Experiments and Finite Element Model Results on the Deformation Response of an X80 Weld Zone
Bibliographic record
Abstract
The modification of microstructure and mechanical properties of steels after a welding process has received considerable attention in the literature. In the case of welding HSLA steels for pipeline applications, the filler metal employed usually is overmatched (i.e. higher strength) compared to base metal to avoid fracture in this zone of the weld. For this reason, considerable work has emphasized microstructure evolution in the heat affected zone and the associated modification of mechanical properties in this region. In this study, the combined effect of microstructure/property distribution and the geometry of the weld are examined to understand where localization, necking and fracture occurs under tensile loading of a laboratory weld. To achieve that, a series of tests were conducted on two different types of X80 submerged arc welds: Single and tandem wire welds. The tensile samples were machined transverse to the weld on plates 16 mm thick. Samples were tested where the geometry of the weld was preserved (i.e. the weld cap is left intact) and where the cap was removed in order to remove its effect. The local plastic strain during testing was determined using the Digital Image Correlation technique (DIC). For the single wire weld, the influence of the cap geometry seems to be of second order, as the fracture location is the same with or without caps. But for the tandem wire welding, the fracture location is very different depending on the geometry: In the case where caps are kept, the fracture occurs outside the HAZ, in the base metal suggesting the important interplay between local mechanical properties and the weld geometry. A Finite Element Model (FEM) was developed to gain insight into the geometrical effects on the local strain field distribution. The experimental strain distribution is compared to the FEM results to rationalize the effect of geometry. The model results are then used to discuss the position of fracture for the different samples, which correspond well to the experimental results.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".