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A full engine cycle analysis of a turbofan engine for optimum scheduling of variable guide vanes
Aerospace Science and Technology 47 (2015) 21–30
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A full engine cycle analysis of a turbofan engine for optimum scheduling of variable guide vanes Sangjo Kim a , Donghyun Kim a , Changmin Son b,∗ , Kuisoon Kim a , Myungho Kim c , Seongki Min c a b c
Department of Aerospace Engineering, Pusan National University, Busan 609-735, Republic of Korea School of Mechanical Engineering, Pusan National University, Busan 609-735, Republic of Korea 4-Advanced Propulsion Technology Center, Agency for Defense Development, Daejeon, Republic of Korea
a r t i c l e
i n f o
Article history: Received 17 April 2015 Received in revised form 7 September 2015 Accepted 9 September 2015 Available online 16 September 2015 Keywords: Variable guide vanes Axial compressor Turbofan engine Off-design performance 1D meanline analysis
a b s t r a c t This paper proposes a full engine cycle analysis to derive the schedule of variable guide vanes (VGVs) in a multi-stage axial compressor for improving the performance of a turbofan engine with required surge margin. Most researchers assumed the operating line of a compressor in process of scheduling of VGVs. However, it has been known that the performance of a compressor is influenced by the angle of VGVs. As a result, the performance variation of a compressor can affect an engine. Therefore, a full engine cycle analysis is conducted to consider the effect of VGVs on a turbofan engine. The VGVs are applied to the front stages of the high pressure compressor in the low-bypass ratio turbofan engine. The compressor of the front stages is transonic three-stage axial flow compressor. The commercial engine simulation program, NPSSTM is employed to analyze the on- and off-design performance of the turbofan engine. 1D meanline analysis is used for performance prediction of a multi-stage axial flow compressor with VGVs. The engine simulation program is coupled with the compressor performance prediction tool to consider the engine performance variation with application of the VGVs. The proposed scheduling algorithm of the inlet guide vane (IGV) and stator vanes (SV) is adjusting the vanes angle to have the minimum loss incidence angle at all rotor blades and to satisfy the required surge margin at off-design condition. The result shows that the proposed algorithm can obtain the scheduling of the IGV, 1st and 2nd SVs angle with stable operation and improved specific fuel consumption of the engine. © 2015 Elsevier Masson SAS. All rights reserved.
1. Introduction When the compressor rotating speed and pressure ratio are reduced, the axial velocity of the front stages of the compressor is decreasing more rapidly than the blade speed. This characteristics cause the high incidence angle of the air onto the blades. As a result, the operating point is pushed to the surge line which will bring about the stall and surge in the compressor. The compressor surge causes the blade vibration and can create rapid blade failure and the compressor flow breaks down [1]. There are several methods [2] to vary the engine cycle to avoid surge on the compressor. Typical approaches use the bleed values or variable exhaust nozzles. Especially, the variable inlet guide vane (IGV) and stator vane (SV) in an axial compressor are generally used to avoid the unstable region. By adapting the variable guide vane (VGV) at low speed, the large incidence angle of the airflow onto the front stage
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Corresponding author. Tel.: +82 (0)51 510 2321. E-mail address: [email protected] (C. Son).
http://dx.doi.org/10.1016/j.ast.2015.09.007 1270-9638/© 2015 Elsevier Masson SAS. All rights reserved.
rotor blades is reduced to have stable incidence angle. Moreover the VGVs can accomplish accurate matching of the stages, which is crucially important to achieve low losses and stable operation over on- and off-design conditions. Turbojet-to-ramjet transition is very important for the operation of the turbine-based combined cycle engine for the hypersonic flight propulsion system [3,4]. It can operate as turbo mode for low speed range (Mach number 0–3), then changes into ramjet model for higher speed range (Mach number 2.5–5) [5]. However, it has been known that additional difficulties arise in attempting to produce a turbojet which worked well throughout such a wide speed rage. With fixed geometry compressors, turbojets ceased to act as pressure amplifiers beyond Mach number 2.7. The addition of VGVs can raise the limit slightly beyond Mach number 3 [6]. There are numerous studies on investigating the performance and effectiveness of a compressor with VGVs. Mallett and Groesbeck [7] investigated the effects of a compressor interstage bleed and two-position inlet guide vanes to determine their effectiveness in alleviating the part speed stall margin of the J71-A2(X-29)
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Nomenclature 1D HPC HPT IGV LPC LPT m N P PR SF SM SV SFC
one-dimensional high pressure compressor high pressure turbine inlet guide vane low pressure compressor low pressure turbine mass flow rate (kg/s) rotating speed (rpm) pressure (kPa) pressure ratio scaling factor surge margin stator vane specific fuel consumption
turbojet engine. In their study, Mallett and Groesbeck [7] discovered that closing the inlet guide vanes increased the compressor efficiency and slightly raised both the steady-state operating line and stall line in the low-speed range. When the inlet guide vane angle was rotated as +20 degree at design speed, the corrected mass flow rate, total pressure ratio, and efficiency were decreased in 17.9%, 22.8%, and 7.2%, respectively, compared with fixed angle condition. Urasek et al. [8] conducted the performance test of a single stage transonic axial compressor with IGV and SV for stall free operation. Urasek et al. [8] reported that at part speed conditions, the stall points moved to lower flows and correspondingly lower pressure ratio when the guide vanes were closed from their design angles. Steinke [9] performed scheduling of VGVs angle to maximize the efficiency of a three-stage axial compressor on- and off-design condition, a peak efficiency of 0.86 was obtained at design speed near design flow. At part speeds peak efficiency were 0.87 to 0.89 with reset VGVs. Haglind [10] studied the possibility of reducing the formation of contrails by using VGVs for the fan of a high bypass turbofan engine. The author showed that the threshold formation temperature of contrails was reduced by about 1.5 K in the troposphere by employing VGVs for the fan of the engine, corresponding to an altitude of about 300 m. Gallar et al. [11,12] reported the integrated genetic algorithm optimizer within a meanline compressor performance prediction code to maximize the compressor efficiency while keeping an adequate user-defined value of the surge margin. The study assumed that the operating line on the compressor is considered unaffected by the angle of VGVs. The scheduling results for an eight-stage axial compressor in a modern high bypass ratio engine were compared with experimental data from the compressor rig. The result shows that when the schedule of VGVs was applied to the compressor, the efficiencies at highest and lowest total pressure ratio condition were increased in 0.77% and 6.48%, respectively. Abdollah et al. [13] developed an automated optimization tool for scheduling of VGVs in a multi-stage compressor. By using the tool, a ten-stage axial compressor was optimized to maximize its total pressure ratio in off-design conditions. The operating point of a speed line was calculated by surge margin equation with 20% margin. The authors reported that the operating mass flow rate and total pressure ratio were increased in 5.48% and 3.72%, respectively when the compressor used schedule of VGVs. Barbosa et al. [14] carried out the transient study on a small gas turbine performance for different variable IGV angles of a five-stage transonic axial compressor. The authors indicated that simulations needed to study the control strategy. Sun and Elder [15] presented a numerical methodology for optimizing VGVs angle setting in a seven-stage axial compressor to improve the compressor performance at a specific inlet mass
T VGV
η φ
temperature (K) variable guide vane efficiency angle of rotation – IGV and SV settings
Subscripts c eff op rel surge t unscaled
corrected efficiency operating point relative surge point total unscaled value at a performance map
flow rate on each speed line. The investigators reported that varying the stagger of the front stages provides a powerful technique to rematch the stages in order to obtain a high overall performance with a wider surge-free flow range. Most authors assumed the operating line of a compressor in process of scheduling of VGVs. However, it has been demonstrated that the steady-state operating line and stall line are changed by adjusting the angle of a guide vane [7]. The operating line on a compressor is calculated by performance a full engine cycle analysis. Therefore, the engine performance analysis with VGVs is needed to consider the realistic condition for scheduling of VGVs. Therefore, a full engine cycle analysis is conducted to consider the effect of VGVs on a turbofan engine. This study derives the schedule of VGVs of the three-stage axial compressor in the lowbypass ratio turbofan engine by using the full engine cycle analysis. 1D meanline analysis is used to predict the performance of the compressor with VGVs. 1D meanline analysis results are compared with performance test for verification and validation. The commercial engine simulation program, NPSSTM is employed for performance analysis at on and off-design condition. The performance map of the compressor with VGVs is applied to the engine simulation program to predict its impact. The operating line on the performance map of the compressor is calculated by conducting the off-design engine simulation. A scheduling algorithm of the VGVs is suggested to improve both the surge margin and engine SFC at off-design condition. The algorithm takes into account the operating line and the surge margin on the compressor. The engine performance and surge margin with scheduled VGVs are compared with the case of IGV angle only and without VGVs. 2. Engine model The engine, on which the full engine cycle analysis is tested and presented, is a low bypass ratio mixed flow turbofan engine for military flight application. The engine configuration and design parameters, such as engine SFC, bypass ratio, and specific thrust, are refer to the Honeywell/ITEC F124 engine [16]. A schematic picture of the turbofan engine is shown in Fig. 1. The compression system of the engine consists of a three-stage fan, a three-stage axial compressor and a single stage centrifugal compressor. The fan is divided in to two parts, namely inner fan and outer fan, because the fan pressure ratio and isentropic efficiency is change according to the radial direction [17,18]. For modeling purpose, the high pressure compressor (HPC) is split into two compressors, axial part and radial part of HPC. The air at the exit of the radial part of HPC is drawn to cool the high-pressure turbine (HPT) nozzle and rotor. And the air bleed from the exit of the axial part of HPC is
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Fig. 1. Schematic picture of the turbofan engine.
