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Record W4416166939 · doi:10.3390/pr13113665

An Extended Rayleigh Equation for the Uniform Inviscid Plane Flow with Gas Bubble Crossflow

2025· article· en· W4416166939 on OpenAlexaff
C. Q. Ru

Bibliographic record

VenueProcesses · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInviscid flowLift (data mining)BubblePlane (geometry)Potential flowRayleigh scatteringFlow (mathematics)Lift coefficient

Abstract

fetched live from OpenAlex

The classic second-order Rayleigh equation governs the linear stability of single-phase inviscid plane flows, and its extension to two-phase inviscid plane flows with a crossflow of another fluid remains to be investigated. The present work studies the linear stability of steady uniform inviscid two-phase flow in a horizontal channel with gas bubbles injected from the lower wall and removed from the upper wall. An extended fourth-order Rayleigh equation with constant coefficients is derived for the linear stability of the two-phase uniform inviscid plane flow with the bubble crossflow injected at the bubble terminal velocity. Our analytical results show that the uniform inviscid plane flow driven by the bubble crossflow is linearly unstable with rapidly growing disturbances in the absence of the lift force. On the other hand, when the positive lift force coefficient is nearly equal to the added mass coefficient, the uniform inviscid plane flow driven by the bubble crossflow is linearly stable to the admissible disturbances consistent with the bubble-injection boundary conditions. These analytical results reveal the destabilizing effect of the bubble crossflow and confirm the stabilizing effect of the positive lift force on the inviscid plane flows, which could stimulate further research interest in the qualitatively different roles of the bubble crossflow and the lift force in the stability of inviscid plane flows as compared to viscous plane flows.

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: none
Teacher disagreement score0.942
Threshold uncertainty score0.282

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 head0.225
Teacher spread0.217 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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