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Record W1987771410 · doi:10.1115/1.2759976

Flow, Thermal, Energy Transfer, and Entropy Generation Characteristics Inside Wavy Enclosures Filled With Microstructures

2007· article· en· W1987771410 on OpenAlex
Shohel Mahmud, Roydon Fraser, Ioan Pop

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 · 2007
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStreamlines, streaklines, and pathlinesWavinessNusselt numberMechanicsEnclosureHeat transferReynolds numberMaterials scienceThermodynamicsPhysicsTurbulence

Abstract

fetched live from OpenAlex

Flow, thermal, energy, and irreversibility characteristics inside wavy enclosures packed with microstructures are reported in this paper. It is assumed that the entire enclosure has sufficient and interconnected void spaces; those allow fluid movement inside the cavity. The Darcy momentum equation is selected for momentum transfer modeling by considering a relatively small pore Reynolds number (Rep). Modeled equations are solved numerically using the finite volume method. Streamlines, isothermal lines, energy streamlines, average Nusselt number, and average entropy generation number are calculated and displayed in order to show their dependency on and variation with Rayleigh number (Ra), surface waviness (λ), and aspect ratio (AR) of the enclosure. Depending on the wall waviness pattern, the enclosure is divided into three modes (phase-plus, phase-zero, and phase-minus modes). However, for the current calculation, wall waviness is kept symmetric with respect to the vertical and horizontal centerlines of the enclosure.

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 categoriesnone
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 score0.175
Threshold uncertainty score0.924

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 head0.007
GPT teacher head0.189
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