Region-Specified Ratcheting Behavior of API X80 Welded Joint Under Uniaxial Cyclic Loading
Bibliographic record
Abstract
Evaluation of mechanical performance of different regions can be difficult by using standard size samples due to the size limitation of weld metal and heat-affected zone (HAZ). At first, the microstructure of different regions was characterized and quantified by Scanning Electron Microscope, which indicate that the pipeline steel is a typical acicular ferrite steel. In this study the deformation behavior of different regions (base metal, weld metal and heat affected zone) in a welded joint of API X80 pipeline steel were studied by conducting uniaxial loading tests on miniature specimens with the cross section of 2×0.5mm and gauge length of 9mm. From the results of uniaxial tension in base metal and weld metal it is shown that the welding is overmatching. Compared to the base metal, the coarse grained HAZ exhibits a lower strength, while the fine grained HAZ exhibits a higher strength. Under near zero-to-tension cyclic stress loading, all regions of the welded joints exhibit progressive accumulation of plastic strain. Under the same stress level, the base metal shows the fastest ratcheting strain accumulation, which is the result of lower strength than other regions. This fact may indicate that the ratcheting behavior of the overall welded joint is highly dependence on that of base metal for the present case. But when under the same normalized stress level (σ = σ/σYS), the fine grained HAZ has the highest ratcheting strain accumulation, while the coarse grained HAZ has the lowest ratcheting strain accumulation, which reveals that the intrinsic resistance to ratcheting is yield strength dependent.
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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".