temperature leading to a rise in absorbed energy up to 13.3 J. However, beyond 250°C, the energy absorption decreases substantially. In conclusion, while AA5052-H36 may offer superior performance in high-temperature tensile loading compared to AA6061-T6, the choice of alloy for applications above 250°C should be made with careful consideration of the trade-offs, including strength, corrosion resistance, and manufacturability, to prevent possible creep-related failures.
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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 | 0.001 |
| 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) | 0.002 | 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".