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Record W2113899553 · doi:10.1115/1.1370516

Thermal Resistance Models for Non-Circular Moving Heat Sources on a Half Space

2001· article· en· W2113899553 on OpenAlexafffund
Yuri S. Muzychka, M. M. Yovanovich

Bibliographic record

VenueJournal of Heat Transfer · 2001
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPéclet numberDimensionless quantityHeat fluxMechanicsThermal resistanceSquare rootOrientation (vector space)Square (algebra)MathematicsHeat transferMathematical analysisMaterials scienceGeometryPhysics

Abstract

fetched live from OpenAlex

Solutions to stationary and moving heat sources on a half space are reviewed for rectangular and elliptic contacts. The effects of shape, heat flux distribution, and orientation with respect to the direction of motion are examined. The dimensionless thermal resistance is shown to be a weak function of heat source shape if the square root of contact area is used as a characteristic length scale. Simple expressions are developed for calculating total thermal resistances of non-circular moving heat sources by combining asymptotic solutions for large and small values of the Peclet number. Both uniform and parabolic heat flux distributions are examined. A model is developed for predicting average or maximum flash temperatures of real sliding contacts. Comparisons of the proposed model are made with numerical solutions for two cases involving non-circular contacts.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.225
Teacher spread0.210 · 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

Citations99
Published2001
Admission routes2
Has abstractyes

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