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Record W2318219781 · doi:10.2514/6.2014-2822

Fluid-Structure Interactions in a Tube Bundle Subject to Cross-Flow. Part B : Two-Phase Flow Modeling

2014· article· en· W2318219781 on OpenAlexafffund
Eliott Tixier, Cédric Béguin, Stéphane Étienne, Dominique Pelletier, Alexander Hay, Guillaume Ricciardi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBundleFlow (mathematics)Two-phase flowMechanicsTube (container)Computer scienceMaterials sciencePhysicsMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The response of a tube bundle subject to a two-phase cross-flow is investigated using a porous medium approach. This is the second of a two-part paper: in Part A new equations for the fluid and the structure were developed using a volume averaging technique. The main advantage of such an approach is that, compared to DNS, coarser and fixed meshes can be used for unsteady simulations, substantially alleviating the computational cost. The objective of part B is to extend the previous fluid-structure interaction model to two-phase flows. Following the same volume averaging technique, we describe the two-phase mixture using a Euler-Euler formulation. A model for the interaction between the gas and the liquid phase, similar to the fluid structure interaction model, in lumped into the equations. The solid structure, the gas and the liquid phases are fully coupled in a well posed set of equations. The code is verified by the method of manufactured solutions and its ability to represent fluid structure interactions in two-phase flows is assessed by comparing its predictions with results from DNS simulations and previous experimental data.

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: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.768

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 head0.011
GPT teacher head0.275
Teacher spread0.264 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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