MétaCan
Menu
Back to cohort
Record W4402689186 · doi:10.2514/1.t7332

Ice Crystal Environment-Modular Axial Compressor Rig: Critical Temperatures for Accretion

2024· article· en· W4402689186 on OpenAlexaff
Martin Neuteboom, Jeanne G. Mason, Philip Chow, Christopher Dumont

Bibliographic record

VenueJournal of Thermophysics and Heat Transfer · 2024
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsNational Research Council Canada
FundersFederal Aviation AdministrationNational Research Council
KeywordsModular designAccretion (finance)Gas compressorIce crystalsGeologyAstrobiologyAerospace engineeringMaterials scienceEnvironmental scienceComputer scienceMeteorologyPhysicsEngineeringAstrophysicsOperating system

Abstract

fetched live from OpenAlex

The Ice Crystal Environment Modular Axial Compressor Rig (ICE-MACR) is a purpose-built compressor rig for investigating the physics of inflight ice crystal icing of turbofan aircraft engines. The onset of ice accretion within the rig against various parameters of temperature, such as gas path static temperature, gas path wet bulb temperature, and casing metal temperature, has been studied. Changes in accretion behavior as a function of the various temperatures within the ICE-MACR are explored. True accretion, which needs the presence of melt water, requires a gas path static temperature warmer than freezing. Accretion can occur as temperatures increase until the static wet bulb temperature exceeds freezing, at which point no steady accretion growth can occur. Total wet bulb temperature (TWB0) was not found to be a trigger for accretion; however, it does affect the accretion characteristics. Based on the observed static temperature and static wet bulb temperature limits on accretion, a theoretical temperature range within a compressor prone to ice crystal icing can be calculated. This range is predicted to be significantly smaller for an engine operating at sea level than at altitude.

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 score0.280
Threshold uncertainty score0.377

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 head0.010
GPT teacher head0.226
Teacher spread0.217 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Thermophysics and Heat TransferSame topicSpacecraft and Cryogenic TechnologiesFrench-language works237,207