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Record W2887901317 · doi:10.11159/htff18.144

Modelling Local Nusselt Numbers for Channels with Flow in Transition

2018· article· en· W2887901317 on OpenAlexaffvenue
Iván Cornejo, Petr A. Nikrityuk, Robert E. Hayes

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNusselt numberFlow (mathematics)Transition (genetics)MechanicsComputer sciencePhysicsReynolds numberTurbulenceChemistry

Abstract

fetched live from OpenAlex

This work reports a study of heat transfer in turbulent flow entering into small channels, which causes a transition to laminar flow.Heat transfer in channels has been extensively studied, especially the Nusselt-Graetz problem, most commonly constant wall temperature or constant wall heat flux.Early works reported Nusselt values for circular pipes with laminar developed flows, including analytical solutions validated with experiments.Later, developing laminar flows were also studied, presenting correlations for Nusselt-Greatz along the entry region.Most of the engineering flows are turbulent, in such flows, convection increases significantly and laminar flow assumptions are not valid.Although that there are Nusselt numbers reported for the developed turbulent flows, describing the entry region is still a challenge.In literature, flows in circular channels are classified into three main categories: Laminar for Re < 2 300, turbulent for Re > 10 000, and transitional for the Re in between [1].However, some cases, such as monolith type substrates, fit into none of those categories.Monolith based reactors are extensively used in the automotive industry, since they produce lower pressure drop than fixed beds; they are implemented in several other industrial processes as well.It creates a growing interest in its modelling [2,3].Usually, the flow before a monolith is turbulent (Re ~ 10 4 ), however, its pass from an inlet pipe to channels that are one or two orders of magnitude smaller, decreases the Reynolds number dramatically.Although, there is a strong reduction of the Reynolds, to the order of 10 2 typically, turbulence is still strong in the entry region.In these cases, laminar flow does not apply, also, correlations for turbulent flow are not meant to work at such low Reynolds numbers, neither for decaying turbulence.Clearly the decaying turbulence will affect the mass and heat transfer coefficients in the entry region, which could have a significant impact on the performance of the entire reactor; hence, it must be described accurately.The goal of this study is to identify and quantify the effect of the decaying turbulence on the Nusselt along the entry region of monolith channels.We used circular channels as a first approach, which are still not studied under the mentioned conditions.Given the difficulty to measure accurate profiles inside channels of about 1 mm of diameter [4], the study used Large Eddy Simulation, which is a highly precise and extensively validated numerical technique, suitable for flows in transition.The results agreed previously reported data [1,5], also showed a significant effect of the entering turbulence on the Nusselt along the beginning of the channels.This work extends available models for laminar flow, to take into account the turbulence.The proposed model describes the heat transfer in the transitional region accurately; it also converges to the correct Nusselt in the fully developed laminar zone.RANS models were also tested, finding different levels of agreement, but, in general, resulting not suitable to describe the entire region accurately.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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 designSimulation or modeling
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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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