Components Map Generation of Gas Turbine Engine Using Genetic Algorithms and Engine Performance Deck Data

2006 ◽  
Vol 129 (2) ◽  
pp. 312-317 ◽  
Author(s):  
Changduk Kong ◽  
Jayoung Ki
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Gas Turbine ◽  
Test Data ◽  
Engine Performance ◽  
Scaling Method ◽  
Turbine Engine ◽  
Scaling Methods ◽  
Map Generation ◽  
Component Map

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be used. Because the components map is an engine manufacturer’s propriety obtained from many experimental tests with high cost, they are not provided to the customer generally. Some scaling methods for gas turbine component maps using experimental data or data partially given by engine manufacturers had been proposed in a previous study. Among them the map generation method using experimental data and genetic algorithms had showed the possibility of composing the component maps from some random test data. However not only does this method need more experimental data to obtain more realistic component maps but it also requires some more calculation time to treat the additional random test data by the component map generation program. Moreover some unnecessary test data may introduced to generate inaccuracy in component maps. The map generation method called the system identification method using partially given data from the engine manufacturer (Kong and Ki, 2003, ASME J. Eng. Gas Turbines Power, 125, 958–979) can improve the traditional scaling methods by multiplying the scaling factors at design point to off-design point data of the original performance maps, but some reference map data at off-design points should be needed. In this study a component map generation method, which may identify the component map conversely from some calculation results of a performance deck provided by the engine manufacturer using the genetic algorithms, was newly proposed to overcome the previous difficulties. As a demonstration example for this study, the PW206C turbo shaft engine for the tilt rotor type smart unmanned aerial vehicle which has been developed by Korea Aerospace Research Institute was used. In order to verify the proposed method, steady-state performance analysis results using the newly generated component maps were compared with them performed by the Estimated Engine Performance Program deck provided by the engine manufacturer. The performance results using the identified maps were also compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method and the methods explained above.

Components Map Generation of Gas Turbine Engine Using Genetic Algorithms and Engine Performance Deck Data

2006 ◽  
Author(s):  
Changduk Kong ◽  
Jayoung Ki ◽  
Changho Lee
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Gas Turbine ◽  
Test Data ◽  
Engine Performance ◽  
Scaling Method ◽  
Turbine Engine ◽  
Scaling Methods ◽  
Map Generation ◽  
Component Map

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. Because the components map is an engine manufacturer’s propriety obtained from many experimental tests with high cost, they are not provided to the customer generally. Some scaling methods for gas turbine component maps using experimental data or data partially given by engine manufacturers had been proposed in previous study. Among them the map generation method using experimental data and genetic algorithms (Kong et al., 2004) had showed a possibility composing the component maps from some random test data. However not only this method needs more experimental data to obtain the more realistic component maps but also it requires some more calculation time to treat the additional random test data by component map generation program. Moreover some unnecessary test data may introduce to generate inaccuracy in component maps. And the map generation method called as the system identification method using partially given data from engine manufacturer (Kong et al., 2003) can improve the traditional scaling methods by multiplying the scaling factors at design point to off-design point data of the original performance maps, but some reference map data at off-design points should be needed. In this study a component map generation method which may identify component map conversely from some calculation results of a performance deck provided by engine manufacturer using the Genetic Algorithms was newly proposed to overcome the previous difficulties. As a demonstration example for this study, the PW206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute) was used. In order to verify the proposed method, steady-state performance analysis results using the newly generated component maps were compared with them performed by EEPP (Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method and the methods explained at the above.

Component Map Generation of a Gas Turbine Using Genetic Algorithms

2004 ◽  
Vol 128 (1) ◽  
pp. 92-96 ◽  
Author(s):  
Changduk Kong ◽  
Seonghee Kho ◽  
Jayoung Ki
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Performance Analysis ◽  
Gas Turbine ◽  
Pressure Ratio ◽  
Engine Performance ◽  
Experimental Tests ◽  
Real Component ◽  
Map Generation ◽  
Component Map

