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Record W2090871668 · doi:10.1080/15567265.2012.655850

Pressure Drop for Subsonic Gas Flow in Microchannels and Nanochannels

2012· article· en· W2090871668 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

VenueNanoscale and Microscale Thermophysical Engineering · 2012
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPressure dropMechanicsMaterials scienceMach numberFlow (mathematics)Slip (aerodynamics)Isothermal processThermodynamicsPhysics

Abstract

fetched live from OpenAlex

The objective of this article is to furnish the research and design communities with a simple and convenient means of predicting pressure drop for subsonic gas flow in microducts. The pressure drop is utilized to overcome the friction against the walls and simultaneously accelerate the flow to compensate for the decrease in density. A general pressure drop model for approximately isothermal subsonic gas flow in microchannels is proposed. The momentum changes due to gas acceleration along the channel are taken into account. The model is also extended to the transition regime by employing the appropriate second-order slip boundary conditions. As for subsonic gas flow, no solutions or graphical and tabulated data exist for almost all geometries when the outlet Mach number is greater than 0.3. The developed simple model fills this void and can be used for the practical engineering design of microchannels and nanochannels by the research and design communities.

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 score0.534
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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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