used to cool the low-pressure turbine (LPT). This work assumes that the axial part of HPC is the three-stage transonic axial compressor with IGV, which was presented in Kang et al. [19]. Table 1 shows the design parameters of the engine. The performance map of outer fan is scaled from that of inner fan to consider the differences in fans geometries. Because the core flow is about twice as big as bypass flow. The scale factors are derived from the on-design point analysis and applied to the off-design performance analysis. The equations for the calculation are as follows:
PRbypass = 1 + (PRcore − 1) ×
ηbypass ηbypass = ηcore × ηcore
PRbypass − 1
PRcore − 1
SFPR = SFeff =
Performance: sea level static, standard day, nominal engine, max power
Parameter
Value
Maximum thrust (kN) SFC (g/kN s) Bypass ratio Airflow (kg/s) Turbine inlet temperature (K) Fan pressure ratio Overall pressure ratio
20.6 22.10 0.49 31.1 1600 2.5 19.0
(1) design
(2) design
For the modeling of the performance of inner fan, it implemented the performance map of fan from Suzuki and Kuno [20] is used. The performance map of the axial part of HPC with VGVs is calculated by using 1D meanline analysis. The method and procedure are treated in more detail in the next section. The performance map of the mixed-flow compressor [21] is applied to the radial part of HPC. To treat the high and low pressure turbines in the off-design condition, the performance maps of the turbine are utilized from the database in NPSSTM [22]. The performance maps of those components are scaled upon pressure ratio, efficiency, and mass flow rate except for the axial part of HPC. The scale factors are calculated from the following equations [23]:
SFflow =
Table 1 Turbofan engine design parameters.
mc , design mc , unscaled PRdesign − 1
PRunscaled − 1
ηdesign ηunscaled
(3) (4) (5)
For validation purpose, the performance prediction results for F124 engine are compared with test data. Result is shown in Table 2 and it can be observed that the prediction results of the present engine model agree well test data. 3. Compressor performance analysis with VGV The overall performance parameters of the compressor are given in Table 3. The meridional view and blade row configuration of the compressor are presented in Fig. 2.
Table 2 Performance prediction validation. Parameter
NPSS (Present result)
F124 [16]
Diff. (%)
SFC (g/kN s) Specific thrust (kN/kg/s)
22.0990 0.6659
22.0939 0.6651
−0.02% −0.12%
Table 3 Three-stage compressor performance parameters [19]. Parameter
Value
Number of stages Total pressure ratio Isentropic efficiency Inlet mass flow (kg/s) Rotating speed (RPM)
3 2.50 0.84 9.90 20,000
3.1. 1D meanline analysis Assuming one-dimensional compressible flow, Euler equation employing loss models is applied to calculate rotor efficiency and stator losses at on- and off-design conditions. The selected correlations for 1D meanline analysis are listed in Table 4. The choice of the empirical correlation is based on Kim et al. [25], where the influence of the correlation was investigated in detail. The total pressure ratio and stage efficiency are then calculated iteratively based on the boundary condition and selected correlations. 3.2. Comparison of the performance prediction results Fig. 3 shows the comparison of performance test [19] and predicted results. The 1D meanline results show the underestimated pressure ratio at all speed lines. However, the trends of the pressure ratio and isentropic efficiency of the 1D meanline are agreed well with performance test. In general, it is difficult to predict
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Fig. 2. Meridional view and blade row configuration of the three-stage compressor.
Table 4 Selected correlations for 1D meanline analysis. Correlation
Reference
Incidence angle
Minimum loss Stall Choking
Aungier [24] Aungier [24] Kim et al. [25]
Deviation angle
Reference Axial velocity ratio Incidence angle
Lieblein [26] Hu et al. [27] Lieblein [26]
Losses
Minimum profile loss Off-design profile loss, stall region Off-design profile loss choking region, Shock loss The other losses
Wright and Miller [28] Aungier [24]
Flow blockage
Kim et al. [25] Jansen and Moffatt [29] Wright and Miller [28] Wright and Miller [28]
exactly the performance of a multi-stage axial compressor by using the numerical method [30–33,37]. Kang et al. [19] reported that the difference of the mass flow rate between the performance test and the numerical result of the three-stage axial compressor is 3%. Kang et al. [19] explained the reason is the blade untwist phenomenon caused by force acting on the compressor rotor tip where its thickness is very thin. Therefore present study focuses on the trend of the compressor performance rather than the exact numerical value. Fig. 3. Comparison of performance test and predicted results.
4. Off-design engine performance Off-design performance analysis is conducted under sea level static condition to investigate the engine performance and the operating characteristics. The engine performance is analyzed for the engine thrust range 3.56–20.68 kN. The engine SFC and the surge margin of the compressor with VGVs are compared at the same engine thrust conditions. The operating line on the performance map of the fan for the engine without VGVs is shown in Fig. 4. In the performance map, the relative corrected rotating speed is given by
N c ,rel =
√ ( N / T t )op √ ( N / T t )design
(6)
The results show that the pressure ratio and corrected mass flow decreases with engine thrust. In general, the definition of surge margin is the difference between the operating point of the compressor and the surge line. The surge margin is calculated by using Eq. (7) [34].
SM = 1. −
PRop × mc , surge PRsurge × mc ,op
(7)
Fig. 4. The operating line on the performance map of the fan for the engine without VGV.
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Fig. 5. The operating line on the performance map of the axial part of HPC for the engine without VGV.
Fig. 7. The operating line on the performance map of the HPT for the engine without VGV.
Fig. 6. The operating line on the performance map of the radial part of HPC for the engine without VGV.
Fig. 8. The operating line on the performance map of the LPT for the engine without VGV.
The surge margin of the fan at the 50% rotational speed is about 18%. The decrease of the surge margin with engine thrust is observed. Fig. 5 presents the operating line on the performance map of the axial part of HPC for the engine without VGV. The corrected mass flow rate of the axial part of HPC decreases with the engine thrust. The compressor is approaching to surge region when it is operating at below 87% of the design speed. The efficiency of the compressor decreases when it is operating at surge region. This phenomenon is also reported by Robert [2]. The front stages of the compressor may go into stall since the mass flow rate generally falls off more rapidly than the rotating speed [35]. The off-design behavior of the radial part of HPC for the engine without VGV is plotted in Fig. 6. The result indicates that the surge margin is decreased at off-design condition. The variation of the corrected mass flow rate according to the engine thrust is smaller than that of the other compressors. In general, a decrease of rotating speed will lead to a decrease in flow density and an increase of axial velocity, and hence choking will start at a rear stage [35]. Fig. 7 and Fig. 8 show the operating line on the performance map of the high pressure turbine (HPT) and low pressure turbine (LPT) for the engine without VGV, respectively. Little change of the operating point in the HPT is observed. The pressure ratio and mass flow parameter of the LPT decrease with the engine thrust.
The rotational speed is changed from 100% to 65% of design speed at the off-design condition. Fig. 9 reveals the SFC versus Thrust for the engine without VGVs. The engine shows minimum value of SFC when the thrust is about 8 kN. The typical “fish-hook” behavior is shown with the throttling down of the engine [36]. The surge margin of the axial part of HPC versus Thrust for the engine without VGVs is presented in Fig. 10. At the on-design condition, the surge margin is about 10%. The surge margin decreases with the engine thrust. Especially, the surge margin shows negative value when the engine thrust is below 5 kN. 5. Algorithm for scheduling of the VGVs 5.1. Scheduling of IGV angle only Fig. 11 shows the algorithm for scheduling of IGV angle to satisfy the required surge margin. The target surge margin is set at 10%. Firstly, on-design cycle analysis is performed. Then, for offdesign cycle analysis, cycle analysis program requires the complete performance maps, such as compressors and turbines. The performance maps of the axial part of HPC with variable IGV angle is generated by using 1D meanline analysis and enter in table format. From the off-design cycle analysis, the surge margin is calculated by employing Eq. (7). If the surge margin is smaller than the target
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Fig. 9. SFC versus Thrust for the engine without VGV.
