Variable inlet guide vane (IGV) is used to control the mass flow and generate prewhirl in centrifugal compressors. The efficient operation of IGV is limited to the range of aerodynamic characteristics of their vane profiles. In order to find out the best vane profile for IGV regulation, the modern optimization method was adopted to optimize the inlet guide vane profile. The main methodology idea was to use artificial neural network for continuous fitness evaluation and use genetic algorithm for global optimization. After optimization, the regulating performance of IGV has improved significantly, the prewhirl ability has been enhanced greatly, and the pressure loss has been reduced. The mass flow and power of compressor reduced by using the optimized guide vane at large setting angles, and the efficiency increased significantly; the flow field distribution has been improved obviously, since the nonuniform distribution of flow and flow separation phenomenon greatly weakened or even completely disappeared. The achievement of this research can effectively improve the regulation ability of IGV and the performance of compressor.
In order to adapt to climate change and to meet the user requirements, the gas mass flow in actual operation of a centrifugal compressor needs to be regulated normally [
IGV is installed in the inlet of compressor to regulate mass flow (Figure
IGV in centrifugal compressor.
Usually, researchers pay more attention to the impeller rather than the inlet guide vane, since it is a stationary part in centrifugal compressor. Therefore, there are few designers using modern optimization methods to do optimization design for inlet guide vane profile. In practical application, the inlet guide vanes are used with the existing NACA profile. Cao et al. [
At present, the genetic algorithm is more commonly used for the optimization design of blade in turbomachinery. However, the evolution process of the genetic algorithm needs a lot of fitness and needs a large number of invoking flow calculation procedures, so that the convergence speed is very slow. The optimization of this paper is based on the approximate function technology. The aerodynamic performance of guide vane can be rapidly evaluated by approximate function model. This evaluation process can simulate the real performance of guide vane as fast as possible and without the time-consuming calculation of flow field. According to the samples generated by the database, the approximate function relationship between the geometric optimization variables and the parameters of the aerodynamic target is established by using artificial neural network. On this basis, the genetic algorithm is used to optimize and predict the optimal solution. Then, the predicted results are checked by N-S flow field numerical calculation, and the results are added to the database sample to generate new approximate functions. The optimal solution satisfying different optimization objectives is searched repeatedly. The optimization of guide vane combining genetic algorithm and artificial neural network is adopted in this paper, eliminating a large number of flow field calculations, which can greatly reduce the optimization time.
The ideal IGV regulation system should be able to produce larger prewhirl while minimizing its own losses. We have summarized two evaluation criteria of the performance of IGV regulation, prewhirl coefficient and total pressure loss coefficient.
When the centrifugal compressor adopts inlet guide vanes to regulate, the prewhirl is generated by changing the intake direction, thereby changing the working capacity of the impeller to the gas and realizing the regulation of variable working condition of compressor. Therefore, the ability of the vane to generate prewhirl is an important index to evaluate its performance.
If the airflow gets into the impeller after IGV regulation without loss, according to the principle of momentum conservation, the movement of the airflow in the region will keep momentum unchanged. The cross section at the exit of the guide vane is taken as the object of study. First, we assume the airflow is incompressible before entering into impeller, so the density of gas is constant. We assume the prewhirl angle generated by inlet guide vane is consistent with the setting angle of guide vane, ignoring its deviation and assume the distribution of axial velocity
The equivalent prewhirl radius
The numerator and denominator of formula (
In order to quantitatively describe the prewhirl effect of IGV regulation, introduce the concept of prewhirl coefficient, which is defined as
The magnitude of prewhirl coefficient represents the prewhirl capacity of IGV regulation. The purpose of installing IGV in centrifugal compressors is to produce sufficient prewhirl to achieve the purpose of flow regulation. Therefore, the greater the prewhirl coefficient value of IGV at a certain setting angle, the better.
The flow loss or flow efficiency is regarded as one of the evaluation criteria for evaluating the performance of IGV, as in other static flow components of fluid machinery. In this paper, the total pressure loss coefficient
The pressure loss coefficient represents the magnitude of the flow loss in the IGV channel, so the value of the pressure loss coefficient should be reduced as much as possible.
The parameterization is to describe the guide vane profile with finite design parameters so as to control and modify the guide vane profile. The number of design parameters determines the variability of guide vane profile and also affects the amount of design work. The more the design parameters, the greater the design workload. Therefore, it is very important to select the minimal design variables to express the profile of the guide vane in the process of optimization.
Currently,
The optimization design that was done in this paper is based on the original IGV profile. In order to achieve a good fitting effect and minimize the error between the original data and fitting data, the least squares method was used. In order to ensure the aerodynamic configuration requirements of IGV, the Bezier curve [
The vane profile is similar to the airfoil and its special geometrical characteristics; the suction and pressure sides were separately fitted, so there are two curves in each section [
Figure
Curve fitting of guide vane.
