Optimization of Friction Stir Weld Joint Quality Using a Meshfree Fully-Coupled Thermo-Mechanics Approach
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Bibliographic record
Abstract
There is currently a need for an efficient numerical optimization strategy for the quality of friction stir welded (FSW) joints. However, due to the computational complexity of the multi-physics problem, process parameter optimization has been a goal that is out of reach of the current state-of-the-art simulation codes. In this work, we describe an advanced meshfree computational framework that can be used to determine numerically optimized process parameters while minimizing defects in the friction stir weld zone. The simulation code, SPHriction-3D, uses an innovative parallelization strategy on the graphics processing unit (GPU). This approach allows determination of optimal parameters faster than is possible with costly laboratory testing. The meshfree strategy is firstly outlined. Then, a novel metric is proposed that automatically evaluates the presence and severity of defects in the weld zone. Next, the code is validated against a set of experimental results for ½” AA6061-T6 butt joint FSW joints. Finally, the code is used to determine the optimal advancing speed and rpm while minimizing defect volume based on the proposed defect metric.
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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) | 0.000 | 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 it