Critical Review of Risk Criteria for Natural Gas Pipelines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Risk Assessment is an integral part of an Integrity Management Program (IMP), and it is generally the first step in most IMPs. Risk is of the product of two variables, the likelihood of failure and the consequence of failure, where failure is defined as a loss of containment event. Hence, it is necessary to calculate both variables in order to accurately model risk. To assess risk, criterion need to be established and the actual risk needs to be compared to the criterion in order to determine the acceptability of risk. Currently, most industry risk assessment models are qualitative risk models, where consequence is generally characterized by class, relative population measures, or some other relative measure. While this may be adequate for some relative risk ranking purposes, it is generally not accurate in representing the true consequences and the arbitrary nature leads to overly conservative or overly un-conservative results. Conversely, Quantitative Risk Assessment (QRA) models take into account the effect of the thermal radiation due to ignited pipeline rupture and evaluate the consequence on the surrounding human population. Such a consequence model is dependent on the pipeline properties (i.e. diameter and MOP) and the structure properties (i.e. precise locations and types of structures). The overall risk is then represented by two specific, well defined measures: Individual Risk (IR) and Societal Risk (SR). The goal of this paper is to perform a critical review of IR and SR acceptability criteria that are widely available and widely used, and outline the criteria (and the approach) adapted by TransCanada Pipelines. Worldwide, there are several different standards that define the criteria for evaluating IR and SR, particularly some countries with higher population densities around pipelines (e.g. UK and Netherlands). These IR and SR criteria have been compared in a hypothetical case study, to determine the most appropriate method in terms of the assumptions for calculating risks, the criteria, and how the actual risks compares to the criteria. The outcome of this study was the adoption of a defendable process for calculating SR, along with the associated criterion.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it