RISK AND IMPACT ASSESSMENT OF NATURAL GAS PIPELINES IN RURAL HIGHWAY RIGHTS OF WAY
Bibliographic record
Abstract
The placement and location of hydrocarbon pipelines with respect to road geometries and cross sections can have an effect on the safety of the highway system and its users and adjacent residents, as well as operational and economic impacts on highway maintenance, construction, and modification activities. To assess these risks and impacts, the Transportation Association of Canada (TAC) commissioned Bercha Engineering Limited (Bercha) to conduct an in-depth, comprehensive study directed at generating a qualitative and quantitative understanding of the implications of locating pressurized natural gas pipelines in various locations within rural road right-of-ways. The study covered four primary representative road types together with their variations in ADDT, vehicle speed, and cross section, as well as three representative pipeline sizes and pressure categories for three different pipeline locations. The three pipeline locations consisted of one in the shoulder, one below the ditch, one just inside the edge of the right-of-way, and a fourth control location where the pipeline is away from the effects of the roadway. The method for systematically quantifying the risks to the public, considering the effects of the pipeline-roadway synergy, including effects on the pipeline failure rate as well as consequences of possible failure including ignition by vehicles, was developed and applied to each of the 108 generic cases. Both individual and collective risks and their variations for each of the different combinations were evaluated, and discussed. Similarly, economic impacts, including increases in the unit cost of common maintenance, construction, and reconstruction activities for the road operators were also identified. A series of conclusions and recommendations was generated and the study was reported in detail in a comprehensive final report together with supporting appendices. Although previous studies have been done on the use of common utility and transportation corridors, no comprehensive quantiative assessment of risks and economic impacts for representative combinations of road and pipeline characteristics has appeared previously, resulting in a significant volume of new observations and information available from the work reported herein. For the convering abstract of this conference see ITRD number E201066. (A)
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".