Application of a Newly Standardized Risk-Based Pressure Design Approach – Implications From Pilot Studies
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 Standards Association’s (CSA’s) Standard Z662. This new approach was adopted in the non-mandatory Annex C of the 2023 edition of CSA Z662. The risk-based design approach uses a set of hoop stress factors to calculate the minimum wall thickness from the pipe’s pressure, diameter, and specified minimum yield strength. The hoop stress factors are calibrated to meet reliability targets based on undamaged pipe burst and third-party mechanical damage failure limit states. These reliability targets are defined for a set of consequence-based safety classes to achieve a consistent, broadly acceptable, level of risk for all pipelines. Since the approach was adopted in CSA Z662 in 2023, several pilot studies, as described in this paper, have applied it to segments of high-pressure transmission pipelines in Canada. While this approach can also apply to new designs, the pilot studies described in this paper consider scenarios in which existing designs must be re-evaluated, including for class location changes due to population encroachment and the construction of road crossings. This paper describes the results of these pilot studies and demonstrates the safety and financial implications of adopting the new risk-based pressure design approach at such sites that need re-evaluating. This is done by comparing the design requirements under the new risk-based approach, such as pressure and wall thickness, with the requirements of the existing class location approach. In some cases, the pilot studies demonstrate that the new risk-based approach can reduce over-conservatism with less-restrictive design requirements, resulting in a positive financial benefit while maintaining broadly acceptable levels of safety. The benefit of using alternative mitigation options, such as mechanical damage prevention measures, is also explored in some of the pilot studies.
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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 | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".