A Generic Approach for Gas Turbine Adaptive Modeling

Visser, W. P. J.; Kogenhop, O.; Oostveen, M.

doi:10.1115/gt2004-53721

Cited by 17 publications

(15 citation statements)

References 21 publications

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“…A gas turbine model is created by arranging ("stacking") different predefined components (like inlet, compressors, combustors, turbines and exhaust nozzles) in a configuration, corresponding to the specific engine to be simulated. A more extensive description of the GSP modelling tool can be obtained in literature (Visser et al, 2004). The GSP model used in the simulation of the GE90-85B engine is shown in Figure 5.…”

Section: Methodology and Results Of The Engine Simulationmentioning

confidence: 99%

Feasibility Analysis of Hydrogen as Additional Fuel in Aircraft Propulsion

Juste¹,

Benavides²

2008

International Journal of Green Energy

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When considering economic aspects, recent work has shown that 100% hydrogen fueled airplanes will not be feasible for at least several decades. This paper analyzes some of the technological topics involved in the use of hydrogen as additional fuel in conventional kerosene fueled aircrafts. The addition of limited quantities of hydrogen does not require modifying aircraft shape or volume, and therefore, since it has no impact on its aerodynamics, could represent a starting point and smooth transition to 100% hydrogen use situation. An estimate of both engine and aircraft performances has been carried out in order to evaluate the benefits of this technological option. The addition of small quantities of hydrogen to a kerosene fueled gas turbine decreases its specific fuel consumption, no matter what the engine thrust. This decrease in specific fuel consumption will change the performance characteristics such as range, payload, operating empty weight (OEW) and fuel weight for a similar maximum take-off weight (MTOW) of the aircraft.

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Section: Methodology and Results Of The Engine Simulationmentioning

confidence: 99%

Feasibility Analysis of Hydrogen as Additional Fuel in Aircraft Propulsion

Juste¹,

Benavides²

2008

International Journal of Green Energy

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“…2. Compressor fouling, turbine erosion and concurrent degradations are modelled in the Gas turbine Simulation Program (GSP) software [5]. The generated data are then compared to the data generated from our Simulink model to evaluate the validity and accuracy of the data which are used in this work.…”

Section: Remarkmentioning

confidence: 99%

“…Optimal neural networks are obtained by using different number of training data sets to predict 2, 5, 8 and 12 flights ahead turbine temperature in the presence of compressor fouling and turbine erosion. The Gas turbine Simulation Program (GSP) [5] is a component-based modelling environment which allows steadystate and transient simulation of any gas turbine configuration. It was developed by the National Aerospace Laboratory (NLR).…”

Section: Engine Degradation Prediction Problemmentioning

confidence: 99%

“…The interest in application and use of neural networks in health monitoring and prognosis is mainly due to their capability in modelling nonlinearities of dynamical systems. The aircraft gas turbine engine is a highly nonlinear dynamical system [1,2,[4][5][6][7][8][9], and therefore, in order to model time delays and memory associated with the dynamics of the system, a dynamic neural network should be required for learning its dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic neural networks for gas turbine engine degradation prediction, health monitoring and prognosis

Kiakojoori

Khorasani

2015

Neural Comput & Applic

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In this paper, the problem of health monitoring and prognosis of aircraft gas turbine engines is considered by using computationally intelligent methodologies. Two different dynamic neural networks, namely the nonlinear autoregressive with exogenous input neural networks and the Elman neural networks, are developed and designed for this purpose. The proposed dynamic neural networks are designed to capture the dynamics of two main degradations in the gas turbine engine, namely the compressor fouling and the turbine erosion. The health status and condition of the engine in terms of the turbine output temperature (TT) are then predicted subject to occurrence of these deteriorations. Various scenarios consisting of fouling and erosion separately as well as combined are considered. For each scenario, several neural networks are trained and their performance in predicting multiple flights ahead TTs is evaluated. Finally, the most suitable neural networks for achieving the best prediction are selected by using the normalized Bayesian information criterion model selection. Simulation results presented demonstrate and illustrate the effective performance of our proposed neural networkbased prediction and prognosis strategies.

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“…Consequently a number of software tools were developed for a quick low order performance analysis of the whole engine, e.g. [1][2][3][4]. Often these tools are written as one piece of software in a single team for all engine components.…”

Section: Introductionmentioning

confidence: 99%

Development and application of a pre-design tool for aero-engine combustors

Tietz

Behrendt

2011

CEAS Aeronaut J

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A software tool was developed to design aeroengine combustors on a preliminary level. Only a small set of input parameters is required to design conventional as well as lean combustors. During the design calculation the combustor contour, the geometry of the desired cooling concept and the air flow distribution within the combustor are optimized. Optimization targets are to minimize the cooling air consumption with respect to the material temperature limits and to reach homogeneous material temperatures as well as a stable combustion. In the case of a staged burner the burner air and fuel fractions are optimized regarding minimal NO x production (qualitative) for the design condition. Off-design calculations on the basis of designed combustors can be executed for engine conditions other than take-off to calculate the altered conditions within the combustor. This paper shows the design and off-design process of the combustor tool in detail. In a second part application examples are given. The presented results show the capabilities of the tool for the pre-design of lean combustors with respect to the trade-off between the reduction of NO x emissions and the reduction of the fuel consumption as well as the capabilities for identifying potential cooling issues.

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A Generic Approach for Gas Turbine Adaptive Modeling

Cited by 17 publications

References 21 publications

Feasibility Analysis of Hydrogen as Additional Fuel in Aircraft Propulsion

Feasibility Analysis of Hydrogen as Additional Fuel in Aircraft Propulsion

Dynamic neural networks for gas turbine engine degradation prediction, health monitoring and prognosis

Development and application of a pre-design tool for aero-engine combustors

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