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Record W2030504183 · doi:10.1080/10893950590913233

CHANNEL-TO-CHANNEL PRESSURE DIFFERENCES IN SERPENTINE MINICHANNEL FLOW SYSTEMS

2005· article· en· W2030504183 on OpenAlex

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

VenueMicroscale Thermophysical Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceDimensionless quantityFlow (mathematics)MechanicsReynolds numberChannel (broadcasting)Pressure gradientOpen-channel flowPressure dropFlow conditionsFinite element methodThermodynamicsPhysicsTelecommunicationsComputer scienceTurbulence

Abstract

fetched live from OpenAlex

One of the interconnected factors that can lead to failures in the flow plates of PEM fuel cells is the pressure differences that exist between adjacent flow channels. These pressure differences lead to stresses in the channel supports—i.e., the ribs—which can be important in the presence of stresses arising due to other factors such as temperature gradients in the flow plates. In order to investigate the magnitudes of the pressure differences across the supports and the places where the maximum pressure differences occur, the flow and pressure variations in various forms of serpentine channels, these channels having a rectangular cross-sectional shape, have been numerically calculated. The presence of the diffusion layer has been ignored and the flow has been calculated using a commercial finite-element software package using the governing equations written in dimensionless form. Solutions have been obtained for various values of the Reynolds number for each of the flow geometries considered for two chan...

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.183
Teacher spread0.176 · 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