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Record W194455555

Flow Visualization within the Liquid Phase of Pool Fire

2013· article· en· W194455555 on OpenAlexafffund
Alireza Vali, David S. Nobes, L.K. Kostiuk

Bibliographic record

VenueResearch Repository (Delft University of Technology) · 2013
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoundary layerMaterials scienceThermocoupleCombustorMechanicsTemperature gradientBoilingFlow (mathematics)Layer (electronics)ThermalChemistryThermodynamicsMeteorologyComposite materialCombustion
DOInot available

Abstract

fetched live from OpenAlex

The effects of altering the lower thermal boundary condition of a methanol pool from -5 °C to 50°C was investigated within a 90 mm diameter and 12 mm deep quartz burner under steady state burning condition in a quiescent air environment. The temperature and velocity within the liquid were measured by a single thermocouple traversed through the pool and PIV, respectively, in order to better understand the transport of mass and energy in the liquid. Temperature measurements revealed a distinct two-layer vertical thermal structure with the upper layer of the pool being almost uniform and near the boiling temperature of the fuel, while in the lower layer experienced an increasing temperature gradient as the bottom boundary temperature was lowered. The thickness of the thermally uniform layer increased as the bottom temperature was increased. The measured fluid velocity showed a complementary two-layer structure with the upper layer being dominated by a pair of counter-rotating vortices that kept this portion of the liquid well mixed and transferred heat from the hot pool wall to the pool center, while the flow in the lower layer was uniformly low in value and vertical.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.279

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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 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

Citations0
Published2013
Admission routes2
Has abstractyes

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