Off-design performance prediction of gas turbines without the use of compressor or turbine characteristics

Suraweera, Janitha Kanishka

doi:10.22215/etd/2012-07392

Cited by 6 publications

(5 citation statements)

References 42 publications

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“…These kinds of models can then be used to optimise flight trajectories (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16) , to save fuel, time and money. According to Suraweera (17) , component level modelling (CLM) plays a fundamental role in engine modelling. It has largely been used to model engine outputs (17)(18)(19)(20)(21)(22)(23) , performance deterioration (24) and fault diagnosis (25) .…”

Section: Introductionmentioning

confidence: 99%

“…According to Suraweera (17) , component level modelling (CLM) plays a fundamental role in engine modelling. It has largely been used to model engine outputs (17)(18)(19)(20)(21)(22)(23) , performance deterioration (24) and fault diagnosis (25) . This CLM approach consists in modelling each engine component based on thermodynamical assumptions and equations (26) .…”

Section: Introductionmentioning

confidence: 99%

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Cessna Citation X simulation turbofan modelling: identification and identified model validation using simulated flight tests

Botez¹,

Bardela²,

Bournisien³

2019

Aeronaut. j.

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The aviation industry relies on accurate models. These models are used to predict an aircraft system’s outputs, and thus allow an understanding of the parameters involved, which could lead to system improvements. This study focuses on the engine modelling of an aircraft, and on its experimental validation using the Cessna Citation X Research Aircraft Simulator designed by CAE Inc., equipped with a level D Flight Dynamics toolbox. Level D is the highest rank attributed by the Federal Aviation Administration FAA certification authorities for flight dynamics. The proposed model aims to predict the thrust and the fuel consumption for various altitudes, Mach numbers and throttle lever angles (TLA). Different generic static models, which correspond to their steady state, from the literature, were used in this study; however, most of them were validated under restricted hypotheses. An optimisation algorithm was used in order to tune the static model parameters with the set of identification flight test data. Another set of data was then used in order to validate the identified model. Furthermore, a dynamic model corresponding to the transient operations was identified. TLA steps, impulses and ramp perturbations were performed in order to identify the system response, and to validate system dynamic model with other flight tests than the identification tests.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cessna Citation X simulation turbofan modelling: identification and identified model validation using simulated flight tests

Botez¹,

Bardela²,

Bournisien³

2019

Aeronaut. j.

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“…There are many papers devoted to an accurate offdesign performance calculation without maps utilization [7,8]. However, their utilization is timeconsuming.…”

Section: Introductionmentioning

confidence: 99%

Industrial Gas Turbine Engine Off-Design Performance Improvement Controlling Cooling Air Flow

Moroz

Burlaka

Barannik

2018

NTU "KhPI" Bulletin

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The modern gas turbine engine has been used in current power generation industry for almost half a century. They are designed to operate with the best efficiency during normal operating conditions and at specific operating points. However, due to power grid demands, different ambient temperatures, fuel types, relative humidity and driven equipment speed the gas turbine units have to work today on partial load too, which can affect the hot gas path condition and life expectancy. At these off-design conditions, gas turbine's efficiency and life deterioration rate might significantly deviate from the design specifications. In this paper, a digital twin concept for gas turbine unit off-design performance prediction (AxSTREAM® platform) is used. The description of created digital twin is presented. The validation of proposed gas turbine unit digital twin is carried out by comparison with literature source test data. The GTU performance estimation controlling cooling air at part load modes using digital twin was performed.

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“…These models are used to generate performance numerical dynamic models [2][3][4][5] which are used to optimize flight trajectories [5][6][7][8][9][10][11][12][13][14][15][16] for flight cost reduction. The most common approach for engine modeling is the Component Level Modeling (CLM) [17][18][19][20][21][22][23][24]. In this approach, each component of the turbofan is modelled in order to simulate the entire engine.…”

Section: Introductionmentioning

confidence: 99%

Cessna Citation X Engine Model Experimental Validation

Bardella¹,

Botez²,

Pageaud³

2017

Modelling, Identification and Control

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The aviation industry is motivated to develop and validate new aircraft models for the prediction of engine performance. These models are used in the preliminary aircraft design in order to predict its engines performance. The purpose of this study is to design an accurate model of the fan and compressor engine components. This model will then be integrated in a full engine model based on a component modeling approach. Several methods already exist to model compressing components. Among them, the stage-stacking method is used in this paper. This method can be used to predict the compressor performance but also its deterioration (ex: "fouling"). In both cases, the principle is the same. Each stage is separated, and the first stage outputs are used for the next stage as inputs until the last stage is reached, when the final outputs are acquired. A Cessna Citation X Level D Research Flight Simulator designed by CAE Inc. is used to sample the data needed to identify and validate the engine models elaborated for the whole flight envelope. Level D is the highest level of certification given by the FAA for the flight dynamics. Thus the simulator is used as real aircraft flight dynamics data. Different flight tests were performed to mesh the flight envelope for different flight conditions (Mach numbers from 0 to 0.92; altitude from 0 to 50000ft and Throttle Lever Angle,TLA, from "idle" to "max" in degrees). Nonetheless, the stage stacking method needs information which is not always available, such as the blade angle. A "grey box" approach was chosen. The unmeasurable parameters were identified in order to tune the model, and thus to reduce the global error between the model and the simulation data. A "black box" approach was also with an optimisation algorithm to approximate the outputs as polynomial functions of the inputs. In both cases the results were found to be accurate.

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Off-design performance prediction of gas turbines without the use of compressor or turbine characteristics

Cited by 6 publications

References 42 publications

Cessna Citation X simulation turbofan modelling: identification and identified model validation using simulated flight tests

Cessna Citation X simulation turbofan modelling: identification and identified model validation using simulated flight tests

Industrial Gas Turbine Engine Off-Design Performance Improvement Controlling Cooling Air Flow

Cessna Citation X Engine Model Experimental Validation

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