Performance Monitoring and Modeling of Small Diameter MDPE Natural Gas Pipelines Subject to Ground Movement
Bibliographic record
Abstract
Considering the need to undertake pipeline replacement in a cost-effective manner while ensuring the public safety interest, evaluating the performance of pipelines subject to soil loading from landslides is a key concern in some of the natural gas distribution systems operated by FortisBC Inc. As it is typically uneconomical and impractical to relieve stresses in distribution pipe systems by excavating or instrumenting the pipelines to measure the highly localized strains, undertaking numerical and/or analytical modeling combined with experimentation is a key aspect in attempting to relate the measured ground movement to performance of pipe. For this purpose, capturing the fundamental soil-pipe interaction in small-diameter extensible plastic pipes and undertaking field monitoring to validate the numerical model are critically important. With this background, this paper presents field measurement and numerical modeling undertaken to model the performance of 115 mm diameter medium density polyethylene (MDPE) pipes buried in West Quesnel, BC, Canada. Using field survey data, the active landslides occurring perpendicular to the pipe axis at these two sites have been periodically characterized since 2000/2001. Materials removed from the pipe system were tested to characterize the pipeline material behavior and limit strains. The data derived from these tests along with a range of soil behaviors are used to support pipe-soil interaction numerical simulation and thus characterize the strains accumulated in the pipeline in service. This paper discusses the limitations, challenges and recommendations for numerical modeling of soil-pipe interaction in small-diameter plastic pipes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".