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Record W4233948256 · doi:10.32920/ryerson.14656749

Modeling and Development of an Experimental Pneumatic Facility for Aircraft Bleed Air System Studies

2021· preprint· en· W4233948256 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMass flowBleedEnvironmental control systemFlow (mathematics)Automotive engineeringEngineeringControl systemAirflowSimulationAerospace engineeringComputer scienceMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Research on aircraft bleed air systems has been performed at Ryerson University for the last eight years. During this time, the requirements of the test apparatus have been constantly expanding. This thesis work aims at developing a new reconfigurable rig that supports current and future research on aircraft bleed air control systems and takes advantage of lessons learned from previous test rigs. The new rig consists of two temperature control channels in a parallel arrangement to allow for flow sharing control, and a load tank with variable exhaust. Beyond the development of the test rig, research has been performed to improve mass flow measurement based on signals from traditional thermal mass flow and pressure sensors. The proposed method utilized these redundant means of indicating flow to obtain fast and accurate flow measurement through the use of a dynamically weighted average. This method has been experimentally investigated using the test rig.

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 score0.272
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 science0.0000.001
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 head0.091
GPT teacher head0.342
Teacher spread0.250 · 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

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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