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Record W2278149846 · doi:10.1088/1009-0630/18/3/19

Study on Free Surface and Channel Flow Induced by Low-Temperature Plasma via Lattice Boltzmann Method

2016· article· en· W2278149846 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePlasma Science and Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsPlasma actuatorLattice Boltzmann methodsPlasmaVolumetric flow rateVortexMechanicsBoundary layerFlow velocityFlow control (data)Flow (mathematics)Open-channel flowChemistryMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Active boundary layer flow control and boundary layer manipulation in the channel flow that was based on low temperature plasma were studied by means of a lattice Boltzmann method. Two plasma actuators were placed in a row to obtain the influence rule of their separation distance on the velocity profile at three locations and maximum velocity in the flow field. Two plasma actuators were placed symmetrically inside a channel to examine the effect of channel height and voltage on the velocity profile and flow rate. It was found that the channel height controls the distribution of flow velocity, which affected the flow rate and its direction. Increasing plasma voltage had a negative effect on the flow rate due to the generation of a larger and stronger flow vortex.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.261
Teacher spread0.245 · 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