General thermomechanical model of FSW based on a characteristic temperature for deformation and heat transfer
Bibliographic record
Abstract
Abstract This paper presents a coupled model of heat transfer and plastic deformation in friction stir welding (FSW), accounting for the temperature profile in the substrate near the pin. This approach is analogous to the boundary layer analysis in fluid mechanics and is based on the methodology of scaling and calibration based on published data. A model focusing on common conditions in FSW, such as relatively slow translation and high rotation velocities, a thin shear layer and the influence of the shoulder on the maximum temperature was reformulated. This paper extends previous work by considering the heat flow into the pin and an improved criterion for determining the temperature at the edge of the shear layer. The results are a set of updated closed-form expressions for the maximum temperature, the thickness of the shear layer, the shear stress around the pin, torque and thermal effect of the shoulder, applicable to all metals. The predictions from this model are verified against a comprehensive database of published experiments. Applications of this model also include the accelerated determination of procedure variables and the generalization of maps of process limits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".