In order to estimate the precise performance of the existing gas turbine engine, the component maps with more realistic performance characteristics are needed. Because the component maps are the engine manufacturer’s propriety obtained from very expensive experimental tests, they are not provided to the customers, generally. Therefore, because the engineers, who are working the performance simulation, have been mostly relying on component maps scaled from the similar existing maps, the accuracy of the performance analysis using the scaled maps may be relatively lower than that using the real component maps. Therefore, a component map generation method using experimental data and the genetic algorithms are newly proposed in this study. The engine test unit to be used for map generation has a free power turbine type small turboshaft engine. In order to generate the performance map for compressor of this engine, after obtaining engine performance data through experimental tests, and then the third order equations, which have relationships with the mass flow function, the pressure ratio, and the isentropic efficiency as to the engine rotational speed, were derived by using the genetic algorithms. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB (Kurzke, 2001). In order to verify the proposed scheme, the experimental data for verification were compared with performance analysis results using traditional scaled component maps and performance analysis results using a generated compressor map by genetic algorithms (GAs). In comparison, it was found that the analysis results using the generated map by GAs were well agreed with experimental data. Therefore, it was confirmed that the component maps can be generated from the experimental data by using GAs and it may be considered that the more realistic component maps can be obtained if more various conditions and accurate sensors would be used.

Component Map Generation of a Gas Turbine Using Genetic Algorithms

2004 ◽  
Author(s):  
Changduk Kong ◽  
Seonghee Kho ◽  
Jayoung Ki
Keyword(s):  
Genetic Algorithms ◽  
Performance Analysis ◽  
Gas Turbine ◽  
Pressure Ratio ◽  
Engine Performance ◽  
Experimental Tests ◽  
Real Component ◽  
Map Generation ◽  
Turboshaft Engine ◽  
Component Map

In order to estimate the precise performance of the existing gas turbine engine, the component maps with more realistic performance characteristics are needed. Because the components maps are engine manufacturer’s propriety obtained from very expensive experimental tests, they are not provided to the customers, generally. Therefore, because the engineers, who are working the performance simulation, have been mostly relying on component maps scaled from the similar existing maps, the accuracy of the performance analysis using the scaled maps may be relatively lower than that using the real component maps. Therefore, a component map generation method using experimental data and the genetic algorithms are newly proposed in this study. The engine test unit to be used for map generation has a free power turbine type small turboshaft engine. In order to generate the performance map for components of this engine, after obtaining engine performance data through many experimental tests, and then the third order equations, which have relationships the mass flow function, the pressure ratio and the isentropic efficiency as to the engine rotational speed were derived by using the genetic algorithm. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB (Kruzke, 2001). In order to verify predominance of the proposed scheme, the performance analysis results using the maps obtained by this study were compared with those using the compressor map provided by the engine manufacturer and the scaled turbine maps obtained from the GASTURB, as well as experimental results. In comparison, it was found that the component maps can be generated from the experimental test data by using the genetic algorithms, and it was confirmed that the analysis results using the generated maps were very similar to those using the scaled maps from the GASTURB.

A New Scaling Method for Component Maps of Gas Turbine Using System Identification

2002 ◽  
Author(s):  
Changduk Kong ◽  
Jayoung Ki ◽  
Myoungcheol Kang
Keyword(s):  
Gas Turbine ◽  
Engine Performance ◽  
Operating Conditions ◽  
Scaling Method ◽  
Design Point ◽  
The Real ◽  
Simulated Performance ◽  
Flight Envelope ◽  
Scaling Methods ◽  
Performance Error

A scaling method for characteristics of gas turbine components using experimental data or partially given data from engine manufacturers was newly proposed. In case of currently used traditional scaling methods, the predicted performance around the on-design point may be well agreed with the real engine performance, but the simulated performance at off-design points far away from the on-design point may not be well agreed with the real engine performance generally. It would be caused that component scaling factors, which were obtained at on-design point, is also used at all other operating points and component maps are derived from different known engine components. Therefore to minimize the analyzed performance error in the this study, firstly component maps are constructed by identifying performances given by engine manufacturers at some operating conditions, then the simulated performance using the identified maps is compared with performances using currently used scaling methods. In comparison, the analyzed performance using the currently used traditional scaling method was well agreed with the real engine performance at the on-design point but had maximum 12% error at off design points within the flight envelope of a calculation example turboprop engine. However the performance result using the newly proposed scaling method had maximum 6% reasonable error even at all flight envelope.

