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Record W226452713 · doi:10.1139/tcsme-2008-0007

APPLICATION OF SECOND MOMENT CLOSURE AND HIGHER ORDER GENERALIZED GRADIENT DIFFUSION HYPOTHESIS TO IMPINGEMENT HEAT TRANSFER

2008· article· en· W226452713 on OpenAlexvenueno aff
Farzad Bazdidi–Tehrani, Mehran Rajabi‐Zargarabadi

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsNusselt numberMechanicsTurbulenceReynolds numberHeat transferClosure (psychology)Churchill–Bernstein equationMoment closureHeat fluxMoment (physics)Reynolds-averaged Navier–Stokes equationsThermodynamicsSecond moment of areaPhysicsMaterials scienceStatistical physicsClassical mechanics

Abstract

fetched live from OpenAlex

This paper discusses the importance of turbulent heat flux modeling in predicting an impinging flow. A higher order version of the generalized gradient diffusion hypothesis (HOGGDH) is employed for the simulation of turbulent heat flux in impingement heat transfer. The flow field is modeled with both high and low Reynolds second moment closure turbulence models. For the high Reynolds second moment closure both GGDH and HOGGDH are not capable of capturing the shape of local Nusselt number profile in the impingement region. Combination of the low Reynolds second moment closure with either GGDH or HOGGDH models can reasonably predict the local Nusselt number distribution in comparison with the available experimental data. Results show that the HOGGDH over-predicts the turbulent heat transfer and the local Nusselt number particularly in the impingement zone.

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: none
Teacher disagreement score0.682
Threshold uncertainty score0.736

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 head0.013
GPT teacher head0.187
Teacher spread0.174 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

Explore more

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