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Record W2587946822 · doi:10.1139/cjp-2016-0801

On mode-matching analysis of fluid-structure coupled wave scattering between two flexible waveguides

2017· article· en· W2587946822 on OpenAlexvenueno aff
Sajid Shafique, Muhammad Afzal, Rab Nawaz

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsScatteringInletMode (computer interface)OpticsForcing (mathematics)Eigenmode expansionWaveguideNormal modeMatching (statistics)MechanicsSurface (topology)Enhanced Data Rates for GSM EvolutionField (mathematics)Power (physics)Evanescent waveVibrationComputational physicsAcousticsGeometry

Abstract

fetched live from OpenAlex

A mode-matching analysis articulates the coupled wave scattering in a 2D waveguide structure. An elastic plate is attached at the upper surface parallel to the axis of inlet–outlet ducts whereas a flanged junction is introduced between two flexible waveguides. The main intention is to see how choice of appropriate edge conditions and the incident forcing affect the scattered field for both structure-borne and fluid-borne vibrations. The graphical results illustrate that different physical conclusions should be drawn. Through apposite numerical results, we observe the power distributions in attenuated regions with abrupt changes of height. Such configurations are directly relevant to the models of fluid and structural interactions.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.286
Teacher spread0.254 · 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 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

Citations33
Published2017
Admission routes1
Has abstractyes

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