Evaluation of local mechanical properties and correlation with tensile properties of AA7075-T6 friction stir welds via shear punch testing
Bibliographic record
Abstract
Friction stir welding, used for joining light alloys in the aeronautics industry, generates an asymmetric thermomechanical cycle along the weld line, leading to uneven heat input and significant variations in mechanical properties. To evaluate these variations, the shear punch test offers an effective solution, especially when sample size or constraints limit traditional tensile testing. This test, based on the blanking process, accommodates various grain sizes and sample thicknesses, making it versatile for diverse microstructures. Additionally, it produces mechanical curves similar to tensile tests, enabling a reliable correlation between local and global mechanical properties in welded joints. The aim of this work is to establish a correlation between local mechanical properties obtained through shear punch testing and global properties derived from tensile testing in different zones of a welded joint. A correlation between ?ys, ?ys, and ?us with ?us was derived based on the von Mises criterion and the Power Law Strain Hardening (PLSH). The yield strength ?ys is expressed as 1.73?ys, determined at a 0.2% offset. For the ultimate tensile strength, the relationship ?us = (1/Sf).?us is applied, where Sf depends on the hardening exponent n obtains from tensile test. In this study, n? values derived from the shear punch test data were used to calculate Sf allowing the correlation to be extended to regions where tensile testing strength coefficients, such as strain hardening exponents n, were unavailable. This approach highlights the value of shear punch testing as a tool for evaluating local mechanical properties in welded joints. In conclusion, the strain hardening exponent from the shear punch test is approximately 1.3 times that from tensile testing. The highest n? value (0.14099) was in the TMAZ retreating side, The maximum ultimate strength (441.77 MPa) was found in the nugget zone, while the lowest value, 278.90 MPa, occurred in the HAZ advancing side. The (?us/?ys) ratio peaked at 1.82 in the TMAZ retreating side, exceeding the nugget zone by over 20%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".