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Record W4233693178 · doi:10.1115/1.4049303

Experimental Assessment of a Sliding-Blade Inside-Out Ceramic Turbine

2020· article· en· W4233693178 on OpenAlexaff
Dominik Thibault, P. K. Dubois, B. Picard, Alexandre Landry-Blais, Jean‐Sébastien Plante, Mathieu Picard

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2020
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsShroudCeramicTurbine bladeTurbineMechanical engineeringTurbochargerMaterials scienceBlade (archaeology)Reliability (semiconductor)Structural engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract In order to reach 40% efficiency, sub-MW turbines must operate in a recuperated gas Brayton cycle at a turbine inlet temperature (TIT) above 1300 °C. Current sub-MW turbines have material-related operating temperature limits. Still to this day, there is no cost-effective rotor design which operates at such high temperatures. This paper introduces a novel, sliding-blade, inside-out ceramic turbine (ICT) wheel configuration, which could enable high-efficiency sub-MW recuperated engines to be achieved with cheap monolithic ceramic blades. The inside-out configuration uses a rotating structural hoop, or shroud, to convert centrifugal forces into compressive blade loading. The sliding-blade architecture uses a hub with angled planes on which ceramic blades slide up and down, allowing to match the radial expansion of the structural shroud. This configuration generates low stress values in both ceramic and metallic components and can achieve high tip speeds. A prototype is designed and its reliability is calculated using cares software. The result is a design which has a single blade probability of failure (Pf) of 0.1% for 1000 h of steady operation. Analyses also demonstrate that reliability is greatly dependent on friction at ceramic-to-metal interfaces. Low friction could lead to acceptable reliability levels for engine applications. The prototype was successfully tested in a laboratory turbine environment at a tip speed of 350 m/s and a TIT of 1100 °C without any damage. These achievements demonstrate the robustness of the sliding-blade ICT configuration. Further research and development will focus on increasing tip speed and TIT to higher values.

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 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 score0.103
Threshold uncertainty score0.547

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 head0.240
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

Classification

machine, unvalidated

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

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2020
Admission routes1
Has abstractyes

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