Changes in residual stresses caused by an interruption in the weld process of ships and offshore structures
Bibliographic record
Abstract
Residual stresses are present in welded stiffened steel plates that are used to construct ships and other offshore structures. These locked-in stresses can exceed the yield stress of the parent plate material. Interruptions due to stop and restart in the welding process in these structures cannot be eliminated completely. It is suspected that weld interruptions are detrimental, though the effect of an interruption on the residual stress distribution is not well understood. Hence, this study was undertaken to determine the change in the residual stresses due to various stop durations in the weld process. The stop time varied from 10 to 60 seconds and the resulting stresses were compared with those observed when the weld is not interrupted. Neutron diffraction was used to determine the residual stresses. The study revealed that, compared to the residual stresses observed for a continuous weld, immediately before the stop location there is a decrease in the resulting residual stresses which is balanced by a concomitant increase immediately following the restart of the weld. The difference between the low and the high stress points in the distribution increased as the stoppage time (duration) increased. This paper presents the specimen design, specimen preparation and construction, test method, and test data obtained for four steel plate specimens.
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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 | 0.000 |
| 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) | 0.001 | 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".