Welding Induced Distortions and Strains of a Built-Up Panel, Experiment and Numerical Validation
Bibliographic record
Abstract
Weld build-up or weld cladding is a welding process in which weld metal can be deposited in order to reclaim the material thickness. In certain applications, welding induced distortions must be controlled while simultaneously minimizing welding induced residual strains. In order to examine the relative effect of the weld build-up region on welding induced distortion and residual strains, two panels were fabricated with either a small 100 × 100 × 3 or large 200 × 200 × 3 mm depression that was subsequently filled by welding. During welding, the strains, displacements, and temperature were continuously monitored in order to compare the transient solution with companion finite element method (FEM) models of the same structures. The coupled thermo-mechanical problem was solved using Goldak Technology Inc., vrsuite program, with the level of agreement of the measured distortions, strains, and temperature profiles dependent on their location and history. Both the numerical and experimental tests showed that despite the differences in the geometry, both panels developed the same strain state, although the large welded patch had greater peak value and larger distortions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".