scholarly journals Non-linear model calibration for off-design performance prediction of gas turbines with experimental data

2017 ◽  
Vol 121 (1245) ◽  
pp. 1758-1777 ◽  
Author(s):  
Elias Tsoutsanis ◽  
Yi-Guang Li ◽  
Pericles Pilidis ◽  
Mike Newby
Keyword(s):  
Experimental Data ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Simulation Software ◽  
Design Performance ◽  
Turbine Performance ◽  
Map Generation ◽  
Compressor Map ◽  
Performance Adaptation ◽  
Improved Accuracy

ABSTRACTOne of the key challenges of the gas turbine community is to empower the condition based maintenance with simulation, diagnostic and prognostic tools which improve the reliability and availability of the engines. Within this context, the inverse adaptive modelling methods have generated much attention for their capability to tune engine models for matching experimental test data and/or simulation data. In this study, an integrated performance adaptation system for estimating the steady-state off-design performance of gas turbines is presented. In the system, a novel method for compressor map generation and a genetic algorithm-based method for engine off-design performance adaptation are introduced. The methods are integrated into PYTHIA gas turbine simulation software, developed at Cranfield University and tested with experimental data of an aero derivative gas turbine. The results demonstrate the promising capabilities of the proposed system for accurate prediction of the gas turbine performance. This is achieved by matching simultaneously a set of multiple off-design operating points. It is proven that the proposed methods and the system have the capability to progressively update and refine gas turbine performance models with improved accuracy, which is crucial for model-based gas path diagnostics and prognostics.

Part-Load Performance of Gas Turbines: Part II — Multi-Point Adaptation With Compressor Map Generation and GA Optimization

2012 ◽  
Author(s):  
E. Tsoutsanis ◽  
Y. G. Li ◽  
P. Pilidis ◽  
M. Newby
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Combined Cycle ◽  
Performance Model ◽  
Part Load ◽  
Design Performance ◽  
Turbine Performance ◽  
Map Generation ◽  
Compressor Map ◽  
Performance Adaptation

Accurate gas turbine performance simulation is a vital aid to the operational and maintenance strategy of thermal plants having gas turbines as their prime mover. Prediction of the part load performance of a gas turbine depends on the quality of the engine’s component maps. Taking into consideration that compressor maps are proprietary information of the manufacturers, several methods have been developed to encounter the above limitation by scaling and adapting component maps. This part of the paper presents a new off-design performance adaptation approach with the use of a novel compressor map generation method and Genetic Algorithms (GA) optimization. A set of coefficients controlling a generic compressor performance map analytically is used in the optimization process for the adaptation of the gas turbine performance model to match available engine test data. The developed method has been tested with off-design performance simulations and applied to a GE LM2500+ aeroderivative gas turbine operating in Manx Electricity Authority’s combined cycle power plant in the Isle of Man. It has been also compared with an earlier off-design performance adaptation approach, and shown some advantages in the performance adaptation.

Part-Load Performance of Gas Turbines: Part I — A Novel Compressor Map Generation Approach Suitable for Adaptive Simulation

2012 ◽  
Author(s):  
E. Tsoutsanis ◽  
Y. G. Li ◽  
P. Pilidis ◽  
M. Newby
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Primary Objective ◽  
Operating Conditions ◽  
Small Range ◽  
Part Load ◽  
Turbine Performance ◽  
Wide Range ◽  
Map Generation ◽  
Compressor Map

Part-load performance prediction of gas turbines is strongly dependent on detailed understanding of engine component behavior and mainly that of compressors. The accuracy of gas turbine engine models relies on the compressor performance maps, which are obtained in costly rig tests and remain manufacturer’s proprietary information. The gas turbine research community has addressed this limitation by scaling default generic compressor maps in order to match the targeted off-design measurements. This approach is efficient in small range of operating conditions but becomes less accurate for wide range of operating conditions. In this part of the paper a novel method of compressor map generation which has a primary objective to improve the accuracy of engine models performance at part load conditions is presented. This is to generate a generic form of equations to represent the lines of constant speed and constant efficiency of the compressor map for a generic compressor. The parameters that control the shape of the compressor map have been expressed in their simplest form in order to aid the adaptation process. The proposed compressor map generation method has the capacity to refine current gas turbine performance adaptation techniques, and it has been integrated into Cranfield’s PYTHIA gas turbine performance simulation and diagnostics software tool.

