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Record W4237491808 · doi:10.5383/ijtee.13.02.001

Design and Optimization of a Radial Flow Heat Sink under Free Convection at Steady State Condition

2017· article· en· W4237491808 on OpenAlexaffvenue
Mohammad Azizur Rahman, Himangshu Bhowmik, Shuma Talukdar

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHeat sinkHeat transferFinMechanicsThermodynamicsHeat transfer coefficientConvective heat transferHeat capacity rateMaterials scienceConvectionHeat spreaderPhysicsComposite material

Abstract

fetched live from OpenAlex

Three dimensional numerical models were developed to make prediction free convection heat transfer at steady state condition from radial flow heat sink. The air was considered as the medium of heat transfer. In radial flow heat sink, heat conducts through base in radial pattern and is uniformly transported to the fins. The Tagucy method was used to investigate the effect of several design parameters such as fin length, fin height, number of fins and heat sink base radius on heat transfer. There are five factors and four levels on each factor were chosen. Sixteen types of model were analyzed to obtain total heat transfer for each model. The result was used to estimate the optimum designed values of the parameters affecting the heat sink efficiency. The reproducibility of the optimum design value was verified. The average rate of heat transfer of optimum model was increased by more than 50 % than the reference model. Finally, the heat transfer data of radial flow heat sink were correlated of several outer radius by an equation.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.498
Threshold uncertainty score0.362

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 head0.007
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 teacher head, 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

Citations1
Published2017
Admission routes2
Has abstractyes

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