Fig. 12. IGV angle versus Thrust for the engine with the schedules of IGV only.
Fig. 10. Surge margin of the axial part of HPC versus Thrust for the without VGV.
Fig. 13. Efficiency of the axial part of HPC versus Thrust with the schedules of IGV only.
that there is no IGV angle to satisfy the requirement when the engine thrust is below 8.8 kN. The efficiency of the axial part of HPC versus Thrust with the schedules of IGV only is depicted in Fig. 13. The result shows that the efficiency of the compressor is affect by different scheduling methods. The reason is that the working line on the performance map of the compressor is changed by adjusting the IGV angle. 5.2. Scheduling of IGV, 1st and 2nd SVs angle
Fig. 11. Algorithm for scheduling of IGV angle.
value (10%), the IGV angle is adjusted to satisfy the requirement. In the algorithm, maximum IGV rotating angle is set at 40◦ . For comparison, scheduling of IGV angle is also performed by using compressor performance analysis only with fixed working line on the performance map to satisfy the target surge margin. The resultant schedules of IGV angle are plotted in Fig. 12. The IGV angle of the schedule is smaller using full engine cycle analysis than using compressor performance analysis only. The result of the schedule using compressor performance analysis only shows
The algorithm for scheduling of IGV, 1st and 2nd SVs angle is presented in Fig. 14. In general, in a multi-stage axial compressor, the performance depends on the superposition of each stage performance. If all rotors have minimum loss incidence angle, the whole compressor efficiency will be improved. When the incidence angle is bigger than minimum loss position, it can be assumed that the compressor is operated in the stalling region. On the other hand, it is choking region if incidence angle is smaller than minimum loss position. Therefore, if a blade has minimum loss incidence angle, stable operation and improved efficiency of the compressor are expected. Lieblein [26] investigated the minimum loss incidence angle by performing the linear cascade test. The research showed that the minimum loss position of the blade is influenced by inlet flow condition, such as flow angle and inlet Mach number, and blade geometry. Therefore, the minimum loss incidence angle of each rotor is calculated at each iteration of the algorithm. The present compressor performance prediction program calculates the total pressure ratio and isentropic efficiency by using a boundary condition and geometry. The boundary conditions are the inlet flow condition and rotating speed. The boundary
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Fig. 15. IGV, 1st and 2nd SVs angle versus Thrust.
Fig. 16. The performance map of the axial part of HPC for the engine with and without the schedules of VGVs.
Fig. 14. Algorithm for scheduling of IGV, 1st and 2nd SV angle.
condition of the axial part of HPC is calculated by performing the off-design cycle analysis. For the analysis, the IGV, 1st and 2nd SVs angles are adjusted to have minimum loss incidence angle at each rotor. The compressor performance maps with the VGVs angles are then generated. The off-design cycle analysis is re-performed to obtain the operating points of the compressor. The process will continue until the target surge margin is satisfied. The resultant schedule of the IGV and 1st and 2nd SVs is depicted in Fig. 15. The IGV angle shows the minimum value when engine thrust is about 18 kN. At this operating point, the 1st and 2nd SVs angles are bigger than the IGV. When engine trust is about 3 kN, the results show that the IGV rotating angle is the biggest value and the 1st SV is the next big angle. The rotating angle of the IGV is smaller than that of the case with IGV angle only. Gallar et al. [11] and Abdollah et al. [13] conducted a scheduling of VGVs in a multi-stage axial compressor by using an optimization method. However, unlike some authors, this study proposed a scheduling algorithm which controls the angle of IGV and SVs to have the minimum loss incidence angle at the each rotor. The proposed scheduling algorithm has two advantages. First is that the algorithm has a logic to control the angle of variable guide vanes. It has been known that a minimum loss incidence angle at a blade is changed by varying inlet flow conditions. The inlet flow condition of a compressor can be obtained by using a full
engine simulation in every iteration. The control logic can apply high-fidelity simulation method as well as 1D meanline analysis. Second is that calculation time is lower for the proposed algorithm than for an optimization method. In a study by Gallar et al. [11], the iteration number is about 30,000 (the population size of the algorithm is 100 individuals that run over 300 generations) to find the optimum point by using genetic algorithm. However, in this study, the iteration number is just 5 to find the schedule of VGVs. The result indicates that the number of iterations can be reduced significantly when the proposed algorithm is applied to the scheduling procedure. 6. Results The off-design behavior of the axial part of HPC with and without the schedule of the VGVs is illustrated in Fig. 16. When the engine is operated at low thrust condition, the operating line of the axial part of HPC with the schedule passes the maximum efficiency region while that of the case without the schedule is operated around low efficiency region. The pressure ratio of the axial part of HPC with the schedule is low compared with the case without the schedule. The result shows that the operating line of the axial part of HPC is influence by the VGVs. Fig. 17 is presented the off-design behavior of the radial part of HPC. When the schedule is applied to the engine, the corrected mass flow rate and pressure ratio are changed because the flow conditions at the exit of the axial part of HPC are altered. As a result, the operating line is located to lower efficiency region. It is observed that the operating line of the radial part of HPC is affected by the VGVs in the axial part.
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Fig. 17. The performance map of the radial part of HPC for the engine with and without the schedules of VGVs.
Fig. 19. Surge margin of the axial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
Fig. 18. SFC versus thrust for the engine with and without the schedules of VGVs.
Fig. 20. Efficiency of fan versus Thrust for the engine with and without the schedules of VGVs.
By performing the full engine simulation, the engine performance variation with VGVs can be observed. The SFC versus Thrust for the thrust range 3.56–20.68 kN is shown in Fig. 18 for the engine with and without the schedule of VGVs, respectively. When the VGVs are applied to the engine, the engine SFC is lower than that of the engine without VGVs at low thrust. The engine SFC is slightly increased by the VGVs at relatively high thrust. The use of IGV, 1st and 2nd SVs reduces the engine SFC over the whole thrust range compared with the engine with IGV only. The comparison indicates a need of the proposed algorithm for scheduling of angles of VGVs to improve the engine performance compared with the engine with IGV angle only. The surge margin of the axial part of HPC versus Thrust is depicted in Fig. 19. The results show that the surge margins with VGVs are higher than that of the engine without VGVs. The engine with schedule of VGVs meet the required surge margin over the whole thrust range. The efficiency of the fan versus Thrust is presented in Fig. 20. The efficiency of the fan shows the maximum value when the thrust is about 16 kN. After the peak point, the efficiency is decreased with engine thrust. The efficiency of the fan of the engine with the IGV, 1st and 2nd SVs is increased compared with the engine without VGVs at low thrust. When the engine operates at high thrust, the difference is small.
Fig. 21. Efficiency of the axial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
Fig. 21 presents the efficiency of the axial part of HPC versus Thrust. This figure clearly demonstrates that the efficiency of the axial part of HPC depends on the scheduling algorithm. In the engine with IGV only, between 9 kN and 20.68 kN thrust, the
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Fig. 22. Efficiency of the radial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
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Fig. 24. Efficiency of LPT versus Thrust for the engine with and without the schedules of VGVs.
proach which is consideration of cycle performance and the other researches. 7. Conclusion
Fig. 23. Efficiency of HPT versus Thrust for the engine with and without the schedules of VGVs.