Objective function is the key factor in the process of optimization. The ideal IGV regulation system should be able to produce as much as possible the prewhirl, and its own losses should be as small as possible. In order to enhance the prewhirl ability of guide vane, the prewhirl coefficient is taken as one of the optimization objectives. In addition, in order to reduce the flow losses, the pressure loss coefficient is taken as another optimization objective. Therefore, this optimization has two optimization objectives, and the two optimization objectives will be mutually restricted. If the multiobjective optimization is used, the obtained solution is usually a set of optimal solutions, and it is difficult to find a global optimal solution. Therefore, it is necessary to transform multiobjective optimization into single objective optimization. According to the optimization objective of this research, we need to obtain the maximum value of the prewhirl coefficient and the minimum value of the pressure loss coefficient. In order to combine the two parameters into a single objective function, we put the pressure loss coefficient at the denominator. Thus, the optimization of the guide vane profile is to maximize
The objective function and constraints selected in this paper are based on our previous research results on IGV profile [
The process of optimization design of IGV is shown in Figure
Flow chart of inlet guide vane optimization.
Through the above optimization process, the bottom, the middle, and the top of the vane section profiles were optimized and compared with the original one, as shown in Figure
Comparison of the original and the optimized profile.
After optimization, the pressure loss coefficient of the guide vane is reduced by 1.02027, and the prewhirl coefficient is increased by 0.66518, which significantly improves the prewhirl capability of the guide vanes and greatly reduces the pressure loss. For compressor performance, the flow rate is reduced by 17.67%, the power is reduced by 18%, the pressure ratio is reduced by only 0.007, and the efficiency is increased by 0.94%, shown in Table
Parameters of guide vane regulation before and after optimization.
performance parameter | Original profile | Optimized profile |
---|---|---|
Pressure loss coefficient | 2.54793 | 1.52766 |
Prewhirl coefficient | 1.75281 | 2.41799 |
Mass flow (kg/s) | 25.86 | 21.29 |
Power (MW) | 2.2549 | 1.8479 |
Pressure ratio | 2.39 | 2.383 |
Efficiency (%) | 85.21 | 86.15 |
The optimization was carried out at 60° setting angle of guide vane. In order to explore the performance of optimized guide vane at other setting angles, the performance parameters had been tested at −20°, 0°, 20°, 40°, and 60° and compared with the original ones, as shown in Figure
The comparison of the performance parameters of the guide vane and the compressor at each setting angle.
Pressure loss coefficient
Prewhirl coefficient
Mass flow
Power
Pressure ratio
Efficiency
The optimized guide vane profile can greatly reduce the pressure loss of the guide vane at large setting angles and has little effect on that at small setting angles, while the pressure loss increased slightly at −20° setting angle. When the guide vane is in positive prewhirl regulation, the optimized vane profile can effectively improve the prewhirl capability of the guide vane, and the greater the setting angle of the guide vane, the greater the magnitude of the increase. When the guide vane is in negative prewhirl regulation, the prewhirl capability of the optimized guide vane is slightly decreased.
By adopting the optimized guide vanes, the mass flow and power of the compressor can be reduced at each setting angle and from −20° to 60°; with the increase of the setting angle of the guide vane, the magnitude of the reduction is greater. The optimized guide vane reduces the pressure ratio of the compressor slightly, especially at −20° setting angle. The optimized vane can improve the efficiency of the compressor at positive prewhirl regulation, and the greater the setting angle is, the more obvious the efficiency increases, but there is a small decrease at 0° and −20°.
Therefore, the optimized guide vane greatly improves the regulating ability of the guide vane and the performance of compressor when it is in positive prewhirl regulation, but there are some disadvantages in negative prewhirl regulation. Since the setting angle of guide vane is limited in the negative prewhirl regulation, the disadvantages will not expand. Overall, the optimized vane profile improves the performance of guide vane regulation.
Figures
Comparison of static pressure distribution in the flow passage of the optimized guide vane and the original one.
Original profile
Optimized profile
Comparison of absolute total pressure distribution in the flow passage of the optimized guide vane and the original one.
Original profile
Optimized profile
Figure
Comparison of velocity vector and streamline of the optimized guide vane’s blade to blade section and the original one.
Original profile
Optimized profile
In this paper, the prewhirl coefficient and the total pressure loss coefficient are used as the evaluation indexes for the performance of IGV regulation. The artificial neural network and genetic algorithm are combined to optimize the vane profile of IGV. The ideal IGV profile has been obtained after optimization, and the regulating performance of the guide vane is significantly improved. The optimized guide vane increases its prewhirl capability and reduces its pressure loss greatly. The optimized vane profile makes the pressure field distribution more uniform in the guide vane channel and the vortex of the suction side of the guide vane has completely disappeared, and the flow field distribution in the whole channel has been greatly improved. The optimized IGV can help to reduce the mass flow and the power of compressor and increase the efficiency. Therefore, the optimized profile can greatly improve the regulating performance of IGV.
The authors declare that there are no conflicts of interest regarding the publication of this paper.