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Record W1981155752 · doi:10.1108/09615531211188801

Effect of turbine inlet temperature on rotor blade tip leakage flow and heat transfer

2011· article· en· W1981155752 on OpenAlexaff
Sung In Kim, M. Hamidur Rahman, Ibrahim Hassan

Bibliographic record

VenueInternational Journal of Numerical Methods for Heat &amp Fluid Flow · 2011
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsCasingTurbineInletHeat transferMechanicsMaterials scienceStatorTurbine bladeLeakage (economics)Rotor (electric)AerodynamicsHeat fluxMechanical engineeringThermodynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Purpose One of the most critical gas turbine engine components, the rotor blade tip and casing, is exposed to high thermal load. It becomes a significant design challenge to protect the turbine materials from this severe situation. The purpose of this paper is to study numerically the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer. Design/methodology/approach In this paper, the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer has been studied numerically. Uniform low (LTIT: 444 K) and high (HTIT: 800 K) turbine inlet temperature, as well as non‐uniform inlet temperature have been considered. Findings The results showed the higher turbine inlet temperature yields the higher velocity and temperature variations in the leakage flow aerodynamics and heat transfer. For a given turbine geometry and on‐design operating conditions, the turbine power output can be increased by 1.33 times, when the turbine inlet temperature increases 1.80 times. Whereas the averaged heat fluxes on the casing and the blade tip become 2.71 and 2.82 times larger, respectively. Therefore, about 2.8 times larger cooling capacity is required to keep the same turbine material temperature. Furthermore, the maximum heat flux on the blade tip of high turbine inlet temperature case reaches up to 3.348 times larger than that of LTIT case. The effect of the interaction of stator and rotor on heat transfer features is also explored using unsteady simulations. The non‐uniform turbine inlet temperature enhances the heat flux fluctuation on the blade tip and casing. Originality/value The increase of turbine inlet temperature is usually proposed to achieve the higher turbine efficiency and the higher turbine power output. However, it has not been reported how much the heat transfer into the blade tip and casing increases with the increased turbine inlet temperature. This paper investigates the heat transfer distributions on the rotor blade tip and casing, associated with the tip leakage flow under high and low turbine inlet temperatures, as well as non‐uniform temperature distribution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.306
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2011
Admission routes1
Has abstractyes

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