Corrosion surface morphology‐based methodology for fatigue assessment of offshore welded structures
Bibliographic record
Abstract
Abstract This work employed a novel corrosion‐based fatigue model to determine the fatigue life of offshore welded structures to enable the fatigue assessment of welds under corrosive conditions. In addition to the material's ultimate strength, endurance limit, and stress ratio (mean stress effect), the model includes a corrosion factor concept to account for the impact of corrosion pits on the fatigue performance of welded S355 steel, which is the novel contribution in this paper. X‐ray computed tomography scans of corroded S355 specimens in a salt spray chamber were characterized. Surface texture characterization was employed to obtain surface roughness, size, and aspect ratio of corrosion pits. The corrosion factor was determined based on notch and surface fatigue theories using the characterized pit size, aspect ratio, and surface roughness. Fatigue S‐N curves were then predicted for critical pits and compared against the fatigue code DNVGL‐RP‐C203 and experimental data from the literature. The novel approach combining corrosion characterization method with corrosion‐based fatigue model for the prediction of fatigue S‐N curves provided a minor deviation of only 2.8% between predicted and measured data. This approach can potentially be integrated into predictive frameworks for the remaining life assessment of offshore structures.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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".