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Record W4313887472 · doi:10.1080/10407782.2022.2157351

Large-eddy-simulation of turbulent buoyant flow and conjugate heat transfer in a cubic cavity with fin ribbed radiators

2023· article· en· W4313887472 on OpenAlexaff
Sadia Siddiqa, Sahrish Batool Naqvi, Muhammad Azam, Abdelraheem M. Aly, Md. Mamun Molla

Bibliographic record

VenueNumerical Heat Transfer Part A Applications · 2023
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsConcordia University
FundersNorth South University
KeywordsTurbulenceMechanicsHeat transferLarge eddy simulationTurbulence kinetic energyPhysicsConvectionConvective heat transferVortexClassical mechanics

Abstract

fetched live from OpenAlex

Turbulent convective flow in a cubic cavity is a fundamental model observed in various processes that appeared in environmental and industrial applications. The turbulent fluctuations in the flow field, fluid-solid interaction/coupling, and the transient nature of the problem make it challenging to establish numerical modeling. The turbulent flow and convective heat transfer in a cubic cavity fixed with three fins are studied here. The numerical solutions are obtained through large-eddy simulation with Smagorinsky subgrid-scale model combined with conjugate heat transfer to incorporate temperature distribution in solid fins. The upper and lower walls of the enclosure are differently heated, while the lateral walls are adiabatic, and equally spaced conductive fins are located at the bottom surface. The solutions are initially compared with the numerical and experimental results for validation purposes. Successively, the model is applied to explore the impact of a material (copper) that makes up the horizontal wall on the flow field. We found that the heat transfer essentially alters the turbulent field, and the flow field becomes less homogeneous along the vertical direction. A number of streaky and coherent turbulent structures are found with varying magnitudes. The Q-criterion, second-invariant of the velocity-gradient tensor, predicted that strong vortices occur near the fins and in the surrounding regions of the cavity. Moreover, the energy (entropy) spectral, which plays a crucial role in engineering applications and turbulent theory, is also presented, showing the contribution of each frequency component to the velocity (temperature) variance at a given point. The velocity and temperature fields are found to be anti-symmetric, except close to the front and back walls. The major cause for this is the conducting bottom and fins, which produces thermal stratification in the cavity. The conducting bottom induces the locally unstable thermal stratification in the vicinity of the wall, which intensifies the turbulence as the flow advances toward the temperature-controlled boundaries. Further, the turbulent exchange in the central region is more responsible for the heat transfer than convection that occurs due to the differentially heated walls.

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)0.001
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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