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Record W2022409413 · doi:10.1115/gt2004-53377

Set Up and Operational Experience With a Micro-Turbine Engine for Research and Education

2004· article· en· W2022409413 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsJet engineTurbomachineryTurbineInstallationAutomotive engineeringCentrifugal compressorEngineeringGas compressorTurbofanThrustComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Set up and operation of a mid to large size gas turbine requires a significant investment in the engine and the test cell. The continuing cost of operation and maintenance is also substantial. Both the capital and operating costs are well outside the budget of many educational institutions, and small research centres. Micro-turbines, in particular engines used for model aircraft, are a viable alternative. Their capital costs are low and existing facilities can often be modified to support them. Micro-turbines are complete turbojets often utilizing a centrifugal compressor from a turbo-charger and an axial turbine. This work utilized a micro-jet engine commonly used to propel remote control aircraft. The engine has been set up for research into component degradation and as a laboratory for an upper year engineering course in turbomachinery. It is rated by the manufacturer to produce 150 N of thrust at 132,000 RPM. This paper examines some of the problems encountered in installing small total pressure and temperature probes in a micro engine. The entire test rig, including measurement of thrust and mass flow is presented. As well, the addition of a PC based control system is discussed. Operating data is presented and compared to larger engines to demonstrate the viability of this engine as a test bed. Some problems encountered in using an engine such as this beyond its normal operating envelope, along with some solutions, are presented.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.176

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 head0.024
GPT teacher head0.305
Teacher spread0.280 · 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