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Record W2323329457 · doi:10.1115/fedsm-icnmm2010-30145

Numerical Investigation and Geometric Parameterization of Lamination Inlet of Passive Micromixer

2010· article· en· W2323329457 on OpenAlexaff
Yanfeng Fan, Ibrahim Hassan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicromixerLaminationMixing (physics)InletReynolds numberMechanicsMicrochannelPerpendicularMaterials scienceFlow (mathematics)VortexGeometryPhysicsMechanical engineeringTurbulenceEngineeringMathematicsComposite material

Abstract

fetched live from OpenAlex

A lamination inlet is proposed and optimized in this paper. The perpendicular incoming fluids are applied instead of parallel type. The total mixing length is fixed at 3.2 mm and the depth of channel is fixed at 0.1 mm. The tested Reynolds number is calculated at the entrance of downstream straight channel. The tested Reynolds numbers range from 5 to 200. The perpendicular incoming type enhances the mass-convection and enlarges the interface area. Two parameters, the radius of holes (R) and the distance between two holes (D1), are selected to achieve the optimization. Numerical simulation is used to estimate the mixing performance and flow characteristics. The results show that the vortices are generated in the microchannel. The interface becomes irregular. In order to evaluate the mixing improvement, the parallel lamination is also simulated. The comparison shows that the perpendicular inlet type has better mixing efficiency than the parallel lamination type. This inlet type could be connected with certain mixing element to achieve the applications in biochemistry.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.202

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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 designBench or experimental
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

Citations1
Published2010
Admission routes1
Has abstractyes

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