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FUEL NOZZLE COKING ANALYSIS DUE TO SOAK-BACK IN A GAS TURBINE COMBUSTOR

2015· article· en· W1963772471 on OpenAlexaff
A.S. Bazin, Alain De Champlain, Bernard Paquet

Bibliographic record

VenueInternational Journal of Energetic Materials and Chemical Propulsion · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCombustorNozzleGas turbinesTurbineMaterials scienceWaste managementEnvironmental scienceEngineeringNuclear engineeringAerospace engineeringAutomotive engineeringCombustionMechanical engineeringChemistry

Abstract

fetched live from OpenAlex

Post-shutdown heat soak-back is a commonly known cause for engine deterioration. In gas turbine combustors the heat generated by hot parts as the rotating components of the engine (such as the compressor and the turbine) come to rest is transferred throughout the structure and eventually to the surrounding air cavities. As this surplus heat reaches fuel wetted surfaces, coking becomes susceptible to occur, leaving solid deposition leading to a potential harm to the fuel delivery systems and to frequent overhauls. Numerical and experimental studies will be made in order to get a better understanding of the heat soak-back phenomenon, its potential effect on coking build-up, and to eventually seek solutions to prevent it.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.258
Teacher spread0.244 · 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 designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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