Challenges of Mitigating AC Interference Risks in a 107 Km Multi-Pipeline Corridor
Bibliographic record
Abstract
Abstract An initial AC interference study and mitigation design was performed prior to construction, on the subject NPS 36, 107 km long pipeline (Pipeline A) installed in 2016. The subject pipeline is collocated with an NPS 30 pipeline (Pipeline B) constructed in 1999, for the entire route, and several other pipelines in some areas, all owned by the same operator and with shared cathodic protection systems. Five areas of powerline collocation were identified and modeled in the AC Interference study. During the commissioning survey, elevated AC voltages were recorded in areas with no identified powerlines. Furthermore, it was discovered that some pipeline bonds, existing mitigation systems and other pipelines were not modeled as per the final “as-built” installation or incorporated into the AC mitigation system. Subsequent site investigations were performed to confirm bonding, assess AC interference corrosion risks, and identify additional AC interference sources. The pipelines were remodeled to include the existing “as-built” configuration and these additional interference sources. Re-modeled results were assessed based on field collected data, remotely monitored data, and In-line Inspection (ILI) data on both pipelines to develop an integrated AC mitigation and monitoring system. Several lessons were learned, that can benefit future projects. These lessons include the importance of remodeling the as-built pipeline configuration, complexities related to AC interference in multi-pipeline corridors, and the difficulty in assessing the AC corrosion risk via modeling alone. Assessment and incorporation of site and ILI data into the final AC mitigation and monitoring system design leads to a more holistic result.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".