Influence of pin profile on formability of friction stir-welded aluminum tailor-welded blanks: an experimental and finite element simulation analysis
Bibliographic record
Abstract
In sheet metal forming processes, the forming limit diagram is frequently employed as a criterion for predicting necking initiation. This is one of the most useful and effective methods for the evaluation of the formability of tailor-welded blanks. The goal of this study was to determine the formability of friction stir-welded (FSW) aluminium alloy 6061-temper 6 (AA6061-T6) and aluminium alloy 2017-temper 6 (AA2017-T6) by employing five dissimilar tool pin profiles. To evaluate the limiting dome height, five different combinations of dissimilar blanks were used in experimental and simulation experiments. Material characteristics such as density, elastic modulus, and all multilinear behaviors of blanks were manually assigned for simulation from the test results of true stress versus true strain plots. The punch with die supports was considered as a rigid body, whereas the metallic blanks were considered as plastic material. To carry out the simulation, the entire blank was divided into three zones. The results obtained from the experimental and simulation results showed that the straight square tool pin profile is the optimal tool pin profile for the formability of FSW AA6061-T6 and AA2017-T6. The tested height values obtained from the limiting dome height were 20.5 and 20.9 mm in experimentation and simulation, respectively. The straight cylindrical tool pin profile exhibited the worst formability properties in both experimentation and simulation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".