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Record W7132234256

Gas turbine combustor modelling

2020· book· en· W7132234256 on OpenAlexvenueno aff
Lei-Yong Jiang

Bibliographic record

VenueNPARC · 2020
Typebook
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCombustorGas turbinesCombustionWork (physics)Combustion chamberTurbine
DOInot available

Abstract

fetched live from OpenAlex

The combustor is one of the four major engine components and is directly associated with engine performance such as the efficiency, emissions, safety, and economy. To simulate combustion systems properly, advanced knowledge or expertise in combustion theory and modeling is required. Simply running “off-the-shelf” software without a deep understanding of numerical methods and physical models can be dangerous. Considering the many-faceted criteria and enormous risks related to the design of combustion systems, this requirement is imperative. This book is based on the author’s work on the gas turbine combustor modeling over more than a decade. The contents should serve as good references for engineers and researchers in the development and maintenance of gas turbine engines, and useful learning materials to students who wish to work in this field. Most of the contents are also suitable to engineers and researchers working with other types of combustion systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.119
Threshold uncertainty score1.000

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)0.0010.001

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 head0.188
Teacher spread0.173 · 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.

Study designSimulation or modeling
Domainnot available
GenreOther

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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