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Record W2978013017 · doi:10.1017/aer.2019.115

Hot-streak effect on internally air-cooled nozzle guide vanes and shrouds

2019· article· en· W2978013017 on OpenAlexaff
Lei‐Yong Jiang, Yealim Han, Z. Zhang, Xijia Wu, Michaël Clément, Prakash Patnaik

Bibliographic record

VenueThe Aeronautical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsDepartment of National DefenceNational Research Council Canada
Fundersnot available
KeywordsCombustorNozzleStreakAerospace engineeringMechanicsThermalInletThermocoupleMeteorologyEnvironmental scienceMaterials scienceMechanical engineeringEngineeringPhysicsOpticsCombustionChemistryElectrical engineering

Abstract

fetched live from OpenAlex

ABSTRACT The effect of hot streaks from a gas turbine combustor on the thermodynamic load of internally air-cooled nozzle guide vanes (NGVs) and shrouds has been numerically investigated under flight conditions. The study follows two steps: one for the high-fidelity 60° combustor sector with simplified ten NGVs and three thermocouples attached; and the other for the NGV sectors where each sector consists of one high-fidelity NGV (probe NGV) and nine dummy NGVs. The first step identifies which NGV has the highest thermal load and provides the inlet flow boundary conditions for the second step. In the second step, the flow fields and thermal loads of the probe NGVs are resolved in detail. With the systematically validated physical models, the two-phase flowfield of the combustor-NGVs sector has been successfully simulated. The predicted mean and maximum temperature at the combustor sector exit are in excellent agreement with the experimental data, which provides a solid basis for the hot-streak effect investigation. The results indicate that the second NGV, looking upstream from left, has the highest thermal load. Its maximum surface temperature is 8.4% higher than that for the same NGV but with the mean inlet boundary conditions, and 14.1% higher than the ninth NGV. The finding is consistent with the field-observed NGV damage pattern. To extend the service life of these vulnerable NGVs, some protection methods should be considered.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.384

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 integrity0.0000.001
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 head0.003
GPT teacher head0.209
Teacher spread0.206 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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