Supporting Guidelines for Reviewing Reliability-Based Assessments of Onshore Non-Sour Natural Gas Transmission Pipelines
Bibliographic record
Abstract
In Canada, a great deal of effort has been invested into the use of reliability-based techniques for the design and assessment of non-sour natural gas transmission pipelines. This led to the inclusion of Annex O in the Canadian onshore pipeline code CSA Z662 in 2007, which gives detailed descriptions of all of the key components of reliability-based approaches. However, the annex does not and is not intended to provide recipes for using the reliability-based techniques for particular fields of application such as evaluating the acceptability of changes to location class, service or increasing maximum operating pressure. Consequently, the onus is on the reliability/integrity engineer to tailor the approach to the particular field of application and the specifics of the pipeline. This means that even working in accordance with the code, the approach and optimizing techniques adopted by one engineer may be very different to that adopted by another. This presents a challenge for those reviewing reliability based plans, designs and alternatives for approval. The National Energy Board (NEB) engaged Andrew Francis & Associates Ltd (AFAA) to assist them with constructing a set of supporting guidelines to assess the comprehensiveness and safety of reliability based submissions. Unlike customary design reviews, the guidelines are geared towards provoking a reviewer into asking delving questions rather than into going through a ‘box-checking’ questionnaire. Indeed, asking the case-specific and clarification questions is regarded as a crucial step towards determining the adequacy and effectiveness of the measures proposed in the content and conclusions of a particular filing. Simply questioning whether Annex O has been followed is not encouraged and, even when safety criteria appear to have been met (i.e. box-checking), a reviewer is prompted to challenge the reasonableness of assumptions and ask whether safety levels are providing the lowest practicable risk to the Canadian public. One line of inquiring might be: are sufficient data available; are the data reliable; are the data relevant to the case under consideration; or have the data been analyzed using a valid method applicable to the case. Other typical questions would be have the consequences been properly assessed and are the mitigative and preventative measures providing the lowest practicable risk compared to pressure reduction and pipe replacement. The purpose of this paper is to present an overview of the assessment guidelines and the approach and key considerations for conducting efficient, consistent and fair reviews of reliability based assessments of hazardous material pipelines. In doing so, the paper also identifies some of the pitfalls that engineers conducting reliability based integrity assessments should seek to avoid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.249 | 0.523 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.027 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.013 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.014 |
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".