Study on Estimation Method of the Welding Deformation for Thick Plate Fillet Welding
Bibliographic record
Abstract
In order to manufacture I section of bridge, the fillet welding of the both sides for the web is conducted simultaneously, or conducted one side sequentially. The angular distortion will occur in the case of simultaneous welding, the leaning deformation on the flange to the first welding side will occur in the case of sequential welding for the thick plate. Compared with the angular distortion, it is difficult to correct the leaning deformation on the flange. If we can estimate the amount of the leaning deformation on the flange to first welding side, we will be able to set the flange lean to the second welding side before welding and keep the flange right angle to the web without correcting the deformation after welding. We conducted some cases of experiment and thermal elastic-plastic analysis for I section with sequential fillet welding. From the results, we developed the program for estimating the leaning deformation on the flange with tandem submerged arc welding method sequentially, and we applied to the actual bridge manufacturing. Consequently, we reduce the correcting work drastically, and achieve the cost reduction in production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".