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Record W4416775425 · doi:10.1061/jhend8.hyeng-14394

Liquid Slug Motion in Vertical Risers with Limited Ventilation

2025· article· en· W4416775425 on OpenAlexaff
Youxu Song, Xifeng Chen, Qingzhi Hou, David Z. Zhu, Arris S. Tijsseling

Bibliographic record

VenueJournal of Hydraulic Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSlug flowSlugBody orificeLaminar flowFlow (mathematics)Front (military)BubbleMass flowComputational fluid dynamics

Abstract

fetched live from OpenAlex

Dangerous intermittent slug flows occur when large air pockets entrapped in deep tunnels escape from vertical risers, a phenomenon known as stormwater-induced geysers. Although the dynamics of liquid slug flow in fully ventilated pipelines has been well studied, investigations on the mass shedding of liquid slugs moving in vertical risers with a top orifice are lacking. By means of a three-dimensional computational fluid dynamics model, the dynamic behavior of liquid slugs with different initial slug lengths under different driving pressures and orifice openings was analyzed. Experiments were conducted to provide physical insights and data for model validation. It was found that the length of the rising liquid slug decreased due to a constant mass shedding rate. The latter was independent of the driving pressure and initial slug length, but dependent on the size of the orifice at the top end. The velocities of the slug’s tail and front were linearly related via the mass shedding rate. In the fully open riser, the net force driving the slug decreased but remained positive in the geyser event, while in the riser with limited ventilation it depended on both the driving air pressure and the orifice size and could become negative. A new relationship between the air bubble nose velocity, the water slug front velocity, and the film flow velocity has been derived. The upward film flow velocity can be laminar or turbulent. Moreover, a relationship between the film thickness, mass shedding rate, and pipe diameter has been derived.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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
Published2025
Admission routes1
Has abstractyes

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