CN104408260A - Design method for blade airfoil of tidal current energy water turbine - Google Patents

Abstract

The invention discloses a tidal current energy water turbine blade airfoil design method, comprehensively considering various requirements of water turbine blade design including lift coefficient, drag coefficient, lift-to-drag ratio and cavitation phenomenon, etc., the selected objective function can be based on Different designs require a comprehensive evaluation of turbine airfoils. The abscissa and ordinate of the control points on the leading edge tangent, the trailing edge tangent, and the upper and lower curves of the airfoil are selected as design variables. The cubic spline curve is adopted, which has high fitting precision. FLUENT or CFX computational fluid dynamics software or XFOIL airfoil estimation software are used to calculate the hydrodynamic performance and pressure distribution of the hydrofoil airfoil, which fully guarantees the accuracy of the calculation. The hydrofoil airfoil design method is based on the genetic optimization algorithm, which can obtain the global optimal solution. The invention can not only improve the hydrodynamic performance of the blade airfoil of the tidal current energy water turbine, but also reduce the maximum pressure coefficient of the surface, thereby achieving the purpose of avoiding the cavitation phenomenon.

Description

A design method for blade airfoil of tidal current energy turbine

technical field

The invention belongs to the field of renewable energy, and in particular relates to a blade airfoil design method for designing tidal current energy water turbines, which can be used in the airfoil design of various types of water turbines.

Background technique

With the development of the world economy, energy consumption is increasing. Due to the fossil energy crisis and the environmental pollution and carbon emissions caused by traditional energy, clean and renewable energy is becoming increasingly important. Tidal current energy is a very important new energy source with the advantages of reliability, periodicity, wide distribution, and sustainability. Tidal current energy will play an important role in future energy. In order to utilize tidal current energy, water turbines are adopted as the main energy capture device. Therefore, how to improve the capacity capture efficiency of tidal current energy turbines has become a key factor affecting the popularization and application of tidal current energy generation.

As one of the most important factors that compose the shape of the blade, the hydrofoil airfoil has an important impact on the energy conversion efficiency of the tidal energy turbine. At present, the known airfoils are basically obtained by considering the design requirements of aerospace and wind turbines. There are very few special hydrofoil airfoils for tidal current energy turbines, and there are even fewer airfoil design methods.

There are two main problems in the traditional airfoil design method applied in aerospace and wind turbines: one is that the hydrofoil airfoil has some specific design requirements different from aerospace and wind turbines. The design method is not applicable; second, most of the design methods are mostly based on a single objective, and the actual airfoil design objective is very complex, and multiple objectives need to be considered to obtain a reasonable airfoil; third, most of the design methods are based on sensitivity analysis Optimization method, it is difficult to obtain the global optimal solution. With the development of tidal current power station projects in my country, in order to develop tidal current energy turbines with independent intellectual property rights, it is necessary to establish a complete airfoil design method.

Contents of the invention

The purpose of the present invention is to overcome the shortcomings and deficiencies of the above-mentioned prior art, and propose a tidal current energy water turbine blade airfoil design method.

In order to solve the above technical problems, the technical solution adopted in the present invention is:

Step 1: Determine the design variables and objective function according to the design requirements, and establish the hydrofoil profile optimization model;

Step 2: Determine the calculation method of hydrodynamic performance and pressure coefficient and the fitness function of genetic algorithm;

Step 3: Generate the initial population and fit the hydrofoil airfoil curve;

Step 4: Generate hydrofoil airfoil fluid area grid model, calculate and output hydrodynamic performance, and output information such as lift, drag and pressure;

Step 5: Calculate the objective function according to the hydrodynamic coefficient and the pressure coefficient, evaluate according to the fitness function, and judge whether it is converged. If it converges, the optimization will end. Otherwise, generate a new population and return to step 3.

This method comprehensively considers various requirements of turbine blade design, including lift coefficient, drag coefficient, lift-to-drag ratio, and cavitation phenomenon. The selected objective function can comprehensively evaluate the turbine airfoil according to different design requirements. The abscissa and ordinate of the control points on the leading edge tangent, the trailing edge tangent, and the upper and lower curves of the airfoil are used as design variables. Cubic spline curves are used, which have high fitting accuracy. FLUENT or CFX computational fluid dynamics software or XFOIL airfoil estimation software calculates the hydrodynamic performance and pressure distribution of the hydrofoil airfoil, which fully guarantees the accuracy of the calculation. The hydrofoil airfoil design method is based on the genetic optimization algorithm and can obtain the global optimal solution.

The advantages of the present invention are:

1) Compared with the traditional water turbine design method, the present invention comprehensively considers various aspects of the hydrofoil airfoil design of the water turbine, and can obtain the best hydrofoil airfoil curve according to the requirements of different water areas and marine environments.

2) The design variable selection and curve fitting method in the proposed design method can accurately describe the real hydrofoil airfoil curve, and can expand the design space as much as possible.

