Use of Geomagnetic Data for Evaluation of Telluric Effects on Pipelines
Bibliographic record
Abstract
Abstract Telluric currents interfere with cathodic protection systems and cause variations in pipe-to-soil potentials, which can exceed the levels recommended for protection of the pipeline steel. The amplitudes of telluric currents observed in a pipeline depend on three factors: (1) the level of the geomagnetic activity, (2) conductivity of the underlying earth and (3) pipeline electromagnetic properties and geometric parameters. These factors have been incorporated into mathematical models that are used to estimate the pipe-to-soil potential variations due to telluric activity. The time when pipe-to-soil potential variations exceed the recommended level can be different depending on the different telluric activity at the pipeline locations. To evaluate this, a simple model for the telluric electric field has been set up, based on the geomagnetic data and an earth conductivity model. A statistical study based on the long records of the geomagnetic data from Canadian magnetic observatories and conductivity structures of the deep earth allows evaluating telluric activity for 30 years period. In order to show the geographical areas with different levels of activity, a set of maps has been produced and is available through Atlas of Canada web page: http://atlas.nrcan.gc.ca/auth/english/maps/environmentlnaturalhazards/space_weather. The estimated telluric electric fields were used as an input to model pipe-to-soil potential variations on a pipeline. In order to do this, the developed pipeline model has been incorporated to provide an on-line service for different users. The on-line service allows the user to evaluate the pipe-to-soil potential fluctuations at a particular location for a user-defined pipeline.
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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 | 0.000 |
| 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 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".