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Record W3121716185 · doi:10.1115/ipc2020-9226

Advances and Challenges in Purging Pipeline Sections: Field Measurements vs. 1D Purging Model

2020· article· en· W3121716185 on OpenAlexaff
K. K. Botros, A. Hawryluk, Dmitry Ryapolov

Bibliographic record

VenueVolume 3: Operations, Monitoring, and Maintenance; Materials and Joining · 2020
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsPurgeFlammable liquidInletNatural gasPipeline (software)MechanicsEngineeringPetroleum engineeringEnvironmental scienceMechanical engineeringWaste managementPhysics

Abstract

fetched live from OpenAlex

Abstract Effective purging of air out of a pipeline section before commissioning by direct displacement with natural gas has been safely practiced for decades with the recognition that flammable interfacial mixing zone between the driving gas (behind) and the air (ahead) is inevitable. In cases when the purge velocity is below a threshold dictated by the gravity current velocity (defined in AGA Purging Principles and Practices, 2001), natural gas being lighter than air can in fact ride over air being the heavier gas and short circuit the flow path to the vent at the other end of the pipe section, thus trapping behind pockets of air that could potentially introduce risk of internal explosion with subsequent damage to the pipe section and pose a safety issue to field personnel. Therefore, maintaining the purge velocity above this threshold by a good margin has been a common practice in the purging procedure to-date. In fact, maintaining the purge velocity above the threshold can be controlled by the injection press or flow, where tools and dynamic purging models have been successfully developed and proven to be useful. However, AGA recommends that the drive purge gas pressure be limited to 689 kPag (100 psig) in the inlet purge line to the pipe section to avoid the risk of detonation. In some cases when the inlet purge line is relatively small compared to the main pipe section, this limit on the purge pressure would result in gas/air interfacial velocity much lower than the threshold velocity, hence stratification will occur. This paper provides insight into the possibility of increasing the purge pressure above AGA limit to avoid stratification, while conforming to the safety aspects related to detonation. A purge model is developed to overcome the shortcoming in AGA purge software that limits the purge pressure to maximum of 689 kPag (100 psig). Field trial was conducted to validate the model which demonstrated, as a proof of concept, a successful purge procedure with purge pressure = 5517 kPag (800 psig) in NPS 1.5 purge line to purge nitrogen out of NPS 42, 5.8 km section of a pipeline.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.058
GPT teacher head0.250
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2020
Admission routes1
Has abstractyes

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