efficiency is decreased compared with the engine without VGVs. When the engine thrust is below 9 kN, the IGV, 1st and 2nd SVs increase the efficiency while the others decrease the efficiency. Comparing these two engines with schedule, the improvement of the efficiency is larger for the use of IGV, 1st and 2nd SVs. The results indicate that the use of IGV, 1st and 2nd SVs promise the most efficient operation on the axial part of HPC. The efficiency of the radial part of HPC versus Thrust is plotted in Fig. 22. The results show that the efficiency using the VGVs is decreased compared with the engine without VGVs. Because the operating line in the radial part of HPC with VGVs is goes down to low efficiency region. The efficiency drop on the radial part of HPC is inevitable when employing the VGVs to satisfy required surge margin, but the efficiency gains at the axial part of HPC make the improvement of the engine SFC at low engine thrust. Fig. 23 and Fig. 24 show the efficiency of the HPT and LPT, respectively. The efficiency of the HPT is nearly constant with thrust. Little change of the efficiency according to the schedules is observed. The efficiency of the LPT decreases with engine thrust. Fig. 24 indicates that the use of VGVs slightly increases the efficiency of the LPT compared with the engine without VGVs at low engine thrust. Gallar et al. [11] and Abdollah et al. [13] assumed the operating line of a compressor in process of scheduling of VGVs. The present results show the evidence of the difference between present ap-
In this paper, authors employ a full engine cycle analysis to consider the effect of scheduling of VGVs and VSVs of a three-stage axial compressor on a low-bypass ratio turbofan engine. The proposed algorithm is controlling the angle of IGV and SVs to have the minimum loss incidence angle at the each rotor to improve the performance of the engine with stable operation at on and offdesign conditions. 1D meanline analysis is used to generate the performance map of the compressor with VGVs. The cycle analysis is conducted at on- and off-design conditions. The off-design cycle analysis is performed using the performance maps. The angles of the IGV and SVs of the axial part of HPC are scheduled using engine cycle simulation tool implementing the proposed algorithm. It is observed that the operating lines on the performance map are changed by using VGVs but for the HPT. From the results, it is clear that the engine performance analysis is essential in process of scheduling of the VGVs. The resultant schedule of VGVs shows that the engine with the schedule satisfies the required surge margin and improved SFC at highly off-design condition. In the engine with the schedule of IGV, 1st and 2nd SVs angles, the SFC is better than that of the engine with IGV angle only because of improved efficiency of the axial part of HPC in off-design condition. Conflict of interest statement None declared. Acknowledgements This research was supported by a grant from Agency for Defense Development (ADD-11-01-05-13), Republic of Korea. Also, this work was supported by “Human Resources Program in Energy Technology” of the Korea Institute of Energy Evaluation and Planing (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20144030200570). Special thanks to Korea Aerospace Research Institute (KARI) for sharing compressor geometry and performance information. References [1] Rolls-Royce, The Jet Engine, Rolls-Royce plc, England, 2005.
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[2] M.P. Robert, Plotting component maps in the Navy/NASA engine program (NNEP) – a method and its usage, NASA TM-101433, 1989. [3] W. Huang, L. Yan, J.G. Tan, Survey on the mode transition technique in combined cycle propulsion systems, Aerosp. Sci. Technol. 39 (2014) 685–691. [4] H. Miyagi, H. Kimura, K. Kishi, Combined cycle engine research in Japanese HYPR program, AIAA-1998-3278, 1998. [5] S. Takata, T. Nagashima, S. Teramoto, H. Kodama, Bypass flow pattern changes at turbo-ram transient operation of a combined cycle engine, in: Unsteady Aerodynamics, Aeroacoustics and Aeroelasticity of Turbomachines, 2006, pp. 345–356. [6] Griffon II and turbo-ramjets – technical director of Nord-Aviation delivers twelfth Louis Bleriot lecture, http://www.flightglobal.com/FlightPDFArchive/ 1959/1959%20-%200777.PDF. [7] W.E. Mallett, D.E. Groesbeck, Effects of compressor interstage bleed and adjustable inlet guide vanes on compressor stall characteristics of a highpressure-ratio turbojet engine at altitude, NACA RM E55G27, 1956. [8] D.C. Urasek, R.J. Steinke, W.S. Cunnan, Stalled and stall-free performance of axial-flow compressor stage with three inlet-guide-vane and stator-blade settings, NASA TN D-8457, 1977. [9] R.J. Steinke, Design of 9.271-pressure-ratio five-stage core compressor and overall performance for first three stages, NASA TP 2597, 1986. [10] F. Haglind, Potential of lowering the contrail formation of aircraft exhausts by engine re-design, Aerosp. Sci. Technol. 12 (2008) 490–497. [11] L. Gallar, M. Arias, V. Pachidis, P. Pilidis, Compressor variable geometry schedule optimisation using genetic algorithms, in: Proceedings of the ASME Turbo Expo 2009, GT2009-60049. [12] L. Gallar, M. Arias, V. Pachidis, P. Pilidis, R. Singh, Stochastic axial compressor variable geometry schedule optimisation, Aerosp. Sci. Technol. 15 (2011) 366–374. [13] S. Abdollah, F. Alireza, A. Ruhollah, Optimization of variable stator’s angle for off design compression systems using streamline curvature method, in: Proceedings of the ASME Turbo Expo 2009, GT2009-59772. [14] J.R. Barbosa, F.J.D.S. Silva, J.T. Tomita, C. Bringhenti, Influence of variable geometry transients on gas turbine performance, in: Proceedings of the ASME Turbo Expo 2011, GT2011-46565. [15] J. Sun, R.L. Elder, Numerical optimization of a stator vane setting in multistage axial-flow compressors, Proc. Inst. Mech. Eng. A, J. Power Energy 212 (1998) 247–259. [16] F124 Turbofan Engine Brochure, Honeywell, http://www51.honeywell.com/ aero/portal/Common/Documents/myaerospacecatalog-documents/Defense_ Brochures-documents/F124_Engine.pdf. [17] B. Curnock, J. Yin, R. Hales, P. Pilidis, High-bypass turbofan model using a fan radial-profile performance map, Aircr. Des. 4 (2) (2001) 115–126. [18] M.S. Li, J.F. Yin, B. Curnock, Low bypass ratio turbofan performance modeling with fan radial flow profiles, in: International Gas Turbine Congress, 2003, Paper No. TS-094. [19] Y.S. Kang, T.C. Park, O.S. Hwang, S.S. Yang, Experimental research on multi stage transonic axial compressor performance evaluation, J. Fluid Mach. 14 (6) (2011) 96–101.
[20] M. Suzuki, N. Kuno, Research and development of two-stage Fan component in HYPR project, AIAA Paper No. 95-2344. [21] Technical Report, Air force mixed-flow compressor Garrett turbine engine company, Report No. 21-4460-2.3, 1982. [22] NPSS Team, NPSS User Guide Software Release: NPSS 2.4.1, Ohio Aerospace Institute, Cleveland, 2012. [23] S.M. Jones, An introduction to thermodynamic performance analysis of aircraft gas turbine engine cycles using the numerical propulsion system simulation, NASA TM-2007-214690. [24] R.H. Aungier, Axial-Flow Compressors: A Strategy for Aerodynamic Design and Analysis, The American Society of Mechanical Engineers, New York, USA, 2003. [25] S. Kim, D. Kim, C. Son, K. Kim, M. Kim, S. Min, New profile loss model for improved prediction of transonic axial flow compressor performance in choking region, in: Proceedings of the ASME Turbo Expo 2015, Paper No. GT201542797. [26] S. Lieblein, Experimental flow in two-dimensional cascades, NASA SP-36 183226. [27] J.F. Hu, X.C.H. Zhu, H. Ouyang, X.Q. Qiang, Z.H. Du, Performance prediction of transonic axial compressor based on streamline curvature method, J. Mech. Sci. Technol. 25 (12) (2011) 3037–3045. [28] P.I. Wright, D.C. Miller, An improved compressor performance prediction model, IMech Paper C423/028, 1991. [29] W. Jansen, W.C. Moffatt, The off-design analysis of axial-flow compressors, J. Eng. Power 89 (1967) 453–462. [30] A. Wiedermann, D. Frank, U. Orth, M. Beukenberg, Computational and experimental analysis of an industrial gas Turbine compressor, in: Proceedings of the ASME Turbo Expo 2011, Paper No. GT2011-16336. [31] N. Gourdain, F. Wlassow, X. Ottavy, Effect of tip clearance dimensions and control of unsteady flows in a multi-stage high-pressure compressor, J. Turbomach. 134 (5) (2012) 051005. [32] C. Cornelius, T. Biesinger, P. Galpin, A. Braune, Experimental and computational analysis of a multistage axial compressor including stall prediction by steady and transient CFD methods, J. Turbomach. 136 (6) (2014) 061013. [33] C. Cornelius, T. Biesinger, L. Zori, R. Campregher, P. Galpin, A. Braune, Efficient time resolved multistage CFD analysis applied to axial compressors, in: Proceedings of the ASME Turbo Expo 2014, Paper No. GT2014-26846. [34] J. Castiella, A novel design methodology for enhanced compressor performance based on a dynamic stability metric, Master’s thesis, Massachusetts Institute of Technology, 2005. [35] W.P. William, Fundamentals of Turbomachinery, John Wiley and Sons, Inc, USA, 2007. [36] A.S. Lee, R. Singh, S.D. Probert, Modeling of the performance of a F100-PW229 equivalent engine under sea-level static condition, in: 45th AIAA/ASME/ SAE/ASEE Joint Propulsion Conference & Exhibit, 2009, AIAA 2009-5018. [37] D. Kim, S. Kim, C. Son, K. Kim, M. Kim, S. Min, Transient performance prediction of an axial compressor considering VIGV operation speeds, J. Mech. Sci. Technol. 28 (10) (2014) 4099–4107.
