Corrosion Modeling and Assessment on Transmission Line Structures due to Nearby Stray Current from a DC-Electrified Railway
Bibliographic record
Abstract
The expansion of urban infrastructure has led to an increased sharing of corridors between high-voltage transmission lines and direct current electrified light rail transit (DC-LRT) systems. This situation has raised concerns about stray current-induced corrosion affecting transmission line structures. This paper presents a comprehensive numerical modeling approach using the CDEGS software package to evaluate the impact of stray currents from LRT on the foundations of nearby transmission towers. The proposed model validated through field measurements demonstrates a high accuracy, with errors below 12.5%. Key factors, such as the soil resistivity, the ballast resistance, and the separation distance between railways and transmission lines are analyzed to assess corrosion risks. The study highlights the importance of proactive mitigation strategies to prevent structural degradation and ensure the reliability of power infrastructure, providing utility companies an efficient method for effectively predicting and managing stray current corrosion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".