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Record W2116304184 · doi:10.1109/tpwrd.2003.820216

Coolant Flow Distribution and Pressure Loss in ONAN Transformer Windings—Part II: Optimization of Design Parameters

2004· article· en· W2116304184 on OpenAlexaff
J. Zhang, Xiaogang Li

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2004
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMechanicsMass flow rateVolumetric flow rateMaterials scienceElectromagnetic coilTransformerMass flowCoolantDistribution transformerFlow (mathematics)Electrical engineeringThermodynamicsEngineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

For pt.1, see ibid., vol.19, no.1, p.186-93, January 2004. The effects of total mass flow rate, flow arrangement, and geometrical parameters in ONAN transformer windings are investigated. It is found that the conventional minor losses are predominant in determining the mass flow distribution and pressure losses for the present flows. The sizes of the cooling ducts and the number of disks per pass have strong influence on both the mass flow distribution and the pressure loss. Flow arrangement in the horizontal ducts can have significant influence on the flow distribution, hence on the hot spot formation. Since the rate of heat generation increases in the vertical direction, a corresponding increase in the cooling oil flow rate vertically will optimize winding performance.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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

Citations28
Published2004
Admission routes1
Has abstractyes

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