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Record W2588491851 · doi:10.1080/07373937.2017.1285311

Multipin EHD dryer: Effect of electrode geometry on charge and mass transfer

2017· article· en· W2588491851 on OpenAlexafffund
Alex Martynenko, Tadeusz Kudra, Jin Yue

Bibliographic record

VenueDrying Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDepartment of Agriculture, Nova Scotia
KeywordsElectrohydrodynamicsElectrodeMass transferMechanicsMaterials scienceCurrent (fluid)Electric fieldDewateringRange (aeronautics)ThermalHeat transferAnalytical Chemistry (journal)ChemistryThermodynamicsComposite materialPhysicsEngineering

Abstract

fetched live from OpenAlex

Electrohydrodynamic (EHD) drying is considered as energy-efficient nonthermal technology suitable for dewatering of heat-sensitive materials. This technology relies on the ionic discharge from the vertical pin or fine horizontal wire, impinging wet material deposited on the plate electrode of opposite polarity. The critical issue for the scaling of EHD dryer is the geometry of a multipin/wire discharge and collecting electrodes, in particular the spacing between pins/wires and the gap between discharge electrode and material surface. This paper presents the results of experimental study and mathematical simulation of multipin discharge current to maximize total charge and mass transfer at the material surface. A mathematical model for discharge current based on Poisson’s and Warburg fundamental equations was developed and validated in experiments with multipin electrodes of different spacing (1, 2, 3, 4, and 6 cm) and gaps from 2 to 4 cm. It was demonstrated that linear relationship between total electric current and drying rate is valid for any spacing and any gap with the range from 2 to 4 cm. It was experimentally documented that the judiciously selected geometry of the multipin discharge electrode could mitigate adverse effect of interference between neighboring ionic jets and bring the concept of EHD dryer to industrial practice.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 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

Citations29
Published2017
Admission routes2
Has abstractyes

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