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Record W2054253174 · doi:10.1115/1.2717240

Enhanced Heat Transfer Using Porous Carbon Foam in Cross Flow—Part I: Forced Convection

2006· article· en· W2054253174 on OpenAlex
Yorwearth L. Jamin, A. A. Mohamad

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.

Bibliographic record

VenueJournal of Heat Transfer · 2006
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceHeat transferForced convectionPressure dropNusselt numberMetal foamHeat exchangerComposite materialConvective heat transferThermal resistanceHeat transfer coefficientHeat transfer enhancementPorous mediumNatural convectionPorosityMechanicsThermodynamics

Abstract

fetched live from OpenAlex

Cogeneration of heat and power has become standard practice for many industrial processes. Research to reduce the thermal resistance in heat exchangers at the gas/solid interface can lead to greater energy efficiency and resource conservation. The main objective of this experimental study is to quantify and compare the heat transfer enhancement of carbon foam and aluminum fins. The study measures the heat transfer rate and pressure drop from a heated vertical pipe, with and without porous medium, in forced convection. The largest increase in Nusselt number was achieved by aluminum fins, which was about three times greater than the best carbon foam case.

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: Empirical
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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