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A full engine cycle analysis of a turbofan engine for optimum scheduling of variable guide vanes Sangjo Kim a , Donghyun Kim a , Changmin Son b,∗ , Kuisoon Kim a , Myungho Kim c , Seongki Min c a b c
Department of Aerospace Engineering, Pusan National University, Busan 609-735, Republic of Korea School of Mechanical Engineering, Pusan National University, Busan 609-735, Republic of Korea 4-Advanced Propulsion Technology Center, Agency for Defense Development, Daejeon, Republic of Korea
a r t i c l e
i n f o
Article history: Received 17 April 2015 Received in revised form 7 September 2015 Accepted 9 September 2015 Available online 16 September 2015 Keywords: Variable guide vanes Axial compressor Turbofan engine Off-design performance 1D meanline analysis
a b s t r a c t This paper proposes a full engine cycle analysis to derive the schedule of variable guide vanes (VGVs) in a multi-stage axial compressor for improving the performance of a turbofan engine with required surge margin. Most researchers assumed the operating line of a compressor in process of scheduling of VGVs. However, it has been known that the performance of a compressor is influenced by the angle of VGVs. As a result, the performance variation of a compressor can affect an engine. Therefore, a full engine cycle analysis is conducted to consider the effect of VGVs on a turbofan engine. The VGVs are applied to the front stages of the high pressure compressor in the low-bypass ratio turbofan engine. The compressor of the front stages is transonic three-stage axial flow compressor. The commercial engine simulation program, NPSSTM is employed to analyze the on- and off-design performance of the turbofan engine. 1D meanline analysis is used for performance prediction of a multi-stage axial flow compressor with VGVs. The engine simulation program is coupled with the compressor performance prediction tool to consider the engine performance variation with application of the VGVs. The proposed scheduling algorithm of the inlet guide vane (IGV) and stator vanes (SV) is adjusting the vanes angle to have the minimum loss incidence angle at all rotor blades and to satisfy the required surge margin at off-design condition. The result shows that the proposed algorithm can obtain the scheduling of the IGV, 1st and 2nd SVs angle with stable operation and improved specific fuel consumption of the engine. © 2015 Elsevier Masson SAS. All rights reserved.
1. Introduction When the compressor rotating speed and pressure ratio are reduced, the axial velocity of the front stages of the compressor is decreasing more rapidly than the blade speed. This characteristics cause the high incidence angle of the air onto the blades. As a result, the operating point is pushed to the surge line which will bring about the stall and surge in the compressor. The compressor surge causes the blade vibration and can create rapid blade failure and the compressor flow breaks down [1]. There are several methods [2] to vary the engine cycle to avoid surge on the compressor. Typical approaches use the bleed values or variable exhaust nozzles. Especially, the variable inlet guide vane (IGV) and stator vane (SV) in an axial compressor are generally used to avoid the unstable region. By adapting the variable guide vane (VGV) at low speed, the large incidence angle of the airflow onto the front stage
*
Corresponding author. Tel.: +82 (0)51 510 2321. E-mail address: [email protected] (C. Son).
http://dx.doi.org/10.1016/j.ast.2015.09.007 1270-9638/© 2015 Elsevier Masson SAS. All rights reserved.
rotor blades is reduced to have stable incidence angle. Moreover the VGVs can accomplish accurate matching of the stages, which is crucially important to achieve low losses and stable operation over on- and off-design conditions. Turbojet-to-ramjet transition is very important for the operation of the turbine-based combined cycle engine for the hypersonic flight propulsion system [3,4]. It can operate as turbo mode for low speed range (Mach number 0–3), then changes into ramjet model for higher speed range (Mach number 2.5–5) [5]. However, it has been known that additional difficulties arise in attempting to produce a turbojet which worked well throughout such a wide speed rage. With fixed geometry compressors, turbojets ceased to act as pressure amplifiers beyond Mach number 2.7. The addition of VGVs can raise the limit slightly beyond Mach number 3 [6]. There are numerous studies on investigating the performance and effectiveness of a compressor with VGVs. Mallett and Groesbeck [7] investigated the effects of a compressor interstage bleed and two-position inlet guide vanes to determine their effectiveness in alleviating the part speed stall margin of the J71-A2(X-29)
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Nomenclature 1D HPC HPT IGV LPC LPT m N P PR SF SM SV SFC
one-dimensional high pressure compressor high pressure turbine inlet guide vane low pressure compressor low pressure turbine mass flow rate (kg/s) rotating speed (rpm) pressure (kPa) pressure ratio scaling factor surge margin stator vane specific fuel consumption
turbojet engine. In their study, Mallett and Groesbeck [7] discovered that closing the inlet guide vanes increased the compressor efficiency and slightly raised both the steady-state operating line and stall line in the low-speed range. When the inlet guide vane angle was rotated as +20 degree at design speed, the corrected mass flow rate, total pressure ratio, and efficiency were decreased in 17.9%, 22.8%, and 7.2%, respectively, compared with fixed angle condition. Urasek et al. [8] conducted the performance test of a single stage transonic axial compressor with IGV and SV for stall free operation. Urasek et al. [8] reported that at part speed conditions, the stall points moved to lower flows and correspondingly lower pressure ratio when the guide vanes were closed from their design angles. Steinke [9] performed scheduling of VGVs angle to maximize the efficiency of a three-stage axial compressor on- and off-design condition, a peak efficiency of 0.86 was obtained at design speed near design flow. At part speeds peak efficiency were 0.87 to 0.89 with reset VGVs. Haglind [10] studied the possibility of reducing the formation of contrails by using VGVs for the fan of a high bypass turbofan engine. The author showed that the threshold formation temperature of contrails was reduced by about 1.5 K in the troposphere by employing VGVs for the fan of the engine, corresponding to an altitude of about 300 m. Gallar et al. [11,12] reported the integrated genetic algorithm optimizer within a meanline compressor performance prediction code to maximize the compressor efficiency while keeping an adequate user-defined value of the surge margin. The study assumed that the operating line on the compressor is considered unaffected by the angle of VGVs. The scheduling results for an eight-stage axial compressor in a modern high bypass ratio engine were compared with experimental data from the compressor rig. The result shows that when the schedule of VGVs was applied to the compressor, the efficiencies at highest and lowest total pressure ratio condition were increased in 0.77% and 6.48%, respectively. Abdollah et al. [13] developed an automated optimization tool for scheduling of VGVs in a multi-stage compressor. By using the tool, a ten-stage axial compressor was optimized to maximize its total pressure ratio in off-design conditions. The operating point of a speed line was calculated by surge margin equation with 20% margin. The authors reported that the operating mass flow rate and total pressure ratio were increased in 5.48% and 3.72%, respectively when the compressor used schedule of VGVs. Barbosa et al. [14] carried out the transient study on a small gas turbine performance for different variable IGV angles of a five-stage transonic axial compressor. The authors indicated that simulations needed to study the control strategy. Sun and Elder [15] presented a numerical methodology for optimizing VGVs angle setting in a seven-stage axial compressor to improve the compressor performance at a specific inlet mass
T VGV
η φ
temperature (K) variable guide vane efficiency angle of rotation – IGV and SV settings
Subscripts c eff op rel surge t unscaled
corrected efficiency operating point relative surge point total unscaled value at a performance map
flow rate on each speed line. The investigators reported that varying the stagger of the front stages provides a powerful technique to rematch the stages in order to obtain a high overall performance with a wider surge-free flow range. Most authors assumed the operating line of a compressor in process of scheduling of VGVs. However, it has been demonstrated that the steady-state operating line and stall line are changed by adjusting the angle of a guide vane [7]. The operating line on a compressor is calculated by performance a full engine cycle analysis. Therefore, the engine performance analysis with VGVs is needed to consider the realistic condition for scheduling of VGVs. Therefore, a full engine cycle analysis is conducted to consider the effect of VGVs on a turbofan engine. This study derives the schedule of VGVs of the three-stage axial compressor in the lowbypass ratio turbofan engine by using the full engine cycle analysis. 1D meanline analysis is used to predict the performance of the compressor with VGVs. 1D meanline analysis results are compared with performance test for verification and validation. The commercial engine simulation program, NPSSTM is employed for performance analysis at on and off-design condition. The performance map of the compressor with VGVs is applied to the engine simulation program to predict its impact. The operating line on the performance map of the compressor is calculated by conducting the off-design engine simulation. A scheduling algorithm of the VGVs is suggested to improve both the surge margin and engine SFC at off-design condition. The algorithm takes into account the operating line and the surge margin on the compressor. The engine performance and surge margin with scheduled VGVs are compared with the case of IGV angle only and without VGVs. 2. Engine model The engine, on which the full engine cycle analysis is tested and presented, is a low bypass ratio mixed flow turbofan engine for military flight application. The engine configuration and design parameters, such as engine SFC, bypass ratio, and specific thrust, are refer to the Honeywell/ITEC F124 engine [16]. A schematic picture of the turbofan engine is shown in Fig. 1. The compression system of the engine consists of a three-stage fan, a three-stage axial compressor and a single stage centrifugal compressor. The fan is divided in to two parts, namely inner fan and outer fan, because the fan pressure ratio and isentropic efficiency is change according to the radial direction [17,18]. For modeling purpose, the high pressure compressor (HPC) is split into two compressors, axial part and radial part of HPC. The air at the exit of the radial part of HPC is drawn to cool the high-pressure turbine (HPT) nozzle and rotor. And the air bleed from the exit of the axial part of HPC is
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Fig. 1. Schematic picture of the turbofan engine.
