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Record W2527333733 · doi:10.11159/htff16.1

Investigation of Transfer Characteristics of Complex Surfaces by using Periodic Models

2016· article· en· W2527333733 on OpenAlexvenueno aff
Gergely Kristóf

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Theoretical and Applied Studies in Material Sciences and Geometry
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Application of periodic CFD models greatly simplifies the evaluation of transfer characteristics of complex surfaces, moreover, facilitates the application of scale resolving turbulence models such as large eddy simulation. Owing to the substantial reduction of simulation domain size, and reduction of computing time of individual cases, periodic models are favorable for geometrical optimization. Geometrical simplicity also helps researchers in finding general tendencies as well as generalizing the model results. Practical applications are demonstrated in A) development of heat exchanger tubes with internal grooving and B) improving ventilation characteristics of the urban complex by optimizing building configurations. Possible technical realizations, benefits from the reduction of modelling uncertainties, as well as the limits of applicability are discussed.

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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.402

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 head0.197
Teacher spread0.185 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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