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Record W2907715366 · doi:10.1080/07373937.2018.1531291

Numerical investigation of the multi-pin electrohydrodynamic dryer: Effect of cross-flow air stream

2019· article· en· W2907715366 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

VenueDrying Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsWestern UniversityDalhousie University
Fundersnot available
KeywordsElectrohydrodynamicsMechanicsFlow (mathematics)Computer simulationAirflowElectric fieldMaterials scienceIntensity (physics)Range (aeronautics)MoistureEnvironmental scienceSimulationMechanical engineeringEngineeringPhysicsOpticsComposite material

Abstract

fetched live from OpenAlex

This article presents the results of numerical simulation and experimental study of a multi-pin electrohydrodynamic (EHD) dryer. Combined effect of EHD flow and the external air cross-flow on drying performance was investigated with 3-D numerical model, which accounts for electric field, electric charge transport, external air cross-flow and material-gas moisture transport. Effect of cross-flow air stream on drying was positive in the range of low velocities, changing to negative at high velocities due to counteracting with EHD flow. Numerical simulation predicted previously unknown effect of EHD flow on the cross-flow air stream, which was quantified as an increase of airway resistance. This prediction was fully validated by experiments. Both numerical simulation and experiment proved that for given intensity of EHD flow there is an optimum value of the cross-flow, resulting in maximum drying performance. The numerical model can be applied to determine the optimal operating parameters for multi-pin EHD dryer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.225
Teacher spread0.221 · 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