MétaCan
Menu
Back to cohort
Record W2137944956 · doi:10.1115/imece2004-61323

Compact Models for Transient Conduction or Viscous Transport in Non-Circular Geometries With a Uniform Source

2004· article· en· W2137944956 on OpenAlexaff
Yuri S. Muzychka, M. M. Yovanovich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
Fundersnot available
KeywordsDimensionless quantityThermal conductionMathematical analysisRectangleCross section (physics)MathematicsMechanicsGeometryAnnulus (botany)ScalingTransient (computer programming)Constant (computer programming)PhysicsSquare (algebra)Materials scienceThermodynamics

Abstract

fetched live from OpenAlex

Transient heat conduction in solid prismatic bars of constant cross-sectional area having uniform heat generation and unsteady momentum transport in infinitely long ducts of arbitrary but constant cross-sectional area are examined. In both cases the solutions are mathematically modeled using a transient Poisson equation. By means of scaling analysis a general asymptotic model is developed for an arbitrary non-circular cross-section. Further, by means of a novel characteristic length scale, the solutions for a number of fundamental shapes are shown to be weak functions of geometry. The proposed models can be used to predict the dimensionless mean flux at the wall and the area averaged temperature or velocity for the tube, annulus, channel and rectangle for which exact series solutions exist. Due to the asymptotic nature of the proposed models, it is shown that they are also applicable to other shapes at short and long times for which no solutions or data exist. The root mean square (RMS) error based on comparisons with exact results is between 2.2–7.6 percent for all data considered.

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 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 score0.723
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.217
Teacher spread0.199 · 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.

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

Citations1
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicHeat Transfer and OptimizationFrench-language works237,207