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Record W3186169880 · doi:10.1002/fld.5035

Time‐dependent flows in grooved non‐isothermal channels

2021· article· en· W3186169880 on OpenAlexafffund
S. Panday, J. M. Floryan

Bibliographic record

VenueInternational Journal for Numerical Methods in Fluids · 2021
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiscretizationBoundary (topology)AlgorithmTemporal discretizationSpectral methodChebyshev filterComputer scienceBoundary value problemMathematicsMathematical optimizationApplied mathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract A highly accurate and fully implicit algorithm for analyses of transient effects in heated grooved channels, including chaotic responses and transition to secondary states, has been developed. The algorithm can handle pattern interaction problems arising from combinations of geometric and heating patterns which are expected to be beneficial in the development of energy efficient stirring systems. The algorithm uses spectral spatial discretization and up to sixth‐order temporal discretization, providing the means to deliver machine accuracy. The spatial discretization relies on a combination of Chebyshev and Fourier expansions, guaranteeing very good resolution in the vicinity of the grooved walls. The enforcement of boundary conditions along the irregular boundaries is carried out using the immersed boundary conditions. The overall discretization leads to a gridless algorithm and provides the geometric flexibility required for efficient analyses of multitude of topography patterns. Extensive testing demonstrates that the algorithm achieves the theoretically predicted accuracy.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.348
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.036
GPT teacher head0.388
Teacher spread0.352 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2021
Admission routes2
Has abstractyes

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