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Record W3023890320 · doi:10.1063/5.0003518

Turbulent displacement flow of viscoplastic fluids in eccentric annulus: Experiments

2020· article· en· W3023890320 on OpenAlexafffund
Majid Bizhani, Yasaman Foolad, I.A. Frigaard

Bibliographic record

VenuePhysics of Fluids · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationSchlumberger Foundation
KeywordsMechanicsAnnulus (botany)TurbulenceDragBingham plasticPhysicsDisplacement (psychology)ViscoplasticityNewtonian fluidFluid dynamicsClassical mechanicsRheologyMaterials scienceThermodynamicsComposite material

Abstract

fetched live from OpenAlex

We study displacement flows in strongly eccentric annuli, where the in situ fluid is viscoplastic and the displacing fluid is Newtonian. This mimics the situation found in the cementing of horizontal oil and gas wells. In this configuration, it is common that the yield stress of the displaced fluid prevents displacement from the narrow side of the annulus, where it remains static. We address the question of whether a turbulent flow of the displacing fluid will be effective in removing the static narrow side channel and by what means. The flows proceed with rapid displacement along the wide side of the annulus, leaving behind a gelled channel of fluid on the narrow side. The narrow side is displaced either slowly or not at all. This depends on both the yield stress of the displaced fluid and the turbulence characteristics of the displacing fluid. We influence the latter through the use of drag-reducing polymers. We show that secondary flows in the turbulent displacing fluid are essential to the displacement and also the increased pressure drops in the turbulent flow. We hypothesize that the displacement is enhanced by the transmission of normal stresses into the gelled layer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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.

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

Citations20
Published2020
Admission routes2
Has abstractyes

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