Estimation of corrosion exposure of transmission lines due to de-icing salt applied on roads
Bibliographic record
Abstract
This paper proposes a comprehensive corrosion exposure model for overhead electric transmission conductors near roads in northern climates. The proposed model accounts for the level of traffic, the frequency of winter precipitation, de-icing salt spreading practices, wind speed, and wind direction for predicting the level of chloride contamination during winter as a function of the relative position of a transmission line to the road. The exposure to chlorides is used in combination with relative humidity, air temperature, and SO 2 levels to estimate annual rates of corrosion for the line. The exposure model is successfully validated with inspection data collected over several spans at six sites. The yearly corrosion hazard is also evaluated using the ISO 9223 annual rate of corrosion classification for conductors at 6 different locations with similar service life, which compare well with field measurements of residual zinc layers. The next step in the research is to improve estimates of yearly corrosion rates and residual life by accounting for the effective time of exposure during the service life, the indirect exposure of steel wires due to the shielding effect from of aluminium wires, and the variability of the zinc layer thickness.
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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) | 0.001 | 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) | 0.000 | 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".