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Record W2315208698 · doi:10.1115/imece2008-66683

Design of Streamwise Stagger Within a Pin Fin Array to Minimize Pressure Loss

2008· article· en· W2315208698 on OpenAlexafffund
Stephen A. Andrews, W. Allan

Bibliographic record

VenueVolume 10: Heat Transfer, Fluid Flows, and Thermal Systems, Parts A, B, and C · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsRoyal Military College of Canada
FundersMinistère de la Défense Nationale
KeywordsPressure dropNusselt numberFinHeat transferMechanicsMaterials scienceRange (aeronautics)Reduction (mathematics)PhysicsGeometryReynolds numberComposite materialTurbulenceMathematics

Abstract

fetched live from OpenAlex

An experiment was conducted on the effects of streamwise stagger on heat transfer and pressure drop in a pin-fin array. The data were analyzed so as to highlight how stagger could be used to design a pin fin array for the lowest possible pressure loss. Design of arrays for low pressure loss is important in electronics cooling applications. They require large amounts of heat to be extracted from fixed areas, using a minimum of power to do so. This analysis found that the minimum friction factor occurred at a streamwise stagger of approximately 12% of the range between fully inline and fully staggered. By fixing the pin diameter, varying the stagger resulted in a 63% reduction in friction factor with only a 18% reduction in the Nusselt number, based on the array footprint. Additionally, it was found that for a fixed Nusselt number, the pin diameter could vary within a finite range, with decreasing diameters permitting arrays with more efficient degrees of stagger which continued to carry the required heating/cooling load.

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 categoriesMeta-epidemiology (narrow)
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 score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.016
GPT teacher head0.190
Teacher spread0.174 · 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.

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

Citations0
Published2008
Admission routes2
Has abstractyes

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Same venueVolume 10: Heat Transfer, Fluid Flows, and Thermal Systems, Parts A, B, and CSame topicHeat Transfer and OptimizationFrench-language works237,207