Compressive Strain Capacity Reliability of Hydrogen-Carrying Steel Pipelines in Permafrost
Bibliographic record
Abstract
Abstract In strain-based assessment, the imposed strains on the pipeline due to ground displacement are assessed as strain demands. The pipeline capacity to resist these imposed demands are termed as strain capacities. The tensile strain capacity is often governed by the strain capacity of the girth welds, and the exceedance of tensile strain capacity can lead to a full-bore rupture. In contrast, the imposed compressive strain demand initiates the local buckling of the pipeline, and the compressive strain capacity (CSC) is defined as the average strain across the buckling location at the initiation of the buckle. In the presence of the pressurized environment of hydrogen and hydrogen-methane blends, previous studies have shown that the carbon steels may experience significant reduction in post-yield ductility along with embrittlement and reduction in material toughness. As the CSC of steel pipelines is sensitive to the post-yield strain hardening and ductility of the material, there may be reduction in CSC in hydrogen pipelines. However, there haven’t been any systematic studies to understand the sensitivity of CSC to the ductility reduction in the carbon steels and amount of tolerable loss of ductility. Furthermore, the uncertainty in the amount of ductility reduction is not been characterized in the literature. In the present study, the issues in strain-based assessment of the hydrogen pipelines are addressed with the focus on CSC. The differences in uncertainty modelling of the pipeline parameters, as well as, CSC model errors are explored. Parameters for random variable modelling and uncertainty propagation for reliability analysis when using the limit state for CSC are proposed. Additionally, sensitivity of the estimated probability of failure to the pipeline material, geometry, and model uncertainties are explored through a case study. The results of the study are expected to guide the future work in development of CSC models for the carbon steel pipelines susceptible to ductility reduction and hydrogen embrittlement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".