An Efficient Component Map Generation Method for Prediction of Gas Turbine Performance

2014 ◽  
Author(s):  
Elias Tsoutsanis ◽  
Nader Meskin ◽  
Mohieddine Benammar ◽  
Khashayar Khorasani
Keyword(s):  
Gas Turbine ◽  
Performance Prediction ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Small Range ◽  
Engine Model ◽  
Turbine Performance ◽  
Map Generation ◽  
Compressor Map ◽  
Component Map

Improving efficiency, reliability and availability of gas turbines have become more than ever one of the main areas of interest in gas turbine research. This is mainly due to the stringent environmental regulations that have to be met in such a mature technology sector; and consequently new research challenges have been identified. One of these involves the establishment of high fidelity, accurate, and computationally efficient engine performance simulation, diagnosis and prognosis technology. Performance prediction of gas turbines is strongly dependent on detailed understanding of the engine component behaviour. Compressors are of special interest because they can generate all sorts of operability problems like surge, stall and flutter; and their operating line is determined by the turbine characteristic. Compressor performance maps, which are obtained in costly rig tests and remain manufacturers proprietary information, impose a stringent limitation that has been commonly resolved by scaling default generic maps in order to match the targeted off-design or engine degraded measurements. This approach is efficient in small range of operating conditions but becomes less accurate for a wider range of operations. In this paper, a novel compressor map generation method, with the primary objective of improving the accuracy and fidelity of the engine model performance prediction is developed and presented. A new compressor map fitting and modelling method is introduced to simultaneously determine the best elliptical curves to a set of compressor map data. The coefficients that determine the shape of compressor maps’ curves have been analyzed and tuned through a multi-objective optimization algorithm in order to meet the targeted set of measurements. The proposed component map generation method is developed in the object oriented Matlab/Simulink environment and is integrated in a dynamic gas turbine engine model. The accuracy of this method is evaluated for off-design steady state and transient engine conditions. The proposed compressor map generation method has the capability to refine current gas turbine performance prediction approaches and to improve model-based diagnostic techniques.

Nonlinear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic Algorithm

2011 ◽  
Vol 133 (7) ◽  
Author(s):  
Y. G. Li ◽  
M. F. Abdul Ghafir ◽  
L. Wang ◽  
R. Singh ◽  
K. Huang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Scaling Factor ◽  
Performance Model ◽  
Operating Conditions ◽  
Performance Models ◽  
Design Performance ◽  
Turbine Performance ◽  
Thermodynamic Performance ◽  
Performance Adaptation

Accurate gas turbine performance models are crucial in many gas turbine performance analysis and gas path diagnostic applications. With current thermodynamic performance modeling techniques, the accuracy of gas turbine performance models at off-design conditions is determined by engine component characteristic maps obtained in rig tests and these maps may not be available to gas turbine users or may not be accurate for individual engines. In this paper, a nonlinear multiple point performance adaptation approach using a genetic algorithm is introduced with the aim to improve the performance prediction accuracy of gas turbine engines at different off-design conditions by calibrating the engine performance models against available test data. Such calibration is carried out with introduced nonlinear map scaling factor functions by “modifying” initially implemented component characteristic maps in the gas turbine thermodynamic performance models. A genetic algorithm is used to search for an optimal set of nonlinear scaling factor functions for the maps via an objective function that measures the difference between the simulated and actual gas path measurements. The developed off-design performance adaptation approach has been applied to a model single spool turbo-shaft aero gas turbine engine and has demonstrated a significant improvement in the performance model accuracy at off-design operating conditions.

Thermo-Fluid Modelling for Gas Turbines—Part I: Theoretical Foundation and Uncertainty Analysis

2009 ◽  
Author(s):  
Konstantinos G. Kyprianidis ◽  
Vishal Sethi ◽  
Stephen O. T. Ogaji ◽  
Pericles Pilidis ◽  
Riti Singh ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Simulation Software ◽  
System Level ◽  
Fluid Models ◽  
Performance Simulation ◽  
Turbine Performance ◽  
Aircraft System ◽  
The Impact ◽  
Made In

