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Record W4283582911 · doi:10.11159/ffhmt22.212

Towards Understanding the Interfacial Structures of Non-developing Slug Flow in Vertical Pipes

2022· article· en· W4283582911 on OpenAlexaffvenue
Shahriyar G. Holagh, Wael H. Ahmed

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2022
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSlugSlug flowFlow (mathematics)GeologyMechanicsMaterials sciencePetroleum engineeringComputer scienceTwo-phase flowPhysics

Abstract

fetched live from OpenAlex

Non-developing slug two-phase flows in vertical pipes are widely found in various industries. These flows are of a highly complex nature largely due to the deformability of the gaseous phase resulting in unstable interfacial flow structures at different flow regimes. Such complex interfacial structures strongly control the multiphase transport phenomena including energy, mass, and momentum transfer between the phases. Therefore, a clear understanding of the behaviour characteristics of these interfacial structures is critical to the optimum design of multiphase flow systems. This study briefly provides a review on the behaviour of the gas-liquid interfacial structures for the slug flow regime in co-current upward two-phase flows. This review founds that the interfacial structures of gas-liquid interface exhibit different shapes and behaviours in non-developed compared to the fully-developed regions of slug regime. The behaviour of these structures is found to be heavily influenced by gas injector design, pipe diameter, gas and liquid phase properties, and operating flow conditions. The review also showed that the interfacial structures have been widely studied in developed region, while they have remained less understood in the non-developed region. Also, the impact of liquid and gas phases' thermo-fluid properties (density, viscosity, and surface tension) and pipe diameter on the interfacial structures in this flow regime have received the least attention.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.260
Teacher spread0.222 · 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 designObservational
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

Citations4
Published2022
Admission routes2
Has abstractyes

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