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Record W2142842489 · doi:10.1115/1.4004621

Fluidelastic Instability in Normal and Parallel Triangular Arrays of Finned Tubes

2012· article· en· W2142842489 on OpenAlexafffund
J. Wang, D. S. Weaver

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTube (container)FinInstabilityMechanicsMaterials scienceBase (topology)PhysicsComposite materialMathematics

Abstract

fetched live from OpenAlex

An experimental study was carried out to investigate fluidelastic instability in finned tube bundles in normal and parallel triangular arrays. Three arrays of each geometry type were studied experimentally: two arrays with serrated, helically wound finned tubes of different fin densities, and a bare tube array with the same base diameter as the finned tubes. All six tube arrays studied had the same tube pitch. The finned tubes under consideration were commercial finned tubes typically used in the fossil and process industries. For the purpose of the present investigation, the concept of “effective diameter” of a finned tube, as previously used to predict vortex shedding, was used to compare the finned tube results with other finned tube results as well as the existing bare tube world data. The experimental results for the triangular arrays show that the fin’s structure strongly influences the fluidelastic stability of finned tube bundles and the fin pitch is demonstrated to reduce the difference in the stability threshold between the tube array geometries as the fin density increases. Overall, the effect of serrated fins on fluidelastic instability is very complex and array geometry dependent, stabilizing some arrays and destabilizing others. Clearly, the effect of fins cannot be accounted for by the simple use of an effective diameter of an equivalent bare tube. An earlier version of this paper appeared at the ASME 2010 FSI Conference, FEDSM-ICNMM2010-30223.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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

Citations13
Published2012
Admission routes2
Has abstractyes

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