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Record W4386071100 · doi:10.11159/htff23.174

Aerodynamic Drop Breakup Suppression Due To Vaporization

2023· article· en· W4386071100 on OpenAlexvenueno aff
Bradley Boyd, Sid Becker, Ling Yue

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
FundersAmerican Chemical Society Petroleum Research Fund
KeywordsBreakupVaporizationDrop (telecommunication)AerodynamicsMechanicsMaterials scienceComputer scienceAeronauticsAerospace engineeringPhysicsEngineeringThermodynamicsTelecommunications

Abstract

fetched live from OpenAlex

The vaporization of a freely moving liquid droplet in a uniform high-temperature gas stream is investigated through direct numerical simulation.The sharp liquid-gas interface is tracked using the geometric Volume-of-Fluid (VOF) method.The incompressible Navier-Stokes equations are solved in conjunction with a two-fluid model for the thermal energy advection and conduction, with an immersed Dirichlet boundary condition at the interface to implicitly account for the latent heat absorption.The model is implemented in the open-source solver, Basilisk, which uses adaptive quadtree/octree mesh for spatial discretization and will allow for adaptive mesh refinement of the region near the interface.An acetone droplet at a moderate Weber number is simulated where the drop deforms into a bag shape and experiences breakup.The rate of vaporization of the drop is then increased to study the influence of vaporization on the drop breakup behaviour.By increasing the rate of vaporization, we observe the suppression of droplet breakup, making an otherwise unstable droplet stable.

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 score0.048
Threshold uncertainty score0.650

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 head0.005
GPT teacher head0.197
Teacher spread0.193 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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