used to cool the low-pressure turbine (LPT). This work assumes that the axial part of HPC is the three-stage transonic axial compressor with IGV, which was presented in Kang et al. [19]. Table 1 shows the design parameters of the engine. The performance map of outer fan is scaled from that of inner fan to consider the differences in fans geometries. Because the core flow is about twice as big as bypass flow. The scale factors are derived from the on-design point analysis and applied to the off-design performance analysis. The equations for the calculation are as follows:
PRbypass = 1 + (PRcore − 1) ×
ηbypass ηbypass = ηcore × ηcore
PRbypass − 1
PRcore − 1
SFPR = SFeff =
Performance: sea level static, standard day, nominal engine, max power
Parameter
Value
Maximum thrust (kN) SFC (g/kN s) Bypass ratio Airflow (kg/s) Turbine inlet temperature (K) Fan pressure ratio Overall pressure ratio
20.6 22.10 0.49 31.1 1600 2.5 19.0
(1) design
(2) design
For the modeling of the performance of inner fan, it implemented the performance map of fan from Suzuki and Kuno [20] is used. The performance map of the axial part of HPC with VGVs is calculated by using 1D meanline analysis. The method and procedure are treated in more detail in the next section. The performance map of the mixed-flow compressor [21] is applied to the radial part of HPC. To treat the high and low pressure turbines in the off-design condition, the performance maps of the turbine are utilized from the database in NPSSTM [22]. The performance maps of those components are scaled upon pressure ratio, efficiency, and mass flow rate except for the axial part of HPC. The scale factors are calculated from the following equations [23]:
SFflow =
Table 1 Turbofan engine design parameters.
mc , design mc , unscaled PRdesign − 1
PRunscaled − 1
ηdesign ηunscaled
(3) (4) (5)
For validation purpose, the performance prediction results for F124 engine are compared with test data. Result is shown in Table 2 and it can be observed that the prediction results of the present engine model agree well test data. 3. Compressor performance analysis with VGV The overall performance parameters of the compressor are given in Table 3. The meridional view and blade row configuration of the compressor are presented in Fig. 2.
Table 2 Performance prediction validation. Parameter
NPSS (Present result)
F124 [16]
Diff. (%)
SFC (g/kN s) Specific thrust (kN/kg/s)
22.0990 0.6659
22.0939 0.6651
−0.02% −0.12%
Table 3 Three-stage compressor performance parameters [19]. Parameter
Value
Number of stages Total pressure ratio Isentropic efficiency Inlet mass flow (kg/s) Rotating speed (RPM)
3 2.50 0.84 9.90 20,000
3.1. 1D meanline analysis Assuming one-dimensional compressible flow, Euler equation employing loss models is applied to calculate rotor efficiency and stator losses at on- and off-design conditions. The selected correlations for 1D meanline analysis are listed in Table 4. The choice of the empirical correlation is based on Kim et al. [25], where the influence of the correlation was investigated in detail. The total pressure ratio and stage efficiency are then calculated iteratively based on the boundary condition and selected correlations. 3.2. Comparison of the performance prediction results Fig. 3 shows the comparison of performance test [19] and predicted results. The 1D meanline results show the underestimated pressure ratio at all speed lines. However, the trends of the pressure ratio and isentropic efficiency of the 1D meanline are agreed well with performance test. In general, it is difficult to predict
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Fig. 2. Meridional view and blade row configuration of the three-stage compressor.
Table 4 Selected correlations for 1D meanline analysis. Correlation
Reference
Incidence angle
Minimum loss Stall Choking
Aungier [24] Aungier [24] Kim et al. [25]
Deviation angle
Reference Axial velocity ratio Incidence angle
Lieblein [26] Hu et al. [27] Lieblein [26]
Losses
Minimum profile loss Off-design profile loss, stall region Off-design profile loss choking region, Shock loss The other losses
Wright and Miller [28] Aungier [24]
Flow blockage
Kim et al. [25] Jansen and Moffatt [29] Wright and Miller [28] Wright and Miller [28]
exactly the performance of a multi-stage axial compressor by using the numerical method [30–33,37]. Kang et al. [19] reported that the difference of the mass flow rate between the performance test and the numerical result of the three-stage axial compressor is 3%. Kang et al. [19] explained the reason is the blade untwist phenomenon caused by force acting on the compressor rotor tip where its thickness is very thin. Therefore present study focuses on the trend of the compressor performance rather than the exact numerical value. Fig. 3. Comparison of performance test and predicted results.
4. Off-design engine performance Off-design performance analysis is conducted under sea level static condition to investigate the engine performance and the operating characteristics. The engine performance is analyzed for the engine thrust range 3.56–20.68 kN. The engine SFC and the surge margin of the compressor with VGVs are compared at the same engine thrust conditions. The operating line on the performance map of the fan for the engine without VGVs is shown in Fig. 4. In the performance map, the relative corrected rotating speed is given by
N c ,rel =
√ ( N / T t )op √ ( N / T t )design
(6)
The results show that the pressure ratio and corrected mass flow decreases with engine thrust. In general, the definition of surge margin is the difference between the operating point of the compressor and the surge line. The surge margin is calculated by using Eq. (7) [34].
SM = 1. −
PRop × mc , surge PRsurge × mc ,op
(7)
Fig. 4. The operating line on the performance map of the fan for the engine without VGV.
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Fig. 5. The operating line on the performance map of the axial part of HPC for the engine without VGV.
Fig. 7. The operating line on the performance map of the HPT for the engine without VGV.
Fig. 6. The operating line on the performance map of the radial part of HPC for the engine without VGV.
Fig. 8. The operating line on the performance map of the LPT for the engine without VGV.
The surge margin of the fan at the 50% rotational speed is about 18%. The decrease of the surge margin with engine thrust is observed. Fig. 5 presents the operating line on the performance map of the axial part of HPC for the engine without VGV. The corrected mass flow rate of the axial part of HPC decreases with the engine thrust. The compressor is approaching to surge region when it is operating at below 87% of the design speed. The efficiency of the compressor decreases when it is operating at surge region. This phenomenon is also reported by Robert [2]. The front stages of the compressor may go into stall since the mass flow rate generally falls off more rapidly than the rotating speed [35]. The off-design behavior of the radial part of HPC for the engine without VGV is plotted in Fig. 6. The result indicates that the surge margin is decreased at off-design condition. The variation of the corrected mass flow rate according to the engine thrust is smaller than that of the other compressors. In general, a decrease of rotating speed will lead to a decrease in flow density and an increase of axial velocity, and hence choking will start at a rear stage [35]. Fig. 7 and Fig. 8 show the operating line on the performance map of the high pressure turbine (HPT) and low pressure turbine (LPT) for the engine without VGV, respectively. Little change of the operating point in the HPT is observed. The pressure ratio and mass flow parameter of the LPT decrease with the engine thrust.
The rotational speed is changed from 100% to 65% of design speed at the off-design condition. Fig. 9 reveals the SFC versus Thrust for the engine without VGVs. The engine shows minimum value of SFC when the thrust is about 8 kN. The typical “fish-hook” behavior is shown with the throttling down of the engine [36]. The surge margin of the axial part of HPC versus Thrust for the engine without VGVs is presented in Fig. 10. At the on-design condition, the surge margin is about 10%. The surge margin decreases with the engine thrust. Especially, the surge margin shows negative value when the engine thrust is below 5 kN. 5. Algorithm for scheduling of the VGVs 5.1. Scheduling of IGV angle only Fig. 11 shows the algorithm for scheduling of IGV angle to satisfy the required surge margin. The target surge margin is set at 10%. Firstly, on-design cycle analysis is performed. Then, for offdesign cycle analysis, cycle analysis program requires the complete performance maps, such as compressors and turbines. The performance maps of the axial part of HPC with variable IGV angle is generated by using 1D meanline analysis and enter in table format. From the off-design cycle analysis, the surge margin is calculated by employing Eq. (7). If the surge margin is smaller than the target
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Fig. 9. SFC versus Thrust for the engine without VGV.
