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Record W2133565639 · doi:10.1002/qj.49712656803

Three‐dimensional modelling of ice accretion density

2000· article· en· W2133565639 on OpenAlexaff
Krzysztof Szilder, Edward P. Lozowski

Bibliographic record

VenueQuarterly Journal of the Royal Meteorological Society · 2000
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSupercoolingClear iceAccretion (finance)MechanicsAtmospheric sciencesMeteorologyPhysicsGeologyMaterials scienceAstrophysicsSea iceArctic ice packAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract A three‐dimensional, random‐walk, ballistic model is used to simulate the density and structure of an ice accretion formed by impinging supercooled droplets. The model is calibrated using experimental observations of the ice density at the stagnation line on a fixed circular cylinder. A relationship has been established between the Macklin parameter, used commonly to relate atmospheric conditions with ice accretion density, and model parameters. The model is applicable over a wide range of growth conditions, including, in the limits, growth where the droplets freeze on impact and growth where the droplets spread over and percolate into the existing ice structure.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.017
GPT teacher head0.202
Teacher spread0.185 · 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

Citations8
Published2000
Admission routes1
Has abstractyes

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