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Record W4389541022 · doi:10.17118/11143/20960

An experimental study of buoyant jets : effects ofviscoplasticity

2023· article· en· W4389541022 on OpenAlexaff
Mir Hedayat Moosavi, Hossein Hassanzadeh, Soheil Akbari, Seyed Mohammad Taghavi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsViscoplasticityPhysicsMechanicsComputer scienceFinite element methodThermodynamics

Abstract

fetched live from OpenAlex

In this paper, we experimentally investigated the injection of a Newtonian jet into Newtonian/viscoplastic ambient fluids.Although this study has applications in environmental flows, mixing processes, and so on, the main application of our interest is the plug and abandonment of oil and gas wells.Hence, we analyzed the impingement time of the jet in addition to other jet characteristics, namely, the laminar length and the deviation length.Furthermore, we observed two regimes for different ambient fluids, i.e. the mixing regime for a Newtonian ambient fluid and the trapped regime for a viscoplastic ambient fluid.Moreover, we examined the impact of the Reynolds number (Re) and the Bingham number (BN), on the jet characteristics.Re and BN have opposite effects on the impingement time, causing a decrease and growth, respectively.We also observed the existence of a laminar length at higher Re in the trapped regime, compared to the mixing regime.An increase in Re results in a growth in the deviation length for both regimes, and this growing trend is more drastic for the mixing regime.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.254
Teacher spread0.246 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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