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Record W2907152573 · doi:10.1080/10407790.2018.1538290

The temperature decomposition method for periodic thermal flows with general wall conditions

2018· article· en· W2907152573 on OpenAlex
Ping Li, Junfeng Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNumerical Heat Transfer Part B Fundamentals · 2018
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research GridCompute Canada
KeywordsTransient (computer programming)Heat fluxBoundary value problemThermalWork (physics)Boundary (topology)MechanicsFlow (mathematics)Periodic boundary conditionsDomain decomposition methodsHeat transferComputer scienceMathematicsThermodynamicsPhysicsMathematical analysisFinite element method

Abstract

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Thermal flows through periodic structures can be found in many industrial applications. By taking advantage of the relationships of flow and thermal fields in periodic modules, computer simulations can be performed over a one-module domain; however, the results can be applied to individual modules. At present this approach is limited to systems with relatively simple boundary situations: either the temperature or heat flux can be specified over the wall surfaces. To address this concern, we develop a temperature decomposition method that can work with more general boundary situations, including the mixed (temperature on some locations and heat flux on other locations) and the convective boundary conditions. The regular temperature is split into two components, namely the transient and equilibrium parts. The transient part decays with the flow and the temperature approaches the equilibrium part gradually. The two components can be solved independently under similar governing equations but different wall and inlet/outlet boundary conditions. The regular temperature can then be quickly obtained by adding them together according to the transient coefficients of individual periodic modules. The algorithm and implementation are described in details, and the method is discussed thoroughly from mathematical and physical considerations. Carefully designed example simulations are also presented to demonstrate the capacity and usefulness of this method for future simulations of thermal periodic flows using various numerical schemes.

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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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.683

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 studies0.0010.000
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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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