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A Model for Thermal-Hydraulic Characteristics of Offset Strip Fin Arrays for Large Prandtl Number Liquids

2009· article· en· W2081421982 on OpenAlexaff
Yuri S. Muzychka, Gaetan K. Kenway

Bibliographic record

VenueEnhanced heat transfer/Journal of enhanced heat transfer · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPrandtl numberTurbulent Prandtl numberMechanicsReynolds numberLaminar flowTurbulenceOffset (computer science)Materials scienceThermodynamicsPhysicsNusselt numberHeat transferComputer science

Abstract

fetched live from OpenAlex

An extended model for predicting thermal-hydraulic characteristics of offset strip fin arrays is developed for fluids with Prandtl number greater than unity. This new model is based on the asymptotic behavior for the laminar and turbulent wake regions with an empirically derived correlation for the effect of Prandtl number suppression on the j factor. The proposed models are compared with existing data for air, water, and polyalphaolefin (PAO), and new data for 5W30 engine oil. Model predictions are within ±20 percent or better for most data sets. The new models for f and j cover a wide range of Reynolds number, 1 < Re < 10,000 and Prandtl number, 0.7 < Pr < 620. A total of 39 unique data sets were used in the present model development.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.242
Teacher spread0.229 · 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 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

Citations4
Published2009
Admission routes1
Has abstractyes

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