The SGT-600 industrial twin-shaft gas turbine modeling for mechanical drive applications at the steady state conditions

Rashidzadeh, Hiva; Hosseinalipour, Seyed Mostafa; Mohammadzadeh, Alireza

doi:10.1007/s12206-015-0946-8

Cited by 15 publications

(21 citation statements)

References 8 publications

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“…The majority of these studies used artificial neural networks [58][59][60] and fuzzy expert systems [61] to represent the shape and predict the operating points within the modeled curves of the compressor performance maps. Maps can also be determined by flow analysis schemes such as the stream line curvature (SLC) methodology [62] or high-fidelity computational fluid dynamics approaches (CFD) [63] if the geometry of the mechanical device is accessible.…”

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

347

158

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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.

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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

347

158

View full text Add to dashboard Cite

show abstract

“…This matching method has acceptable accuracy in predicting gas turbine performance at both design and off-design conditions and is used by numerous researchers. [15][16][17][18][19] Furthermore, this method is implemented for developing off-design performance modeling of three shaft gas turbines in Wang et al 20 and Gu et al 21 which show the competence of this method for the simulation of multi-shaft engines.…”

Section: Gas Turbine Performance Modelingmentioning

confidence: 99%

“…The combustion chamber pressure drop is computed using following correlations provided at Rashidzadeh et al 19 for the studied gas turbine…”

Section: Combustion Chambermentioning

confidence: 99%

Off-design performance improvement of twin-shaft gas turbine by variable geometry turbine and compressor besides fuel control

Sanaye

Hosseini

2019

Proceedings of the Institution of Mechanical Engineers, Part A:

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A novel procedure for finding the optimum values of design parameters of industrial twin-shaft gas turbines at various ambient temperatures is presented here. This paper focuses on being off design due to various ambient temperatures. The gas turbine modeling is performed by applying compressor and turbine characteristic maps and using thermodynamic matching method. The gas turbine power output is selected as an objective function in optimization procedure with genetic algorithm. Design parameters are compressor inlet guide vane angle, turbine exit temperature, and power turbine inlet nozzle guide vane angle. The novel constrains in optimization are compressor surge margin and turbine blade life cycle. A trained neural network is used for life cycle estimation of high pressure (gas generator) turbine blades. Results for optimum values for nozzle guide vane/inlet guide vane (23°/27°–27°/6°) in ambient temperature range of 25–45 ℃ provided higher net power output (3–4.3%) and more secured compressor surge margin in comparison with that for gas turbines control by turbine exit temperature. Gas turbines thermal efficiency also increased from 0.09 to 0.34% (while the gas generator turbine first rotor blade creep life cycle was kept almost constant about 40,000 h). Meanwhile, the averaged values for turbine exit temperature/turbine inlet temperature changed from 831.2/1475 to 823/1471°K, respectively, which shows about 1% decrease in turbine exit temperature and 0.3% decrease in turbine inlet temperature.

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“…Next, the simulation conditions are set in the same experimental conditions as in Rashidzadeh et al, 26 and the turbine is modeled as a turbogenerator. To this end, the reference speed for the power turbine shaft is set as 7700 r/min.…”

Section: Off-design Conditionsmentioning

confidence: 99%

Modeling and simulation of a two-shaft gas turbine propulsion system containing a frictional plate–type clutch

Montazeri-Gh

Fashandi

2018

Proceedings of the Institution of Mechanical Engineers, Part M:

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A marine propulsion system is composed of several subsystems that operate in a variety of energy fields. The propulsion power of a ship can be provided from a two-shaft gas turbine. In this article, the modeling of a two-shaft gas turbine and its associated subsystems including gears, flexible couplings and clutch is considered. These components are connected in the form of a virtual marine propulsion system, which is based on the bond-graph approach. When a clutch is used in a propulsion system, discontinuities occur in the describing model, which leads to some challenging problems when performing computer simulations. The two main difficulties are the numerical stiffness and the variable model structure. In this research, the bond-graph method is adapted as the modeling framework in order to allow a constant system structure model that minimizes the stiffness problem. Next, simulation results of a two-shaft gas turbine are presented in the off-design condition and verified with experimental tests. These results demonstrate the acceptable accuracy of computer simulations. Also, the effects of clutch performance on the dynamics of the marine propulsion system are discussed.

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The SGT-600 industrial twin-shaft gas turbine modeling for mechanical drive applications at the steady state conditions

Cited by 15 publications

References 8 publications

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

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

Off-design performance improvement of twin-shaft gas turbine by variable geometry turbine and compressor besides fuel control

Modeling and simulation of a two-shaft gas turbine propulsion system containing a frictional plate–type clutch

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