Off-design performance of solar Centaur-40 gas turbine engine using Simulink

Gobran, M. H.

doi:10.1016/j.asej.2012.08.007

Cited by 17 publications

(6 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results showed that the digital-control system model can predict real gas turbine measurements. Gobran [32] reported a Simulink model to calculate the off-design running point for single shaft Centaur 40 power generation gas turbine. The effect of ambient conditions on temperature and pressure across the gas turbine at the design condition was discussed.…”

Section: Introductionmentioning

confidence: 99%

Gas Path Fault and Degradation Modelling in Twin-Shaft Gas Turbines

2018

View full text Add to dashboard Cite

In this study, an assessment of degradation and failure modes in the gas-path components of twin-shaft industrial gas turbines (IGTs) has been carried out through a model-based analysis. Measurements from twin-shaft IGTs operated in the field and denoting reduction in engine performance attributed to compressor fouling conditions, hot-end blade turbine damage, and failure in the variable stator guide vane (VSGV) mechanism of the compressor have been considered for the analysis. The measurements were compared with simulated data from a thermodynamic model constructed in a Simulink environment, which predicts the physical parameters (pressure and temperature) across the different stations of the IGT. The model predicts engine health parameters, e.g., component efficiencies and flow capacities, which are not available in the engine field data. The results show that it is possible to simulate the change in physical parameters across the IGT during degradation and failure in the components by varying component efficiencies and flow capacities during IGT simulation. The results also demonstrate that the model can predict the measured field data attributed to failure in the gas-path components of twin-shaft IGTs. The estimated health parameters during degradation or failure in the gas-path components can assist the development of health-index prognostic methods for operational engine performance prediction.

show abstract

Section: Introductionmentioning

confidence: 99%

Gas Path Fault and Degradation Modelling in Twin-Shaft Gas Turbines

2018

View full text Add to dashboard Cite

show abstract

“…In another effort, an interactive gas turbine simulation and modeling environment called "PROOSIS" [68] (PRopulsion Object Oriented SImulation Software) has been developed as part of the "VIVACE-ECP" (Value Improvement through a Virtual Aeronautical Collaborative Enterprise -European Cycle Programme) project to be used by European industries. Since the mid-1990s, SIMULINK and many other GUI (graphical user interface) programs have been developed using MATLAB [69][70][71].…”

Section: Includes Either a Constant Linear Or Quadratic Regression Mmentioning

confidence: 99%

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Tahan¹,

Tsoutsanis

Muhammad³

et al. 2017

Applied Energy

350

158

View full text Add to dashboard Cite

With the privatization and intense competition that characterize the volatile energy sector, the gas turbine industry currently faces new challenges of increasing operational flexibility, reducing operating costs, improving reliability and availability while mitigating the environmental impact. In this complex, changing sector, the gas turbine community could address a set of these challenges by further development of high fidelity, more accurate and computationally efficient engine health assessment, diagnostic and prognostic systems. Recent studies have shown that engine gas-path performance monitoring still remains the cornerstone for making informed decisions in operation and maintenance of gas turbines. This paper offers a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques. The inception of performance monitoring and its evolution over time, techniques used to establish a highquality dataset using engine model performance adaptation, and effects of computationally intelligent techniques on promoting the implementation of engine fault diagnosis are reviewed. Moreover, recent developments in prognostics techniques designed to enhance the maintenance decision-making scheme and main causes of gas turbine performance deterioration are discussed to facilitate the fault identification module. The article aims to organize, evaluate and identify patterns and trends in the literature as well as recognize research gaps and recommend new research areas in the field of gas turbine performance-based monitoring. The presented insightful concepts provide experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring.

show abstract

“…This simulation tool offers the possibility to represent governing thermodynamic equations of the IGT in the Simulink environment. Several studies have reported gas turbine models developed in the Simulink environment [11][12][13][14][15][16][17][18]. In a previous study [19], a thermodynamic model to predict the performance of a twin-shaft IGT at different operating conditions was reported.…”

Section: Introductionmentioning

confidence: 99%

Inter-Stage Dynamic Performance of an Axial Compressor of a Twin-Shaft Industrial Gas Turbine

et al. 2020

View full text Add to dashboard Cite

In this study, the inter-stage dynamic performance of a multistage axial compressor is simulated through a semi-empirical model constructed in the Matlab Simulink environment. A semi-empirical 1-D compressor model developed in a previous study has been integrated with a 0-D twin-shaft gas turbine model developed in the Simulink environment. Inter-stage performance data generated through a high-fidelity design tool and based on throughflow analysis are considered for the development of the inter-stage modeling framework. Inter-stage performance data comprise pressure ratio at various speeds with nominal variable stator guide vane (VGV) positions and with hypothetical offsets to them with respect to the gas generator speed (GGS). Compressor discharge pressure, fuel flow demand, GGS and power turbine speed measured during the operation of a twin-shaft industrial gas turbine are considered for the dynamic model validation. The dynamic performance of the axial-compressor, simulated by the developed modeling framework, is represented on the overall compressor map and individual stage characteristic maps. The effect of extracting air through the bleed port in the engine center-casing on transient performance represented on overall compressor map and stage performance maps is also presented. In addition, the dynamic performance of the axial-compressor with an offset in VGV position is represented on the overall compressor map and individual stage characteristic maps. The study couples the fundamental principles of axial compressors and a semi-empirical modeling architecture in a complementary manner. The developed modeling framework can provide a deeper understanding of the factors that affect the dynamic performance of axial compressors.

show abstract

Off-design performance of solar Centaur-40 gas turbine engine using Simulink

Cited by 17 publications

References 6 publications

Gas Path Fault and Degradation Modelling in Twin-Shaft Gas Turbines

Gas Path Fault and Degradation Modelling in Twin-Shaft Gas Turbines

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Inter-Stage Dynamic Performance of an Axial Compressor of a Twin-Shaft Industrial Gas Turbine

Contact Info

Product

Resources

About