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Record W2083660442 · doi:10.1093/qjmam/hbq011

Microelastohydrodynamics of Swimming Organisms Near Solid Boundaries in Complex Fluids

2010· article· en· W2083660442 on OpenAlexaff
Neil J. Balmforth, Daniel Coombs, Sydney Pachmann

Bibliographic record

VenueThe Quarterly Journal of Mechanics and Applied Mathematics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMechanicsComplex fluidNon-Newtonian fluidNewtonian fluidDilatantForcing (mathematics)Shear thinningShear (geology)Shear stressLubricationThickeningFluid motionClassical mechanicsMaterials sciencePhysicsRheologyThermodynamicsComposite material

Abstract

fetched live from OpenAlex

Microorganisms such as sperm routinely swim close to solid boundaries and within non-Newtonian fluids. In this paper, we exploit the lubrication approximation to model the motion of a flexible sheet near a rigid wall and immersed in a complex fluid. This allows us to specify an internally generated force density on the sheet and allow its shape and velocity to be determined by the interplay between the forcing and the fluid motion. We obtain results for Newtonian and complex fluids, focusing specifically on the influence of shear thinning/thickening and of yield stress. In the latter case, we characterise the threshold forcing that is required for successful swimming to occur. Our results highlight the usefulness of the lubrication approach in modelling micro-scale fluid–structure 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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.224
Teacher spread0.217 · 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

Citations37
Published2010
Admission routes1
Has abstractyes

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