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Fans and Blowers

2012· other· en· W1526886564 on OpenAlex
Keith Marchildon, David Mody

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

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2012
Typeother
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsFan-inCentrifugal fanUpstream (networking)Downstream (manufacturing)EngineeringVibrationMechanical engineeringFlow (mathematics)Process (computing)Automotive engineeringStructural engineeringComputer scienceAcousticsPhysicsMechanicsTelecommunicationsOperations management

Abstract

fetched live from OpenAlex

Abstract Gas movers with low fractional rise of pressure are discussed. These devices are fans (subsuming the term blower) and are of two types, centrifugal and axial. For both types, the principles are presented including the derivation and application of the important rules of affinity. The relation is shown between vendor specification and fan performance. The variety of fan geometries is surveyed and the interaction is examined between a fan and other process components upstream and downstream. Also reviewed are essential auxiliaries, namely fan drives, flow conditioners, noise and vibration controls, and drive seals.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.619
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.002
GPT teacher head0.182
Teacher spread0.180 · 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