Onshore Pipeline Safety Consequence Modelling in Support of the Development of a Risk-Based Safety Class System
Bibliographic record
Abstract
Abstract A consequence-based safety class system was developed as an alternative to the class location system currently used as the basis for defining the maximum allowable hoop stress in Canadian Standard Association’s Standard Z662. Development of the safety class system required models to quantify the safety-related consequences of pipeline releases expressed as simple analytical functions of a limited number of parameters that are typically known at the pipeline design stage. These simple analytical formulas were developed using an empirical approach, in which validated numerical models were first used to estimate the hazard zone sizes for a matrix of cases representing the feasible input parameter ranges for pipelines associated with each service fluid. Subsequent work, described in a companion paper, employed regression analysis of the parametric analysis results to develop the required simplified analytical formulas. This paper describes the safety hazards posed by releases of the various service fluids; the numerical models employed in the parametric analysis to determine the associated hazard areas as a function of key pipeline, service fluid, terrain, and weather-related parameters; and the hazard intensities adopted to delineate the size and extent of the hazard areas bound by both the 1% and 99% lethality contours. It also discusses the sensitivity analysis undertaken to establish the minimum set of pipeline and service fluid parameters that could be used to credibly estimate the size and extent of the applicable lethality zones. It concludes with a set of examples that illustrates the relative size and extent of the model-predicted lethality zones associated with the various hazards that could develop for each service fluid in a representative set of pipelines.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".