MétaCan
Menu
Back to cohort
Record W7020847907

Modelling of Wet Ice Accretions that Result from Spray

2000· article· en· W7020847907 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsAccretion (finance)Sea ice growth processesLiquid waterHeat transferIce formationNumerical modelsWater ice
DOInot available

Abstract

fetched live from OpenAlex

A morphogenetic model has been developed to predict the ice accretion on an ice sensor resulting from water spray. In the numerical model, the spray is divided into an ensemble of fluid elements and their motion and freezing are considered simultaneously. The model predicts both the ice accretion on the vertical cylindrical surface of the sensor and the accretion below the sensor, including icicle formation. The model also allows the simulation and investigation of the stochastic variability of the accretion shape, something that cannot be achieved with conventional continuous, deterministic models. The model predictions of ice accretion shape and mass have been analyzed as function of water spray mass flux and heat transfer conditions. The prediction of the overall ice structure agrees with a simple heat-balance model and our experimental data.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.999

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)0.0020.000

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 head0.022
GPT teacher head0.201
Teacher spread0.178 · 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.

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

Citations3
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicFluid Dynamics and Heat TransferFrench-language works237,207