The AC Close Interval Survey and Other Common AC Measurement Errors
Bibliographic record
Abstract
Abstract The measurement of induced AC voltages along a pipeline is a primary indicator of electrical safety hazards and AC corrosion risks under steady state operation of influencing powerlines. This paper addresses several fallacies, misconceptions and common errors related to the measurement of these AC induced voltages. Many operators monitor AC voltage levels at test stations on an annual basis as part of their cathodic protection survey. However, the locations of the test stations and pipeline AC voltage peaks do not always coincide. In an attempt to determine the AC voltage profile along the pipeline, some operators and consultants perform AC close interval surveys. Through the combined use of basic electrical principles, computer modeling, and an assessment of close interval survey data, this technique is shown to be invalid. Another characteristic of AC interference on pipelines that is often overlooked is the variability of the measured AC voltage, which will fluctuate with the powerline loading throughout the day, from day to day, seasonally and annually. A one-time, annual measurement at test stations is not a reliable indicator of the AC interference risk to the pipeline. Finally, induced AC voltages should be measured with respect to remote earth. When an AC voltage is in proximity to a grounding electrode or some other AC mitigation facility, the AC current discharging to the ground creates a potential gradient in the soil, which will result in the measured voltage being less than the actual voltage to remote earth.
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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 | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".