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Record W4229032684 · doi:10.1063/5.0092026

Displacement flows in eccentric annuli with a rotating inner cylinder

2022· article· en· W4229032684 on OpenAlexafffund
Heeseok Jung, I.A. Frigaard

Bibliographic record

VenuePhysics of Fluids · 2022
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMechanicsAnnulus (botany)PhysicsRotation (mathematics)Eccentricity (behavior)CylinderDisplacement (psychology)BuoyancyAxial compressorFlow (mathematics)Newtonian fluidCentrifugal forceClassical mechanicsGeometryMaterials scienceThermodynamics

Abstract

fetched live from OpenAlex

We experimentally study the effects of inner cylinder rotation on the displacement flow of two Newtonian fluids along a horizontal eccentric annulus, with differing viscosities and densities. With the rotation of the inner cylinder, the flow behavior changes from stratified to helical, as rotation dominates buoyancy, or directly to an azimuthally dispersive regime when rotational velocity dominates axial velocity. Flow separation is observed to occur when eccentricity is high: the displacing fluid is contained in the wide gap of the annulus, and the effective displacement is delayed. Rotation is effective in creating azimuthal flow in the narrow gap, where there is limited flow and bottom-side residual fluid may be present. In most cases, rotation improves the displacement (volumetric efficiency) by shortening the length of the axial elongation of the displacement front, and eventually, steady displacements are seen. The study is motivated by displacement flows occurring during the primary cementing of long horizontal oil and gas wells. Rotating the inner cylinder (casing) is recommended. Our results suggest that this practice increases azimuthal dispersion and can prevent a narrow mud channel from forming if the excess fluid volume is used.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.480

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 head0.008
GPT teacher head0.218
Teacher spread0.211 · 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 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

Citations11
Published2022
Admission routes2
Has abstractyes

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