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Record W2024170475 · doi:10.1115/icnmm2009-82076

The Numerical Simulation of a Passive Interdigital Micromixer With Uneven Lamellar Width

2009· article· en· W2024170475 on OpenAlexaff
Yanfeng Fan, Ibrahim Hassan

Bibliographic record

VenueASME 2009 7th International Conference on Nanochannels, Microchannels, and Minichannels · 2009
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicromixerMixing (physics)Materials scienceReynolds numberMechanicsInletComputer simulationPressure dropMicrofluidicsMechanical engineeringPhysicsEngineeringNanotechnology

Abstract

fetched live from OpenAlex

In this paper, a passive micromixer with interdigital structure is proposed and investigated using numerical simulations. The micromixer contains three layers to achieve the interdigital flow structure. The height of mixing channels is fixed as 0.2 mm. The total width of inlets is 0.9 mm. The mixing regime is rectangular in shape. The Reynolds number, measured at the entrance of straight channel, ranges from 5 to 60. Grid independence is performed to minimize the influence of numerical diffusion on simulation results. The grid size is selected as 6 μm, which can be considered as optimal. The interdigital micromixers with straight downstream channels are designed and simulated. In order to achieve better mixing near the inner walls, uneven lamellae width of each species is applied to create a larger concentration gradient near the inner walls. The results show that the micromixer with uneven lamellar width is able to enhance the mixing near the inner walls. A new passive micromixer with the uneven interdigital inlets is also designed to improve the mixing efficiency at high Re. The simulation results show that this new micromixer has a mixing efficiency larger than 80%, and a maximum pressure drop of 2.7 KPa.

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 categoriesMeta-epidemiology (narrow)
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 score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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.

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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueASME 2009 7th International Conference on Nanochannels, Microchannels, and MinichannelsSame topicPlasma and Flow Control in AerodynamicsFrench-language works237,207