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Record W2318796785 · doi:10.3390/wsf-4-e016

Effects of Velocity and Thermal Boundary Layer with Sustainable Thermal Control Across Flat Plates

2014· article· en· W2318796785 on OpenAlexaff
Emmanuel O. Ogedengbe, Pius Okpara, Marc A. Rosen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBoundary layerBoundary (topology)MechanicsFinite difference methodBoundary value problemThermalHeat transferFinite differenceBoundary layer thicknessComputer scienceMaterials scienceMathematicsPhysicsMathematical analysisThermodynamics

Abstract

fetched live from OpenAlex

Numerical simulations of boundary layers play a significant role in the study and interpretation of physical experiments for theoretical explanations of boundary layer disturbances. The influence of thermal boundary layer on the control of heat transport across flat plates is particularly examined. The Crank-Nicolson differential method, which is widely favoured for finite-difference modelling of boundary layer equations, is reviewed. The stability of this method is compared with other numerical approaches in order to establish the appropriate scheme for sustainable applications, involving the design of any conjugate system with heat transfer between the solid and fluid interface. Specific applications to the analysis of cabin comfort in automobiles are anticipated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.002
GPT teacher head0.203
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes1
Has abstractyes

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