Fig. 12. IGV angle versus Thrust for the engine with the schedules of IGV only.
Fig. 10. Surge margin of the axial part of HPC versus Thrust for the without VGV.
Fig. 13. Efficiency of the axial part of HPC versus Thrust with the schedules of IGV only.
that there is no IGV angle to satisfy the requirement when the engine thrust is below 8.8 kN. The efficiency of the axial part of HPC versus Thrust with the schedules of IGV only is depicted in Fig. 13. The result shows that the efficiency of the compressor is affect by different scheduling methods. The reason is that the working line on the performance map of the compressor is changed by adjusting the IGV angle. 5.2. Scheduling of IGV, 1st and 2nd SVs angle
Fig. 11. Algorithm for scheduling of IGV angle.
value (10%), the IGV angle is adjusted to satisfy the requirement. In the algorithm, maximum IGV rotating angle is set at 40◦ . For comparison, scheduling of IGV angle is also performed by using compressor performance analysis only with fixed working line on the performance map to satisfy the target surge margin. The resultant schedules of IGV angle are plotted in Fig. 12. The IGV angle of the schedule is smaller using full engine cycle analysis than using compressor performance analysis only. The result of the schedule using compressor performance analysis only shows
The algorithm for scheduling of IGV, 1st and 2nd SVs angle is presented in Fig. 14. In general, in a multi-stage axial compressor, the performance depends on the superposition of each stage performance. If all rotors have minimum loss incidence angle, the whole compressor efficiency will be improved. When the incidence angle is bigger than minimum loss position, it can be assumed that the compressor is operated in the stalling region. On the other hand, it is choking region if incidence angle is smaller than minimum loss position. Therefore, if a blade has minimum loss incidence angle, stable operation and improved efficiency of the compressor are expected. Lieblein [26] investigated the minimum loss incidence angle by performing the linear cascade test. The research showed that the minimum loss position of the blade is influenced by inlet flow condition, such as flow angle and inlet Mach number, and blade geometry. Therefore, the minimum loss incidence angle of each rotor is calculated at each iteration of the algorithm. The present compressor performance prediction program calculates the total pressure ratio and isentropic efficiency by using a boundary condition and geometry. The boundary conditions are the inlet flow condition and rotating speed. The boundary
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Fig. 15. IGV, 1st and 2nd SVs angle versus Thrust.
Fig. 16. The performance map of the axial part of HPC for the engine with and without the schedules of VGVs.
Fig. 14. Algorithm for scheduling of IGV, 1st and 2nd SV angle.
condition of the axial part of HPC is calculated by performing the off-design cycle analysis. For the analysis, the IGV, 1st and 2nd SVs angles are adjusted to have minimum loss incidence angle at each rotor. The compressor performance maps with the VGVs angles are then generated. The off-design cycle analysis is re-performed to obtain the operating points of the compressor. The process will continue until the target surge margin is satisfied. The resultant schedule of the IGV and 1st and 2nd SVs is depicted in Fig. 15. The IGV angle shows the minimum value when engine thrust is about 18 kN. At this operating point, the 1st and 2nd SVs angles are bigger than the IGV. When engine trust is about 3 kN, the results show that the IGV rotating angle is the biggest value and the 1st SV is the next big angle. The rotating angle of the IGV is smaller than that of the case with IGV angle only. Gallar et al. [11] and Abdollah et al. [13] conducted a scheduling of VGVs in a multi-stage axial compressor by using an optimization method. However, unlike some authors, this study proposed a scheduling algorithm which controls the angle of IGV and SVs to have the minimum loss incidence angle at the each rotor. The proposed scheduling algorithm has two advantages. First is that the algorithm has a logic to control the angle of variable guide vanes. It has been known that a minimum loss incidence angle at a blade is changed by varying inlet flow conditions. The inlet flow condition of a compressor can be obtained by using a full
engine simulation in every iteration. The control logic can apply high-fidelity simulation method as well as 1D meanline analysis. Second is that calculation time is lower for the proposed algorithm than for an optimization method. In a study by Gallar et al. [11], the iteration number is about 30,000 (the population size of the algorithm is 100 individuals that run over 300 generations) to find the optimum point by using genetic algorithm. However, in this study, the iteration number is just 5 to find the schedule of VGVs. The result indicates that the number of iterations can be reduced significantly when the proposed algorithm is applied to the scheduling procedure. 6. Results The off-design behavior of the axial part of HPC with and without the schedule of the VGVs is illustrated in Fig. 16. When the engine is operated at low thrust condition, the operating line of the axial part of HPC with the schedule passes the maximum efficiency region while that of the case without the schedule is operated around low efficiency region. The pressure ratio of the axial part of HPC with the schedule is low compared with the case without the schedule. The result shows that the operating line of the axial part of HPC is influence by the VGVs. Fig. 17 is presented the off-design behavior of the radial part of HPC. When the schedule is applied to the engine, the corrected mass flow rate and pressure ratio are changed because the flow conditions at the exit of the axial part of HPC are altered. As a result, the operating line is located to lower efficiency region. It is observed that the operating line of the radial part of HPC is affected by the VGVs in the axial part.
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Fig. 17. The performance map of the radial part of HPC for the engine with and without the schedules of VGVs.
Fig. 19. Surge margin of the axial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
Fig. 18. SFC versus thrust for the engine with and without the schedules of VGVs.
Fig. 20. Efficiency of fan versus Thrust for the engine with and without the schedules of VGVs.
By performing the full engine simulation, the engine performance variation with VGVs can be observed. The SFC versus Thrust for the thrust range 3.56–20.68 kN is shown in Fig. 18 for the engine with and without the schedule of VGVs, respectively. When the VGVs are applied to the engine, the engine SFC is lower than that of the engine without VGVs at low thrust. The engine SFC is slightly increased by the VGVs at relatively high thrust. The use of IGV, 1st and 2nd SVs reduces the engine SFC over the whole thrust range compared with the engine with IGV only. The comparison indicates a need of the proposed algorithm for scheduling of angles of VGVs to improve the engine performance compared with the engine with IGV angle only. The surge margin of the axial part of HPC versus Thrust is depicted in Fig. 19. The results show that the surge margins with VGVs are higher than that of the engine without VGVs. The engine with schedule of VGVs meet the required surge margin over the whole thrust range. The efficiency of the fan versus Thrust is presented in Fig. 20. The efficiency of the fan shows the maximum value when the thrust is about 16 kN. After the peak point, the efficiency is decreased with engine thrust. The efficiency of the fan of the engine with the IGV, 1st and 2nd SVs is increased compared with the engine without VGVs at low thrust. When the engine operates at high thrust, the difference is small.
Fig. 21. Efficiency of the axial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
Fig. 21 presents the efficiency of the axial part of HPC versus Thrust. This figure clearly demonstrates that the efficiency of the axial part of HPC depends on the scheduling algorithm. In the engine with IGV only, between 9 kN and 20.68 kN thrust, the
S. Kim et al. / Aerospace Science and Technology 47 (2015) 21–30
Fig. 22. Efficiency of the radial part of HPC versus Thrust for the engine with and without the schedules of VGVs.
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Fig. 24. Efficiency of LPT versus Thrust for the engine with and without the schedules of VGVs.
proach which is consideration of cycle performance and the other researches. 7. Conclusion
Fig. 23. Efficiency of HPT versus Thrust for the engine with and without the schedules of VGVs.
