Impact of Yield to Ultimate Ratio on the Reliability of Burst Limit States
Bibliographic record
Abstract
In order to reduce arctic construction and transportation costs, high strength steels (> X80) have been advocated for use in high pressure gas pipelines. These steels differ from conventional steels by exhibiting lower work hardening capacity, lower strain to failure and possible softening of their HAZ. These differences can impact burst limit state and tensile limit state, in addition to crack arrest. In this paper, the impact of the variations in mechanical properties on the reliability of several pipe limit states involving burst is examined. The paper presents the results of burst limit state analysis using state-of-the-art plastic burst models of strain hardening pipe and considering all the uncertainties that impact the margin of safety of pipes subject to internal pressure. Intact pipes, corroded pipes and externally damaged pipes are considered. The analysis focuses on different design check equations (DCE) which “control” the safe usage of the pipe. In addition, the paper looks at how external or internal damage or corrosion affects the burst capacity differently for medium versus high-strength pipelines steels.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".