Pipeline Stress Relief and Evaluation of Strain Measurement Technology at a Moving Slope
Bibliographic record
Abstract
A major slope in southern Manitoba has been experiencing deep seated movements of approximately 60mm per year. This 24m high × 85m long slope contains a pipeline right of way with five large diameter crude oil lines that were constructed from 1950–1998. It is estimated that the slope has moved up to 3 meters since the pipeline installations. Management of the effects of this slope movement on the pipelines has involved cross-functional strategies that include geotechnical, integrity, and stress evaluations. A finite element analysis (FEA), which considers the interaction between the soil movement and pipeline, was generated to evaluate the pipeline stresses caused by the slope movements to date. The results indicated that the strain capacity on one of the pipelines may be near its limit. Correspondingly and in order to be conservative, a stress relief was conducted on three of the pipelines within the right-of-way. This mitigation involved excavating the pipelines 360 degrees which allowed for their decoupling from the surrounding soil, and the associated pipeline spring back was surveyed. Prior to backfilling, a low friction geotextile was installed around the excavated pipelines to help mitigate future movements. Drainage improvements and a toe berm were also installed to improve the slope stability. Several strain measurement technologies that have been the subject of previous Pipeline Research Council projects were also installed at the site. Stress probe measurements were taken before and after the stress relief; a fiber optic cable was installed; inline inspection bending strain measurements were analyzed; and the FEA analysis was used to model the strains before and after the stress relief. All of these technologies are compared to the measurements from strain gauges that were read both before and after the stress reliefs were conducted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".