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Record W2032175094 · doi:10.1115/imece2013-64102

Dynamic Performance Simulation of an Aeroderivative Gas Turbine Using the Matlab Simulink Environment

2013· article· en· W2032175094 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsConcordia University
FundersQatar National Research FundQatar Foundation
KeywordsPrime moverComputer scienceMATLABTurbineFault (geology)Automotive engineeringSimulationControl engineeringEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

In fossil fuel applications, such as air transportation and power generation systems, gas turbine is the prime mover which governs the aircraft’s propulsive and the plant’s thermal efficiency, respectively. Therefore, an accurate engine performance simulation has a significant impact on the operation and maintenance of gas turbines as far as reliability and availability considerations are concerned. Current trends in achieving stable engine operation, reliable fault diagnosis and prognosis requirements do motivate the development and implementation of real-time dynamic simulators for gas turbines that are sufficiently complex, highly nonlinear, have high fidelity and include fast response modules. This paper presents a gas turbine performance model for predicting the transient dynamic behavior of an aeroderivative engine that is suitable for both mechanical drive and power generation applications. The engine model has been developed in the Matlab/Simulink environment and combines both the inter-component volume and the constant mass flow methods. Dynamic equations of the mass momentum and the energy balance are incorporated into the steady state thermodynamic equations. This allows one to represent the engine model by a set of first order differential and algebraic equations. The developed Simulink model in an object oriented environment, can be easily adapted to any kind of gas turbine configuration. The model consists of a number of subsystems for representing the gas turbine’s components and the thermodynamic relationships among them. The components are represented by a set of suitable performance maps that are available from the open literature. The engine model has been validated with an established gas turbine performance simulation software. Time responses of the main variables that describe the gas turbine dynamic behavior are also included. The proposed gas turbine model with its dynamic simulation characteristics is a useful tool for development of real-time model-based diagnostics and prognostics technologies.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.069
Threshold uncertainty score0.999

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 communication0.0000.001
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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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

Quick stats

Citations44
Published2013
Admission routes1
Has abstractyes

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