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Record W1967241852 · doi:10.1080/10916466.2014.994708

CFD Analysis of Hydrate Formation in Pipelines

2015· article· en· W1967241852 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science and Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputational fluid dynamicsPipeline transportClathrate hydratePetroleum engineeringHydrateEnvironmental scienceChemistryMarine engineeringThermodynamicsGeologyEngineeringEnvironmental engineeringPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Offshore oil and gas exploration and production is increasingly moving further into the deep sea where temperature and pressure conditions favor hydrate. Hydrate formation in gas pipeline is one of the major flow assurance problems, which is enhanced as lower temperature and higher pressure condition. This study explores the CFD analysis of hydrate formation behavior in subsea pipeline by performing sensitivity studies exploring the effects that flow (velocity, diameter) and fluid (viscosity and water fraction) parameters on hydrate formation. The results generated showed that changes in flow conditions or fluid properties have significant effects on the hydrate formation in the 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.825
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.235
Teacher spread0.224 · 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