Effects of Seasonal Variation on AC Interference and Mitigation Design
Bibliographic record
Abstract
Abstract In Canada and in the northern portions of the United States, soil resistivities increase rapidly by up to several orders of magnitude once water in the soil freezes in the winter. Frost-penetration can vary from centimeters up to a meter or more in depth. Although it is standard industry practice in the electrical industry to consider seasonal variations in soil resistivity when modeling grounding facilities for substations and generating stations, this is often not considered in AC interference studies related to pipelines. The effect on AC induction is expected to be minimal, as this is predominantly dependent on the deeper soil layers. However, frozen soil conditions can have a significant impact on the resistive coupling under a phase to ground powerline fault, and the effectiveness of the AC mitigation system. This paper involved a case study of a project involving AC interference on pipelines located in Canada. summer, and winter soil conditions were modeled to determine the effect on the subject pipeline under steady state and fault conditions. Allowable safe touch potentials were also calculated for these two scenarios, and used to assess the safety risks. A mitigation system was designed to ensure that the safety and integrity risks are mitigated to acceptable limits, for both seasonal conditions.
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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 | 0.000 | 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 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".