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Record W2170536830 · doi:10.1115/1.1569508

Thermobuoyancy Treatment for Electronic Packaging Using an Improved Advection Scheme

2003· article· en· W2170536830 on OpenAlexaff
Masoud Darbandi, G. E. Schneider

Bibliographic record

VenueJournal of Electronic Packaging · 2003
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAdvectionBuoyancyMechanicsContext (archaeology)Natural convectionTerm (time)ConvectionHeat transferWork (physics)Control volumeGridFlow (mathematics)MeteorologyComputer scienceEnvironmental sciencePhysicsThermodynamicsMathematicsGeologyGeometry

Abstract

fetched live from OpenAlex

The complex nature of the convective terms in the fluid flow governing equations has caused many researchers to work on estimating more accurate advection term magnitudes by employing better approximate expressions. The trend of progress has been to include more physics of flow in the approximations. However, there is no archival evidence that reports the direct implementation of buoyancy as a physical influence in the advection term modeling. In this work, the influence of buoyancy in an efficient advection term expression is investigated in a control volume context with a collocated grid arrangement. The accuracy of the results obtained by both excluding and including the buoyancy term is evaluated through application to the natural convection heat transfer problem in a cavity at different Rayleigh numbers.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.255
Teacher spread0.242 · 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

Citations19
Published2003
Admission routes1
Has abstractyes

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