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Record W2556073644 · doi:10.1115/ipc2016-64012

Effects of Pipeline Elevation Changes on Optimum Expelling Procedures for Gas Pipelines

2016· article· en· W2556073644 on OpenAlexaff
K. K. Botros, C H Edwards, Brad Watson, T. Thrall

Bibliographic record

VenueVolume 3: Operations, Monitoring and Maintenance; Materials and Joining · 2016
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsTransCanada (Canada)Nova Chemicals (Canada)
Fundersnot available
KeywordsStack (abstract data type)Elevation (ballistics)PurgePipeline (software)BuoyancyPetroleum engineeringPipeline transportMarine engineeringGeologyEnvironmental scienceMechanicsEngineeringMechanical engineeringComputer scienceStructural engineeringWaste managementPhysics

Abstract

fetched live from OpenAlex

Expeller performance has been evaluated in terms of the capability to create suction pressure at the throat. This formulation has been used to assess the effectiveness of evacuating combustible gases from an isolated, depressurized, pipeline section involving mainline block valves up to two times normal spacing with an intermediate vent stack. Additionally, the effects of elevation changes that promote buoyancy driven flows are accounted for in time as the interface between air and gas travels along the pipeline section during expelling. Two expelling strategies were introduced and assessed. These are simultaneous expelling, in which gas is expelled from the pipeline section from both ends, and sequential expelling, in which an intermediate vent stack is used to expel gas from the upstream and downstream segments. The effects of elevation changes and the location of the intermediate vent stack determine the best strategy for expelling so as to maximize the purge velocity in the section of a pipeline to be purged, while maintaining the mean flow velocity in the pipe above the minimum purge velocity to prevent air-gas stratification. It was found that for a ‘Flat-’ or a ‘Cusp-type’ elevation profile it is advantageous to follow a sequential expelling procedure using one expeller at the intermediate vent stack location. In the case of a ‘Vee-type’ elevation profile, a simultaneous expelling procedure is a better option in terms of expelling time, at the cost of needing to deploy two expellers to different sites quite far apart. Air ingress location depends on the expelling strategy and elevation profile.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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