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Record W2913570509 · doi:10.3390/en12030336

Decaying Swirl Flow and Particle Behavior through the Hole Cleaning Device for Horizontal Drilling of Fossil Fuel

2019· article· en· W2913570509 on OpenAlexaff
Jingyu Qu, Tie Yan, Xiaofeng Sun, Zijian Li, Wei Li

Bibliographic record

VenueEnergies · 2019
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMemorial University of Newfoundland
FundersNational Science and Technology Major ProjectNational Natural Science Foundation of China
KeywordsMechanicsAnnulus (botany)Laminar flowFlow (mathematics)Materials scienceParticle (ecology)DrillingIntensity (physics)Multiphase flowVolumetric flow rateFlow conditioningFlow velocityMass flowParticle depositionGeologyPhysicsTurbulenceComposite materialReynolds numberOptics

Abstract

fetched live from OpenAlex

The hole cleaning device is a powerful application which can effectively slow down the deposition of cuttings during drilling. However, in this complicated swirl flow created by the device, the decay of the swirl flow and the particle behavior are not evident yet. In this paper, the decay of the swirl flow and the particle behavior in the swirl flow field are studied by the Eulerian–Eulerian two-fluid model (TFM) coupled with the kinetic theory of granular flows (KTGF), and sliding mesh (SM) technique for simulating the fluid flow. The results show that the swirl intensity decays exponentially along the flow direction under laminar flow conditions. The swirl flow has a longer acting distance at a higher rotational speed, which can effectively slow down the deposition of cutting particles. The initial swirl intensity of swirl flow induced by the blades increases significantly with the increase of blade height and the decrease of the blade angle. The tangential velocity of the cutting particles in the annulus is more significant near the central region, gradually decreases toward the wall in the radial direction, and rapidly decreases to 0 at the wall surface. The decay rate is negatively correlated with the initial swirl intensity. The results presented here may provide a useful reference for the design of the hole cleaning device.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.367

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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