efficiency is decreased compared with the engine without VGVs. When the engine thrust is below 9 kN, the IGV, 1st and 2nd SVs increase the efficiency while the others decrease the efficiency. Comparing these two engines with schedule, the improvement of the efficiency is larger for the use of IGV, 1st and 2nd SVs. The results indicate that the use of IGV, 1st and 2nd SVs promise the most efficient operation on the axial part of HPC. The efficiency of the radial part of HPC versus Thrust is plotted in Fig. 22. The results show that the efficiency using the VGVs is decreased compared with the engine without VGVs. Because the operating line in the radial part of HPC with VGVs is goes down to low efficiency region. The efficiency drop on the radial part of HPC is inevitable when employing the VGVs to satisfy required surge margin, but the efficiency gains at the axial part of HPC make the improvement of the engine SFC at low engine thrust. Fig. 23 and Fig. 24 show the efficiency of the HPT and LPT, respectively. The efficiency of the HPT is nearly constant with thrust. Little change of the efficiency according to the schedules is observed. The efficiency of the LPT decreases with engine thrust. Fig. 24 indicates that the use of VGVs slightly increases the efficiency of the LPT compared with the engine without VGVs at low engine thrust. Gallar et al. [11] and Abdollah et al. [13] assumed the operating line of a compressor in process of scheduling of VGVs. The present results show the evidence of the difference between present ap-
In this paper, authors employ a full engine cycle analysis to consider the effect of scheduling of VGVs and VSVs of a three-stage axial compressor on a low-bypass ratio turbofan engine. The proposed algorithm is controlling the angle of IGV and SVs to have the minimum loss incidence angle at the each rotor to improve the performance of the engine with stable operation at on and offdesign conditions. 1D meanline analysis is used to generate the performance map of the compressor with VGVs. The cycle analysis is conducted at on- and off-design conditions. The off-design cycle analysis is performed using the performance maps. The angles of the IGV and SVs of the axial part of HPC are scheduled using engine cycle simulation tool implementing the proposed algorithm. It is observed that the operating lines on the performance map are changed by using VGVs but for the HPT. From the results, it is clear that the engine performance analysis is essential in process of scheduling of the VGVs. The resultant schedule of VGVs shows that the engine with the schedule satisfies the required surge margin and improved SFC at highly off-design condition. In the engine with the schedule of IGV, 1st and 2nd SVs angles, the SFC is better than that of the engine with IGV angle only because of improved efficiency of the axial part of HPC in off-design condition. Conflict of interest statement None declared. Acknowledgements This research was supported by a grant from Agency for Defense Development (ADD-11-01-05-13), Republic of Korea. Also, this work was supported by “Human Resources Program in Energy Technology” of the Korea Institute of Energy Evaluation and Planing (KETEP), granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20144030200570). Special thanks to Korea Aerospace Research Institute (KARI) for sharing compressor geometry and performance information. References [1] Rolls-Royce, The Jet Engine, Rolls-Royce plc, England, 2005.
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[2] M.P. Robert, Plotting component maps in the Navy/NASA engine program (NNEP) – a method and its usage, NASA TM-101433, 1989. [3] W. Huang, L. Yan, J.G. Tan, Survey on the mode transition technique in combined cycle propulsion systems, Aerosp. Sci. Technol. 39 (2014) 685–691. [4] H. Miyagi, H. Kimura, K. Kishi, Combined cycle engine research in Japanese HYPR program, AIAA-1998-3278, 1998. [5] S. Takata, T. Nagashima, S. Teramoto, H. Kodama, Bypass flow pattern changes at turbo-ram transient operation of a combined cycle engine, in: Unsteady Aerodynamics, Aeroacoustics and Aeroelasticity of Turbomachines, 2006, pp. 345–356. [6] Griffon II and turbo-ramjets – technical director of Nord-Aviation delivers twelfth Louis Bleriot lecture, http://www.flightglobal.com/FlightPDFArchive/ 1959/1959%20-%200777.PDF. [7] W.E. Mallett, D.E. Groesbeck, Effects of compressor interstage bleed and adjustable inlet guide vanes on compressor stall characteristics of a highpressure-ratio turbojet engine at altitude, NACA RM E55G27, 1956. [8] D.C. Urasek, R.J. Steinke, W.S. Cunnan, Stalled and stall-free performance of axial-flow compressor stage with three inlet-guide-vane and stator-blade settings, NASA TN D-8457, 1977. [9] R.J. Steinke, Design of 9.271-pressure-ratio five-stage core compressor and overall performance for first three stages, NASA TP 2597, 1986. [10] F. Haglind, Potential of lowering the contrail formation of aircraft exhausts by engine re-design, Aerosp. Sci. Technol. 12 (2008) 490–497. [11] L. Gallar, M. Arias, V. Pachidis, P. Pilidis, Compressor variable geometry schedule optimisation using genetic algorithms, in: Proceedings of the ASME Turbo Expo 2009, GT2009-60049. [12] L. Gallar, M. Arias, V. Pachidis, P. Pilidis, R. Singh, Stochastic axial compressor variable geometry schedule optimisation, Aerosp. Sci. Technol. 15 (2011) 366–374. [13] S. Abdollah, F. Alireza, A. Ruhollah, Optimization of variable stator’s angle for off design compression systems using streamline curvature method, in: Proceedings of the ASME Turbo Expo 2009, GT2009-59772. [14] J.R. Barbosa, F.J.D.S. Silva, J.T. Tomita, C. Bringhenti, Influence of variable geometry transients on gas turbine performance, in: Proceedings of the ASME Turbo Expo 2011, GT2011-46565. [15] J. Sun, R.L. Elder, Numerical optimization of a stator vane setting in multistage axial-flow compressors, Proc. Inst. Mech. Eng. A, J. Power Energy 212 (1998) 247–259. [16] F124 Turbofan Engine Brochure, Honeywell, http://www51.honeywell.com/ aero/portal/Common/Documents/myaerospacecatalog-documents/Defense_ Brochures-documents/F124_Engine.pdf. [17] B. Curnock, J. Yin, R. Hales, P. Pilidis, High-bypass turbofan model using a fan radial-profile performance map, Aircr. Des. 4 (2) (2001) 115–126. [18] M.S. Li, J.F. Yin, B. Curnock, Low bypass ratio turbofan performance modeling with fan radial flow profiles, in: International Gas Turbine Congress, 2003, Paper No. TS-094. [19] Y.S. Kang, T.C. Park, O.S. Hwang, S.S. Yang, Experimental research on multi stage transonic axial compressor performance evaluation, J. Fluid Mach. 14 (6) (2011) 96–101.
[20] M. Suzuki, N. Kuno, Research and development of two-stage Fan component in HYPR project, AIAA Paper No. 95-2344. [21] Technical Report, Air force mixed-flow compressor Garrett turbine engine company, Report No. 21-4460-2.3, 1982. [22] NPSS Team, NPSS User Guide Software Release: NPSS 2.4.1, Ohio Aerospace Institute, Cleveland, 2012. [23] S.M. Jones, An introduction to thermodynamic performance analysis of aircraft gas turbine engine cycles using the numerical propulsion system simulation, NASA TM-2007-214690. [24] R.H. Aungier, Axial-Flow Compressors: A Strategy for Aerodynamic Design and Analysis, The American Society of Mechanical Engineers, New York, USA, 2003. [25] S. Kim, D. Kim, C. Son, K. Kim, M. Kim, S. Min, New profile loss model for improved prediction of transonic axial flow compressor performance in choking region, in: Proceedings of the ASME Turbo Expo 2015, Paper No. GT201542797. [26] S. Lieblein, Experimental flow in two-dimensional cascades, NASA SP-36 183226. [27] J.F. Hu, X.C.H. Zhu, H. Ouyang, X.Q. Qiang, Z.H. Du, Performance prediction of transonic axial compressor based on streamline curvature method, J. Mech. Sci. Technol. 25 (12) (2011) 3037–3045. [28] P.I. Wright, D.C. Miller, An improved compressor performance prediction model, IMech Paper C423/028, 1991. [29] W. Jansen, W.C. Moffatt, The off-design analysis of axial-flow compressors, J. Eng. Power 89 (1967) 453–462. [30] A. Wiedermann, D. Frank, U. Orth, M. Beukenberg, Computational and experimental analysis of an industrial gas Turbine compressor, in: Proceedings of the ASME Turbo Expo 2011, Paper No. GT2011-16336. [31] N. Gourdain, F. Wlassow, X. Ottavy, Effect of tip clearance dimensions and control of unsteady flows in a multi-stage high-pressure compressor, J. Turbomach. 134 (5) (2012) 051005. [32] C. Cornelius, T. Biesinger, P. Galpin, A. Braune, Experimental and computational analysis of a multistage axial compressor including stall prediction by steady and transient CFD methods, J. Turbomach. 136 (6) (2014) 061013. [33] C. Cornelius, T. Biesinger, L. Zori, R. Campregher, P. Galpin, A. Braune, Efficient time resolved multistage CFD analysis applied to axial compressors, in: Proceedings of the ASME Turbo Expo 2014, Paper No. GT2014-26846. [34] J. Castiella, A novel design methodology for enhanced compressor performance based on a dynamic stability metric, Master’s thesis, Massachusetts Institute of Technology, 2005. [35] W.P. William, Fundamentals of Turbomachinery, John Wiley and Sons, Inc, USA, 2007. [36] A.S. Lee, R. Singh, S.D. Probert, Modeling of the performance of a F100-PW229 equivalent engine under sea-level static condition, in: 45th AIAA/ASME/ SAE/ASEE Joint Propulsion Conference & Exhibit, 2009, AIAA 2009-5018. [37] D. Kim, S. Kim, C. Son, K. Kim, M. Kim, S. Min, Transient performance prediction of an axial compressor considering VIGV operation speeds, J. Mech. Sci. Technol. 28 (10) (2014) 4099–4107.