Prevention of Pipeline Failures in Geotechnically Unstable Areas by Monitoring with Inertial and Caliper In-line Inspection
Bibliographic record
Abstract
Abstract Pipelines in Western Canada cross numerous areas of active or potential landslides that pose a threat to pipeline integrity. The lines with the highest risk of landslides have been surveyed since 1994 with inertial/caliper in-line inspection tools that provide complete information on the pipe centreline shape, bending strain, position on maps as well as movement between inspections. These tools also record caliper measurements of pipe wall deformations which allows for detection of wrinkles and other anomalies that develop as the result of the pipe to soil interaction in landslide areas. This paper demonstrates advantages of the in-line geometry survey over traditional monitoring methods such as geotechnical surveillance or installation of strain gauges on the pipe. The major benefit is providing data for the entire line, not just selected areas of concern. The experience with using this technology revealed that pipeline movement can occur in areas that were not suspected of being subject to landslides, and were not identified by traditional geotechnical patrols. Another important advantage of an in-line geometry survey is the direct measurement of the cumulative effects of landslides on the pipeline integrity since the construction. This allows for accurate identification, sizing and location with Global Positioning System (GPS) of the most vulnerable points in the line in terms of large bending strains and pipe wall deformations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".