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Record W2071916147 · doi:10.1080/10407780701454238

Turbulent Mixed-Convection Cooling of Stacked Heat-Generating Bodies in a Three-Dimensional Domain

2007· article· en· W2071916147 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNumerical Heat Transfer Part A Applications · 2007
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsInletTurbulenceJet (fluid)Natural convectionMechanicsCombined forced and natural convectionForced convectionCooling towerMaterials scienceMechanical engineeringHeat transferPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract A numerical study has been conducted to investigate turbulent mixed-convection air cooling of vertical stacks of heat-generating blocks in a three-dimensional domain simulating a valve hall in a DC/AC converter station. The simulation results include detailed streamline plots of the flow structure, iso-volume plots of the temperature, the magnitude of the net flow in all tower gaps and the maximum temperature in each gap. A parametric study was conducted to explore the effects of geometry and inlet parameters on the cooling effectiveness. These results demonstrate that significant enhancements in the cooling effectiveness can be achieved by simple modifications of the angle of injection of the inlet air jet, the area of the inlet air jet, or the inlet air mass flow rate. ACKNOWLEDGEMENTS This research has been funded by grants from Manitoba Hydro and the Natural Sciences and Engineering Research Council of Canada. This funding is gratefully appreciated. Notes = 0.684 kg/s; A o,c1 = 0.2616 m2; V jet,c1 = 2.516 m/s.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.239
Teacher spread0.223 · 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