Synthesis and generalisation of welding fundamentals to design new welding technologies: Status, challenges and a promising approach
Why this work is in the frame
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Bibliographic record
Abstract
The present paper addresses the renewed need to focus on the physics of welding to realise the full potential of the latest welding technologies which include fibre and disc lasers, friction stir welding and inverter power supplies. The approach to understanding, synthesis and generalisation in other engineering branches is reviewed, highlighting the central role of handbook type solution in the conceptual design stage. It is shown that the multiphysics and multicoupled aspects of welding exceed the capabilities of other engineering approaches and the methodology of scaling is proposed as a promising alternative. The application of scaling to friction stir welding is shown through an example in which the maximum temperature in the metal is generalised into a power law, experimental and numerical data are synthesised into a general correction factor, and secondary effects are captured as dimensionless groups.
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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 | 0.001 |
| 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 | 0.001 |
| 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