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Record W4385888025 · doi:10.55274/r0010394

L52187 Decompression Response of High-Pressure Natural Gas Pipelines Under Rupture or Blowdown Conditions

2004· report· en· W4385888025 on OpenAlexaffabout
Botros, Geerligs, Given

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsBoiler blowdownNatural gasEngineeringPipeline transportPetroleum engineeringHydrostatic testStructural engineeringMechanical engineeringWaste managementInlet

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.266
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes2
Has abstractyes

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