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Record W2332878678 · doi:10.1017/jfm.2014.120

Slender axisymmetric Stokesian swimmers

2014· article· en· W2332878678 on OpenAlexaff
Srikanth Toppaladoddi, Neil J. Balmforth

Bibliographic record

VenueJournal of Fluid Mechanics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of British Columbia
FundersOffice of Naval ResearchUniversity of OxfordYale UniversityNational Science Foundation
KeywordsMechanicsPhysicsTransverse planeRotational symmetrySurface (topology)Classical mechanicsLongitudinal waveShell (structure)Slender-body theoryNonlinear systemSurface waveFlow (mathematics)Wave propagationMaterials scienceStokes flowOpticsGeometryMathematicsStructural engineering

Abstract

fetched live from OpenAlex

Abstract Slender-body theory is used to study axisymmetric swimmers propelled by motions of their surfaces. To leading order, the locomotion speed is given by an integral involving the fluid velocity at the surface of the slender body. Locomotion speeds are calculated for fixed-shape swimmers with prescribed fluid surface velocities and for impermeable swimmers driven by propagating surface waves. Next, the internal mechanics is considered, modelling the swimmer as a viscous fluid bounded by an elastic shell. Prescribed forces are exerted on the shell to drive both the internal and external fluid flow and the surface waves. The internal fluid mechanics is determined using lubrication theory. Locomotion speeds are calculated for transverse and longitudinal waves of surface deformation, and the efficiency of the motions is determined. Transverse surface waves are both weaker and less efficient at driving locomotion than longitudinal waves. The results indicate how estimates of swimming speed based on nearly spherical swimmers with low-amplitude surface waves can be adapted for slender swimmers with nonlinear surface deformations.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.441

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 head0.007
GPT teacher head0.214
Teacher spread0.208 · 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 designTheoretical or conceptual
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

Citations7
Published2014
Admission routes1
Has abstractyes

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