In this two-part publication, various aspects of thermo-fluid modelling for gas turbines are described and their impact on performance calculations and emissions predictions at aircraft system level is assessed. Accurate and reliable fluid modelling is essential for any gas turbine performance simulation software as it provides a robust foundation for building advanced multi-disciplinary modelling capabilities. Caloric properties for generic and semi-generic gas turbine performance simulation codes can be calculated at various levels of fidelity; selection of the fidelity level is dependent upon the objectives of the simulation and execution time constraints. However, rigorous fluid modelling may not necessarily improve performance simulation accuracy unless all modelling assumptions and sources of uncertainty are aligned to the same level. Certain modelling aspects such as the introduction of chemical kinetics, and dissociation effects, may reduce computational speed and this is of significant importance for radical space exploration and novel propulsion cycle assessment. This paper describes and compares fluid models, based on different levels of fidelity, which have been developed for an industry standard gas turbine performance simulation code and an environmental assessment tool for novel propulsion cycles. The latter comprises the following modules: engine performance, aircraft performance, emissions prediction, and environmental impact. The work presented aims to fill the current literature gap by: (i) investigating the common assumptions made in thermo-fluid modelling for gas turbines and their effect on caloric properties and (ii) assessing the impact of uncertainties on performance calculations and emissions predictions at aircraft system level. In Part I of this two-part publication, a comprehensive analysis of thermo-fluid modelling for gas turbines is presented and the fluid models developed are discussed in detail. Common technical models, used for calculating caloric properties, are compared while typical assumptions made in fluid modelling, and the uncertainties induced, are examined. Several analyses, which demonstrate the effects of composition, temperature and pressure on caloric properties of working mediums for gas turbines, are presented. The working mediums examined include dry air and combustion products for various fuels and H/C ratios. The errors induced by ignoring dissociation effects are also discussed.

Thermo-Fluid Modelling for Gas Turbines—Part II: Impact on Performance Calculations and Emissions Predictions at Aircraft System Level

2009 ◽  
Author(s):  
Konstantinos G. Kyprianidis ◽  
Vishal Sethi ◽  
Stephen O. T. Ogaji ◽  
Pericles Pilidis ◽  
Riti Singh ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Fluid Model ◽  
Simulation Software ◽  
System Level ◽  
Computational Time ◽  
Performance Simulation ◽  
Turbine Performance ◽  
Aircraft System ◽  
Different Levels

In this two-part publication, various aspects of thermo-fluid modelling for gas turbines are described and their impact on performance calculations and emissions predictions at aircraft system level is assessed. Accurate and reliable fluid modelling is essential for any gas turbine performance simulation software as it provides a robust foundation for building advanced multi-disciplinary modelling capabilities. Caloric properties for generic and semi-generic gas turbine performance simulation codes can be calculated at various levels of fidelity; selection of the fidelity level is dependent upon the objectives of the simulation and execution time constraints. However, rigorous fluid modelling may not necessarily improve performance simulation accuracy unless all modelling assumptions and sources of uncertainty are aligned to the same level. Certain modelling aspects such as the introduction of chemical kinetics, and dissociation effects, may reduce computational speed and this is of significant importance for radical space exploration and novel propulsion cycle assessment. This paper describes and compares fluid models, based on different levels of fidelity, which have been developed for an industry standard gas turbine performance simulation code and an environmental assessment tool for novel propulsion cycles. The latter comprises the following modules: engine performance, aircraft performance, emissions prediction, and environmental impact. The work presented aims to fill the current literature gap by: (i) investigating the common assumptions made in thermo-fluid modelling for gas turbines and their effect on caloric properties and (ii) assessing the impact of uncertainties on performance calculations and emissions predictions at aircraft system level. In Part II of this two-part publication, the uncertainty induced in performance calculations by common technical models, used for calculating caloric properties, is discussed at engine level. The errors induced by ignoring dissociation are examined at 3 different levels: i) component level, ii) engine level, and iii) aircraft system level. Essentially, an attempt is made to shed light on the trade-off between improving the accuracy of a fluid model and the accuracy of a multi-disciplinary simulation at aircraft system level, against computational time penalties. The results obtained demonstrate that accurate modelling of the working fluid is not always essential; the accuracy/uncertainty for an overall engine model will always be better than the mean accuracy/uncertainty of the individual component estimates as long as systematic errors are carefully examined and reduced to acceptable levels to ensure error propagation does not cause significant discrepancies. Computational time penalties induced by improving the accuracy of the fluid model as well as the validity of the ideal gas assumption for future turbofan engines and novel propulsion cycles are discussed.

Modeling and Analysis of Gas Turbine Performance Deterioration

1994 ◽  
Vol 116 (1) ◽  
pp. 46-52 ◽  
Author(s):  
A. N. Lakshminarasimha ◽  
M. P. Boyce ◽  
C. B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Data ◽  
Field Observations ◽  
Modeling And Analysis ◽  
Turbine Performance ◽  
Common Causes ◽  
Performance Deterioration ◽  
Simulation Results ◽  
Compressor Map

The effects of performance deterioration in both land and aircraft gas turbines are presented in this paper. Models for two of the most common causes of deterioration, viz., fouling and erosion, are presented. A stage-stacking procedure, which uses new installed engine field data for compressor map development, is described. The results of the effect of fouling in a powerplant gas turbine and that of erosion in a aircraft gas turbine are presented. Also described are methods of fault threshold quantification and fault matrix simulation. Results of the analyses were found to be consistent with field observations.

