MétaCan
Menu
Back to cohort
Record W4213416983 · doi:10.1080/02786826.2022.2030463

Development and testing of a universal aerosol conditioner

2022· article· en· W4213416983 on OpenAlexafffund
Kerry Chen, Robert T. Nishida, Charles Robert Koch, Jason S. Olfert

Bibliographic record

VenueAerosol Science and Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerosolParticle (ecology)MechanicsChemistryDilutionVolumetric flow rateGas phaseMeteorologyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

A general purpose aerosol conditioning device called the Universal Aerosol Conditioner (UAC) has been designed and tested. The device may be used to condition an aerosol in multiple ways: dilute the entire aerosol (gas- and particle-phase), dilute only a gas-phase component of the aerosol without diluting the particle concentration, denude the aerosol by removing semi-volatile material from the particle phase, and humidify or dehumidify an aerosol. The UAC accomplishes these processes by bringing the aerosol into contact with sheath air and allowing enough time for gas-phase components of the aerosol to diffuse into the sheath flow. A model was developed to assess the theoretical performance of the UAC and was solved numerically. From the model it was determined that two parameters dictated the rate of diffusion between the two flows: the Péclet number and the ratio of sheath-to-aerosol flow rates. A prototype was designed and built and the theory of operation was experimentally validated by measuring the particle penetration efficiency and the gas dilution factor at various particle sizes and flow conditions. The results showed that at low aerosol and sheath flows, the prototype behaved closely to the theoretical model but diverged from the theory once the sheath flows were increased, presumably due to mixing between the two flows.Copyright © 2022 American Association for Aerosol Research

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 score0.248
Threshold uncertainty score0.248

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueAerosol Science and TechnologySame topicParticle Dynamics in Fluid FlowsFrench-language works237,207