3) Compared with the traditional optimization method, the genetic algorithm adopted in the present invention has the advantages of broad representation of feasible solutions, group searchability, random searchability and globality, and can obtain the global optimal solution.

Description of drawings

Fig. 1 is the flow chart of tidal current energy water turbine airfoil design method in the present invention;

Fig. 2 is hydrofoil airfoil and design variable thereof among the present invention;

Fig. 3 is the target lift coefficient curve among the present invention;

Fig. 4 is the cavitation phenomenon of water turbine hydrofoil airfoil among the present invention;

Fig. 5 is the comparison of different design hydrofoil airfoil designs in the embodiment of the present invention;

Fig. 6 is the pressure distribution comparison under the different design target function situation in the embodiment among the present invention;

Fig. 7 is the comparison of the lift coefficient under different design objective function situations in the embodiment of the present invention;

Fig. 8 is the comparison of drag coefficient under different design target function situations in the embodiment among the present invention;

Fig. 9 is the lift-to-drag ratio comparison under the situation of different design objective functions in the embodiment of the present invention;

In the picture:

1. Hydrofoil; 2. Airfoil curve; 3. Airfoil centerline; 4. Leading edge;

5. Trailing edge; 6. Control point; 7. Control point design domain; 8. Traditional lift coefficient curve;

9. Target lift coefficient curve

Detailed ways

The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

As shown in Fig. 1, the airfoil design method of tidal current energy turbine hydrofoil 1 proposed by the present invention includes an optimization module, an objective function module and a performance calculation module.

The optimization module is mainly to generate the initial design scheme, evaluate the hydrodynamic performance of the new hydrofoil 1 airfoil scheme, and generate new airfoil design parameters on the basis of the original design scheme.

The main function of the objective function module is to generate a new geometric configuration according to the airfoil parameters of the hydrofoil 1, extract the analysis results from the computational fluid dynamics analysis results, and obtain the objective function according to the calculation results.

The main function of the performance calculation module is to generate discrete grid data according to the geometric configuration, and use FLUENT or CFX or XFOIL software to calculate the lift coefficient, drag coefficient and pressure distribution of the hydrofoil 1 airfoil, and provide calculation basis for the objective function module.

According to the above three modules, the present invention adopts the genetic algorithm to optimize the design of the hydrofoil 1 airfoil of the tidal current energy turbine, and the calculation of the proposed hydrofoil 1 airfoil optimization method is carried out according to the following steps.

The first step is to determine the design variables and objective function according to the design requirements, and establish the hydrofoil 1 airfoil optimization model.

The design variables are directly related to the hydrofoil 1 airfoil, so how to select the sampling point method and curve fitting method is particularly important. The selection of the objective function is directly related to the performance of the designed hydrofoil 1 airfoil, which needs to be flexibly set according to the design requirements.

As shown in Figure 2, it is a typical hydrofoil 1, the airfoil centerline 3 is connected between the leading edge 4 and the trailing edge 5, and at least four or more are selected on the airfoil curve 2 of the hydrofoil 1 according to the initial design plan. Control point 6, the control point 6 is a point on the airfoil curve 2, the position of the control point 6 can be moved by changing the abscissa or ordinate size of the control point 6, so that the shape of the airfoil curve 2 can be changed, and then the hydrofoil can be improved. 1 The purpose of hydrodynamic performance, the control point design domain 7 is the design space enclosed by the upper and lower bounds of the abscissa and ordinate of the control point 6, in which m and n control points are respectively selected on the upper and lower airfoil curves 2 of the hydrofoil, in order to To control the shape of the leading edge and trailing edge of hydrofoil 1, the tangent of the leading edge and trailing edge is also used as a design variable, and the design variable x is shown in the following formula.

x＝(x ₀₀ ,x ₁₁ ,y ₁₁ ,x ₁₂ ,y ₁₂ ,...,x _1m ,y _1m ,x ₂₁ ,x ₂₁ ,x ₂₂ ,y ₂₂ ,...,x _2n ,y _2n , x ₀₁ )

Where x ₀₀ and x ₀₁ are the tangents of the leading edge and trailing edge of the hydrofoil 1 respectively, and (x _1m , y _1m ) and (x _2n , y _2n ) are the curve 2 of the upper and lower airfoil of the hydrofoil respectively Control point 6 coordinates, x _2n and x _1m are the abscissas of the control point 6 of the upper and lower airfoil curve 2 of the hydrofoil, and y _1m and y _2n are the ordinates of the control point 6 of the upper and lower airfoil curve 2 of the hydrofoil.

