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Record W3119703935 · doi:10.1115/gt2020-15214

Cooling Improvement of Gas Turbine Rotary Blades

2020· article· en· W3119703935 on OpenAlexaff
Faezeh Rasimarzabadi, Ramin Kamalimoghadam, M. Najafi, Mohammad-Reza Mohammadi, Nasrin Sahranavard fard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsGas compressorMechanical engineeringMechanicsTurbineHeat transferComputational fluid dynamicsAir compressorAir coolingTorqueTurbine bladeAirflowCompressed airEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract A new method is presented to improve cooling of the turbine blades by using active extraction from the compressor outlet to supply more cooling air with more energy. The cool air is extracted from the end of compressor through a set of peripheral holes to the air transferring channels on the disc edge or torque tube using the tangential velocity vector of the rotating shaft which results in increasing the amount and energy of the cooling air. In fact a forward angle of inlet holes for the channels is used to help the pressurized air overcome the air centrifugal force and to accelerate the flow going into the torque tube. To investigate the effect of new idea, both the original and proposed models are analyzed using 3D CFD simulation on a selected physical domain of a gas turbine. The compressible rotating Navier-Stokes equations are used for numerical simulation of two geometries. The governing equations, mesh treatment, boundary conditions and numerical setup are described. The calculation results are compared to those of the original turbine shaft to show the heat transfer improvement by enhancing the cooling flow rate and fluid energy.

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 score0.068
Threshold uncertainty score0.212

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 head0.008
GPT teacher head0.183
Teacher spread0.176 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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