Estimating AC Mitigation Requirements for Pipelines Installed in High Voltage AC Corridors: Fault Conditions
Bibliographic record
Abstract
Abstract A previous paper1 has addressed the question of estimating mitigation requirements for pipelines installed in high voltage AC corridors, such as to maintain induced voltages at acceptable levels during normal operating conditions on the power system. This paper addresses the more difficult problem of estimating what mitigation is required to maintain pipeline coating stress voltages within acceptable limits during fault conditions on the power system. The difficulty of this undertaking arises primarily from the fact that AC interference during fault conditions includes not only induction, but also voltages transferred through earth to the pipeline location from power line poles or towers near which the fault has occurred: as a result, the analysis is more complex and the mitigation requirements are influenced by a greater number of factors. Furthermore, since the goal is to minimize the voltage difference between the earth and the pipeline steel, the interaction between the earth and bare mitigation wire buried next to the pipeline and connected thereto must be considered. This paper shows how factors such as soil resistivity, soil layering, length of parallelism, proximity of pipeline to transmission line, fault current levels, transmission line static wire type, transmission line structure grounding and coating resistance determine mitigation requirements.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| 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".