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Record W4313021720 · doi:10.1115/gt2022-79194

100-Hour Test of an Inside-Out Ceramic Turbine Rotor at Operating Conditions

2022· article· en· W4313021720 on OpenAlexaff
P. K. Dubois, B. Picard, Antoine Gauvin-Verville, P. Méthot, Alexandre Landry-Blais, L.-P. Jean, S. Richard, Jean‐Sébastien Plante, Mathieu Picard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsTheratechnologies (Canada)Université de Sherbrooke
Fundersnot available
KeywordsTurbineShroudRotor (electric)CeramicMechanical engineeringMaterials scienceEngineeringRam air turbineSilicon nitrideAutomotive engineeringCeramic compositeElectrical engineeringSiliconComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Abstract Converting sub-MW turbine rotor blades to ceramics is not a trivial endeavour, but the promise of a substantial increase in turbine inlet temperature (TIT), and therefore cycle efficiency and power density, could mean wide use in upcoming, distributed power, turboelectric aircraft. The inside-out ceramic turbine (ICT) rotor configuration attempts to address this by loading ceramic blades in compression, as centrifugal force pushes them against a rotating structural composite shroud. This paper reports significant experimental progress in the development of ICT rotor technology, aimed at the development of a high-efficiency, turboelectric powerpack. A 20-kW scale, single spool, recuperated ICT was operated with monolithic silicon nitride blades, for a total of 113 h above 1100 °C, including 13 h at the design tip speed of 400 m/s and a cumulative 100 h at 360 m/s, with no critical failure. ICT rotors sustained short excursions with TIT up to 1200 °C and tip speeds up to 430 m/s in hot conditions, and 500 m/s in ambient conditions. An ICT rotor was successfully integrated within a complete recuperated turbogenerator with a nested high speed electric motor. Results suggest that further work on an ICT turbogenerator should enable it to reach a TIT of 1275 °C, a target to achieve 45 % cycle efficiency in the sub-MW range.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
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 score0.031
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.227
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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