Risk-Based Hoop Stress Factors for Pressure Design
Bibliographic record
Abstract
Abstract A risk-based pressure design approach has been developed as an alternative to the class location approach currently used in the Canadian Standard Association’s (CSA’s) Standard Z662. Similar to the current approach, the new approach uses a set of hoop stress factors to calculate the minimum wall thickness from the pressure, diameter, and specified minimum yield strength. The hoop stress factors, termed class factors, are calibrated to keep the failure probability below an allowable value for the limit states representing burst of undamaged pipe under the operating pressure and failure due to equipment impact loading. Yielding under the strength test pressure is addressed as a separate limit on the class factor. To achieve a consistent safety level for all pipelines, the allowable failure probabilities are inversely proportional to the magnitude of failure consequences, as implied by a safety class determined according to the approach described in a companion IPC paper. This paper describes the calibration process used to define the class factors and provides a comparison between the wall thicknesses resulting from the risk-based approach and those obtained from the current hoop stress factors in CSA Z662.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".