scholarly journals Fully Loaded Factory Test of the CW251B12 Gas Turbine Engine

1990 ◽  
Author(s):  
Ihor S. Diakunchak
Keyword(s):  
Gas Turbine ◽  
Test Data ◽  
Performance Test ◽  
Engine Performance ◽  
Test Facility ◽  
Test Results ◽  
Turbine Engine ◽  
Engine Model ◽  
Factory Test ◽  
Industrial Gas Turbine

The fully loaded factory test of the CW251B12 45 MW class industrial gas turbine is described in this paper. This gas turbine is the latest uprating of the W251 series of engines. The main objectives of the factory test were the verification of the performance and the mechanical integrity of the new engine model. A brief description of the main features of the engine, the application of the first unit, the test facility, and the engine instrumentation used in the test is included. Details of the engine performance test results, telemetry test data results, and the hot end component metal temperature measurements are provided.

Fully Loaded Factory Test of the CW251B12 Gas Turbine Engine

1991 ◽  
Vol 113 (4) ◽  
pp. 482-487 ◽  
Author(s):  
I. S. Diakunchak
Keyword(s):  
Gas Turbine ◽  
Test Data ◽  
Performance Test ◽  
Engine Performance ◽  
Test Facility ◽  
Test Results ◽  
Turbine Engine ◽  
Engine Model ◽  
Factory Test ◽  
Industrial Gas Turbine

The fully loaded factory test of the CW251B12 45 MW class industrial gas turbine is described in this paper. This gas turbine is the latest uprating of the W251 series of engines. The main objectives of the factory test were the verification of the performance and the mechanical integrity of the new engine model. A brief description of the main features of the engine, the application of the first unit, the test facility, and the engine instrumentation used in the test is included. Details of the engine performance test results, telemetry test data results, and the hot end component metal temperature measurements are provided.

A New Scaling Method for Component Maps of Gas Turbine Using System Identification

2003 ◽  
Vol 125 (4) ◽  
pp. 979-985 ◽  
Author(s):  
C. Kong ◽  
J. Ki ◽  
M. Kang
Keyword(s):  
Gas Turbine ◽  
Engine Performance ◽  
Operating Conditions ◽  
Scaling Method ◽  
Design Point ◽  
The Real ◽  
Simulated Performance ◽  
Flight Envelope ◽  
Scaling Methods ◽  
Performance Error

A scaling method for characteristics of gas turbine components using experimental data or partially given data from engine manufacturers was newly proposed. In case of currently used traditional scaling methods, the predicted performance around the on-design point may be well agreed with the real engine performance, but the simulated performance at off-design points far away from the on-design point may not be well agreed with the real engine performance generally. It would be caused that component scaling factors, which were obtained at on-design point, is also used at all other operating points and components’ maps are derived from different known engine components. Therefore to minimize the analyzed performance error in the this study, first components’ maps are constructed by identifying performances given by engine manufacturers at some operating conditions, then the simulated performance using the identified maps is compared with performances using currently used scaling methods. In comparison, the analyzed performance by the currently used traditional scaling method was well agreed with the real engine performance at on-design point but had maximum 22% error at off design points within the flight envelope of a study turboprop engine. However, the performance result by the newly proposed scaling method in this study had maximum 6% reasonable error even at all flight envelope.

scholarly journals Devising a method for calculating the turboshaft gas turbine engine performance involving a blade-by-blade description of the multi-stage compressor in a two-dimensional setting

2021 ◽  
Vol 4 (8(112)) ◽  
pp. 59-66
Author(s):  
Ludmila Boyko ◽  
Vadym Datsenko ◽  
Aleksandr Dyomin ◽  
Nataliya Pizhankova
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Gas Turbine ◽  
Engine Performance ◽  
Gas Turbine Engine ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Two Dimensional ◽  
Turbine Engine ◽  
Calculation Results

