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Record W3036197077 · doi:10.1038/s41598-020-66800-5

Use of Surface Corrugations for Energy-Efficient Chaotic Stirring in Low Reynolds Number Flows

2020· article· en· W3036197077 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsWestern University
Fundersnot available
KeywordsReynolds numberLaminar flowMechanicsMixing (physics)Bounding overwatchLimit (mathematics)Flow (mathematics)InstabilityChaoticGroove (engineering)Particle (ecology)Energy (signal processing)Channel (broadcasting)Materials sciencePhysicsComputer scienceGeologyMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

We demonstrate that an intensive stirring can be achieved in laminar channel flows in a passive manner by utilizing the recently discovered instability waves which lead to chaotic particle movements. The stirring is suitable for mixtures made of delicate constituents prone to mechanical damage, such as bacteria and DNA samples, as collisions between the stream and both the bounding walls as well as mechanical mixing devices are avoided. Debris accumulation is prevented as no stagnant fluid zones are formed. Groove symmetries can be used to limit stirring to selected parts of the flow domain. The energy cost of flows with such stirring is either smaller or marginally larger than the energy cost of flows through smooth channels.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.486

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 head0.023
GPT teacher head0.218
Teacher spread0.195 · 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