Uncertainty in gas turbine thermo-fluid modelling and its impact on performance calculations and emissions predictions at aircraft system level

2011 ◽  
Vol 226 (2) ◽  
pp. 163-181 ◽  
Author(s):  
K G Kyprianidis ◽  
V Sethi ◽  
S O T Ogaji ◽  
P Pilidis ◽  
R Singh ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Fluid Model ◽  
Simulation Software ◽  
System Level ◽  
Computational Time ◽  
Performance Simulation ◽  
Turbine Performance ◽  
Aircraft System ◽  
Working Media

In this article, various aspects of thermo-fluid modelling for gas turbines are described and the impact on performance calculations and emissions predictions at aircraft system level is assessed. Accurate and reliable fluid modelling is essential for any gas turbine performance simulation software as it provides a robust foundation for building advanced multi-disciplinary modelling capabilities. Caloric properties for generic and semi-generic gas turbine performance simulation codes can be calculated at various levels of fidelity; selection of the fidelity level is dependent upon the objectives of the simulation and execution time constraints. However, rigorous fluid modelling may not necessarily improve performance simulation accuracy unless all modelling assumptions and sources of uncertainty are aligned to the same level. A comprehensive analysis of thermo-fluid modelling for gas turbines is presented, and the fluid models developed are discussed in detail. Common technical models, used for calculating caloric properties, are compared while typical assumptions made in fluid modelling, and the uncertainties induced, are examined. Several analyses, which demonstrate the effects of composition, temperature, and pressure on caloric properties of working media for gas turbines, are presented. The working media examined include dry air and combustion products for various fuels and H/C ratios. The uncertainty induced in calculations by (a) using common technical models for evaluating fluid caloric properties and (b) ignoring dissociation effects is examined at three different levels: (i) component level, (ii) engine level, and (iii) aircraft system level. An attempt is made to shed light on the trade-off between improving the accuracy of a fluid model and the accuracy of a multi-disciplinary simulation at aircraft system level, against computational time penalties. The validity of the ideal gas assumption for future turbofan engines and novel propulsion cycles is discussed. The results obtained demonstrate that accurate modelling of the working fluid is essential, especially for assessing novel and/or aggressive cycles at aircraft system level. Where radical design space exploration is concerned, improving the accuracy of the fluid model will need to be carefully balanced with the computational time penalties involved.

Modelling and Analysis of Gas Turbine Performance Deterioration

1992 ◽  
Author(s):  
A. N. Lakshminarasimha ◽  
M. P. Boyce ◽  
C. B. Meher-Homji
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Field Data ◽  
Field Observations ◽  
Turbine Performance ◽  
Common Causes ◽  
Performance Deterioration ◽  
Simulation Results ◽  
Compressor Map

The effects of performance deterioration in both land and aircraft gas turbines are presented in this paper. Models for two of the most common causes of deterioration viz. fouling and deterioration are presented. A stage stacking procedure which uses new installed engine field data for compressor map development is described. The results of the effect of fouling in a powerplant gas turbine and that of erosion in a aircraft gas turbine are presented. Also described are methods of fault threshold quantification and fault matrix simulation. Results of the analyses were found to be consistent with field observations.

Non-Linear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic Algorithm

2010 ◽  
Author(s):  
Y. G. Li ◽  
M. F. Abdul Ghafir ◽  
L. Wang ◽  
R. Singh ◽  
K. Huang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Scaling Factor ◽  
Operating Conditions ◽  
Performance Models ◽  
Design Performance ◽  
Turbine Performance ◽  
Thermodynamic Performance ◽  
Non Linear ◽  
Performance Adaptation

Accurate gas turbine performance models are crucial in many gas turbine performance analysis and gas path diagnostic applications. With current thermodynamic performance modelling techniques, the accuracy of gas turbine performance models at off-design conditions is determined by engine component characteristic maps obtained in rig tests and these maps may not be available to gas turbine users or may not be accurate for individual engines. In this paper, a non-linear multiple point performance adaptation approach using a Genetic Algorithm is introduced with the aim to improve the performance prediction accuracy of gas turbine engines at different off-design conditions by calibrating the engine performance models against available test data. Such calibration is carried out with introduced non-linear map scaling factor functions by ‘modifying’ initially implemented component characteristic maps in the gas turbine thermodynamic performance models. A Genetic Algorithm is used to search for an optimal set of non-linear scaling factor functions for the maps via an objective function that measures the difference between the simulated and actual gas path measurements. The developed off-design performance adaptation approach has been applied to a model single spool turboshaft aero gas turbine engine and demonstrated a significant improvement in the performance model accuracy at off-design operating conditions.

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