Full-Scale Fracture Propagation Experiments: A Recent Application and Future Use for the Pipeline Industry
Bibliographic record
Abstract
A full scale fracture propagation test facility has been developed to validate the design, in terms of the ability of the material to avert a propagating fracture, of a major new pipeline to transport gas 1800 miles from British Columbia in Canada to Chicago in the USA. The pipeline, being built by Alliance Pipeline Ltd, will transport rich natural gas, i.e. gas with a higher than normal proportion of heavier hydrocarbons, at a maximum operating pressure of 12,000 kPa. This gas mixture and pressure combination imposes a more severe requirement on the pipe steel toughness than the traditional operating conditions of North American pipelines. As these conditions were outside the validated range of models, two full-scale experiments were conducted to prove the design. This paper will provide details of the construction of the 367m long experimental facility at the BG Technology Spadeadam test site along with the key data obtained from the experiments. Evaluation of this data showed that the test program had validated Alliance’s fracture control design. The decompression data obtained in the experiments will be compared against predictions from a new decompression model developed by BG Technology. The use of the experimental facility and the model to support future developments in the pipeline industry, particularly in relation to the use of high strength steels, will also be discussed.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".