Telluric Hazard Assessment for Northern Pipelines
Bibliographic record
Abstract
Abstract Telluric currents cause variations in pipe-to-soil potentials, which can override a pipeline’s cathodic protection system. The cumulative effect of the “unprotected” time can be significant in areas where telluric activity is high, such as the Canadian north. This paper presents a general approach to the assessment of telluric activity. Telluric currents observed in a pipeline are the result of three simultaneously operating factors: (1) variations of the Earth’s natural geomagnetic field, (2) conductivity of the underlying Earth and (3) pipeline electromagnetic properties and pipeline structure. The first two factors were combined to give an estimation of the telluric electric field that produces variations of the pipe-to-soil potentials in a pipeline. This geoelectric field then can be combined with a particular pipeline equivalent circuit model which gives the pipeline response to the telluric activity in an area. We assess the occurrence of the geomagnetic and telluric activity for a typical year, assuming a general uniform conductivity structure across Canada. A more detailed case study has been done for the auroral zone than spans northern Canada. This includes not only a statistical evaluation of the geomagnetic activity but also specification of regions with different earth conductivities (layered earth structures), which when combined with the geomagnetic evaluation lead to the existence of different regions of telluric activity in the area of investigation. Using results from the assessment of telluric electric fields as an input into the pipeline model, the effects can be interpreted in terms of telluric variations in pipe-to-soil potential.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".