L52187 Decompression Response of High-Pressure Natural Gas Pipelines Under Rupture or Blowdown Conditions
Bibliographic record
Abstract
The Pipeline Research Council International, Inc. found that Scandpower has software that is capable of predicting the transient response of a pipeline segment transporting either conventional or enriched dense phase natural gas mixtures when subjected to a controlled blow down or an uncontrolled rupture event. Consequently PRCI expressed a desire to pursue an experimental work to provide the basis for evaluating the adequacy of the existing software and/or define further development if any. NOVA Research and Technology Corporation (NRTC) was awarded a contract to perform the experimental work and compare results with prediction by the OLGA 2000 software. The existing NPS 2 stainless steel decompression tube test rig at TCPL Gas Dynamic Test Facility (GDTF) in Didsbury, Alberta, Canada, has been expanded specifically for this project. The initial length of 30 meters was extended to 172 meters in order to simulate a longer length to diameter (L/D) ratio. Two sets of tests were conducted: one to simulate pipeline rupture and another to simulate controlled blowdown. Rupture was simulated by a rupture disc located at one end of the tube, while blowdown was affected by a typical blowdown stack and a reduce-bore ball valve. The test scope included three gas mixtures (conventional, medium rich and rich) and three initial pressures: 10, 14 and 20 MPa.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".