Interpretation of the Safety Risk Tolerance Criteria for Integrated Asset Management of Pipelines
Bibliographic record
Abstract
Abstract Safety risk tolerance criteria are commonly established using the risk measures for individual risk and societal risk. Several studies on the review of international standards for safety risk acceptance criteria have identified that in most international standards, the societal risk criterion is expressed in terms an F-N curve where N is the expected number of fatalities due to hazardous conditions posed by an infrastructure element and F is the estimated frequency of N or more fatalities. The Netherlands and the UK have pioneered establishing the risk tolerance criteria for both individual and societal risk. The development of the safety risk tolerance criteria was primarily in the context of regulatory decision-making for the permitting process of the facilities, which was later expanded to include hazardous materials transport and pipelines. For the existing facilities and pipelines, the risk tolerance criteria are used extensively for land-use planning and development. Recently, Canadian standard, CSA Z662:2023 “Oil and Gas Pipeline Systems” has included quantitative risk criteria for pipelines in the informative (non-mandatory) Annex B portion that is applicable for the risk management of all aspects of the pipeline life cycle. Following the established international norms, the individual and societal risk criteria were published such that the societal risk criterion for the F-N curve to be applied over one kilometer of the pipeline. In contrast to the international standards such as IGEM/TD/2 “Assessing the risks from high pressure Natural Gas pipelines” (2015), there is little guidance to differentiate between use of the quantitative safety tolerance criteria for the purpose of permitting of new pipelines and land-use planning with the purpose of pipeline integrity management. This paper presents the differences in the use of available quantitative safety risk tolerance criteria for land-use planning and the pipeline risk management during the pipeline life cycle. The applicability of the risk tolerance as intended during the development of criteria, is critically reviewed when used in the context of risk management for the integrated asset management of the pipeline considering the life cycle performance. Additional considerations for interpreting the safety risk tolerance criteria during decision-making regarding risk mitigation actions are proposed. Furthermore, linear metrics used in risk measures established for other linear infrastructure, such as roads, and railways are compared with pipelines, and the differences between risk measures to establish tolerance criteria for point-source hazard infrastructure, such as chemical facilities, with the linear infrastructure, such as pipelines are highlighted.
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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 | 0.020 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".