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Record W2093880781 · doi:10.2495/fsi070021

The effect of radiation velocity potentials on the drift force on a submerged sphere

2007· article· en· W2093880781 on OpenAlexafffund
S. H. Mousavizadegan, Atiqur Rahman

Bibliographic record

VenueWIT transactions on the built environment · 2007
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsVelocity potentialMultipole expansionMechanicsRADIUSAcoustic radiation forceClassical mechanicsConservative forceLegendre polynomialsDrift velocityRadiationForce field (fiction)AccelerationLegendre functionCenter of mass (relativistic)OpticsElectric fieldBoundary value problemAcousticsQuantum mechanics

Abstract

fetched live from OpenAlex

The effect of the motion of a submerged sphere on the horizontal drift force is investigated analytically.The multipole expansion method is used to derive analytical solutions for the diffraction and radiation velocity potentials in a series of associated Legendre functions.The second-order steady force is obtained by the far field method.The effect of all velocity potentials is taken into account in derivation of the horizontal drift force.The total contribution of the radiation velocity potential is minimal to the horizontal drift force if the center of mass is at a distance less than twenty percent of the radius from the center of the sphere.The effect of the radiation velocity potential in vicinity of the resonant frequency is augmented and may create a relatively large horizontal drift force.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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)0.0030.000

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 head0.178
Teacher spread0.172 · 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

Citations0
Published2007
Admission routes2
Has abstractyes

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