The design and adjustment of modern gas turbine engines significantly rely on the use of numerical research methods. This paper reports a method devised for calculating the thermogasdynamic parameters and characteristics of a turboshaft gas turbine engine. The special feature of a given method is a two-dimensional blade-by-blade description of the compressor in the engine system. Underlying the calculation method is a nonlinear mathematical model that makes it possible to describe the established processes occurring in individual nodes and in the engine in general. To build a mathematical model, a modular principle was chosen, involving the construction of a system of interrelated and coordinated models of nodes and their elements. The approach used in modeling a two-dimensional flow in the compressor makes it possible to estimate by calculation a significant number of parameters that characterize its operation. With the help of the reported method, it is possible to estimate the effect of changing the geometric parameters of the compressor height on the characteristics of the engine. To take into consideration the influence of variable modes of air intake or overflow in various cross-sections along the compressor tract, to determine the effect of the input radial unevenness on the parameters of the compressor and engine in general. To verify the method described, the calculation of thermogasdynamic parameters and throttle characteristics of a single-stage turboshaft gas turbine engine with a 12-stage axial compressor was performed. Comparison of the calculation results with experimental data showed satisfactory convergence. Thus, the standard deviation of the calculation results from the experimental data is 0.45 % for the compressor characteristics, 0.4 % for power, and 0.15 % for specific fuel consumption. Development and improvement of methods for calculating the parameters and characteristics of gas turbine engines make it possible to improve the quality of design and competitiveness of locally-made aircraft engines.

Inverse Generation of Gas Turbine Component Performance Maps From Experimental Test Data

2010 ◽  
Author(s):  
Changduk Kong ◽  
Semyeong Lim ◽  
Seonghwan Oh ◽  
Jihyun Kim
Keyword(s):  
Real Time ◽  
Gas Turbine ◽  
Condition Monitoring ◽  
Test Data ◽  
Performance Test ◽  
Monitoring Program ◽  
Engine Performance ◽  
Gas Turbine Engine ◽  
Performance Data ◽  
Turbine Engine

The gas turbine engine performance is greatly relied on its component performance characteristics. Generally, acquisition of component maps is not easy for engine purchasers because it is an intellectual property of gas turbine engine supplier. In the previous work, the maps were inversely generated from engine performance deck data. However this method is limited to obtain the realistic maps from the calculated performance deck data. Present work proposes a novel method to generate more realistic component maps from experimental performance test data. In order to demonstrate the proposed method, firstly the NI data acquisition device with the proposed LabVIEW on-condition monitoring program monitors and collects real-time performance data such as temperature, pressure, thrust, and fuel flow etc. from a micro turbojet engine of the test setup which is specially manufactured for this study. Real-time data obtained from the test results are used for inverse generation of the component maps after processing by some numerical schemes. Realistic component maps can then be generated from those processed data using the proposed extended scaling method at each rotational speed. Verification can be made through comparison between performance analysis results using the performance simulation program including the generated compressor map and on-condition monitoring performance data.

A Novel Method for Component Map Identification of a Gas Turbine Using Intelligent Method and Engine Performance Deck Data

2007 ◽  
Author(s):  
Changduk Kong ◽  
Seonghee Kho ◽  
Jayoung Ki ◽  
Yongmin Jun
Keyword(s):  
Genetic Algorithms ◽  
System Identification ◽  
Rotational Speed ◽  
Pressure Ratio ◽  
Scaling Method ◽  
Characteristic Equations ◽  
System Identification Method ◽  
Identification Method ◽  
Map Generation ◽  
Component Map

In this study a component map generation method which can identify component characteristics conversely from limited performance deck data provided by engine supplier was newly proposed using a hybrid method with the genetic algorithms and the system identification method. Generally component performance characteristics of compressor and turbine can be expressed as the third order equation with the related function of the engine rotational speed versus the pressure ratio, the mass flow function and the isentropic efficiency. According to the newly proposed scheme, firstly the scaling is performed at each engine rotational speed with some limited performance data which are provided by engine manufacturer, and then the component characteristic equations are obtained using system identification method. Then the initially obtained component characteristics are modified by considering engine component behavior for various operational conditions such as flight Mach number, altitude and atmospheric temperature using genetic algorithms. In the modification, the component characteristics obtained by system identification are used as initial data to reduce the calculation time. And finally component maps are generated by integrating the component characteristic equations taken at each engine rotational speed. In order to verify the proposed method, steady-state performance analysis using the newly generated component maps were performed, and the analysis results were compared with the performance deck data and the analysis results using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method (1% errors) is more effective than the traditional scaling method (10% errors) in overall operational region.

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