Different positions of turbine blades along the spanwise direction have different design requirements. Near the outer part of the blade, the airfoil is required to have a larger lift coefficient and lift-to-drag ratio, as well as a smaller drag coefficient, so that a smaller chord length can be used. Achieving specified hydrodynamic loads. From the perspective of hydrodynamic design, the lift-to-drag ratio of the wing tip area is the most important parameter. Due to the large load on the turbine, thicker airfoils are generally used in order to meet the requirements of structural design. Since the part close to the root of the wing bears a huge load, in order to arrange the structure, there must be special requirements for the thickness of the airfoil, but at this time, a large hydrodynamic performance will be sacrificed. In order to optimize the hydrodynamic performance of the turbine, different airfoils are arranged along the span direction, and specific airfoils need to be designed according to different design requirements. Therefore the present invention divides design object into two classes, and one class is basic hydrodynamic performance, has comprised lift coefficient, drag coefficient and lift-to-drag ratio, is directly related to the energy conversion efficiency of water turbine; The second class is pressure coefficient, directly related Cavitation phenomenon may affect the service life and reliability of the turbine.

First of all for hydrodynamic performance. For airfoils in the field of wind turbines, the blades of the wind turbine may be in the stall region, and when the angle of attack reaches the stall point, the aerodynamic efficiency may drop sharply. As shown in Figure 3, the comparison between the traditional lift coefficient curve 8 and the target lift coefficient curve 9, the traditional airfoil may cause a sharp drop in the lift coefficient near the stall point, which will have an impact on the energy utilization efficiency of the tidal energy turbine, Therefore it is not suitable as the water turbine hydrofoil 1 airfoil. For tidal energy turbines, in the design, it is more hoped that the hydrodynamic performance will not change too drastically with the angle of attack, especially in the stall region. Therefore the present invention proposes that in the specific airfoil design, the separation point is required to slowly move to the trailing edge with the increase of the angle of attack, which is specifically shown as slowly changing the lift coefficient of the target lift coefficient curve 9 with the increase of the angle of attack, fully Guarantee turbine performance. In addition, the drag coefficient, lift-to-drag ratio, etc. will also have an important impact on the hydrodynamic performance of the hydrofoil 1 of the turbine. In order to design the hydrofoil 1 airfoil with the best performance, this requires the objective function to consider the hydrodynamic properties such as lift coefficient, drag coefficient, lift-to-drag ratio and pressure coefficient under multiple working conditions, and carry out comprehensive optimization design.

Secondly, for the pressure coefficient problem. Bubbles form when the pressure in a fluid region is less than the cavitation pressure value. Cavitation is caused by the rapid rupture of an air bubble in water, creating a shock wave. Passage-type cavitation typically occurs in mechanical structures such as pumps, propellers, and impellers. From the perspective of fluid design, the cavitation cavitation problem caused by the pressure of the turbine blade should be considered in the design of the airfoil of the turbine blade, because the shock wave generated by the rupture of the inertial cavity may cause damage to the turbine structure. important damage. As shown in Figure 4, the condition of cavitation phenomenon on the hydrofoil 1, the pressure coefficient distribution will have a maximum value along with the chord position distribution, when the pressure coefficient C _p on the hydrofoil 1 is greater than the cavitation coefficient σ _c Cavitation will occur.

The void coefficient is defined as follows:

${\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; v</span>}}}{\mathrm{<span\; class="notranslate">\; 0.5</span>}\mathrm{<span\; class="notranslate">\; \&rho;</span>}{\mathrm{<span\; class="notranslate">\; V</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

The pressure coefficient is defined as follows:

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}{\mathrm{<span\; class="notranslate">\; 0.5</span>}\mathrm{<span\; class="notranslate">\; \&rho;</span>}{\mathrm{<span\; class="notranslate">\; V</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

Among them, p _v is the cavitation pressure, and p _L is the surface pressure of the hydrofoil 1 airfoil, which mainly depends on the temperature of the water. p ₀ is the partial pressure, q is the dynamic pressure, and V is the flow rate of water.

The cavitation phenomenon is a unique problem in the design of the turbine. The cavitation phenomenon that occurs during the operation of the tidal energy turbine may directly damage the structure of the turbine, thereby affecting the service life and reliability of the turbine. Therefore, it is necessary to reduce the possibility of cavitation in tidal energy turbines as much as possible. In order to avoid cavitation, it is necessary to reduce the maximum pressure coefficient of the upper part of the hydrofoil 1 as much as possible when designing the hydrofoil 1 . However, the pressure coefficient is directly related to hydrodynamic properties such as the lift coefficient and the lift-to-drag ratio, and the lift coefficient can be obtained by numerically integrating the pressure coefficient along the airfoil curve 2 . Therefore, in the optimization model, two aspects can be used to achieve the purpose of avoiding cavitation without losing hydrodynamic performance. On the one hand, the maximum pressure coefficient should be reduced as much as possible, and on the other hand, the pressure coefficient should be evenly distributed along the airfoil curve 2 as much as possible. In order to avoid the occurrence of cavitation, the present invention proposes to take the pressure coefficient as one of the design objective functions.

Finally, in order to obtain the hydrofoil 1 airfoil curve 2 with optimal performance, the objective function comprehensively considers the lift coefficient, drag coefficient, lift-to-drag ratio and pressure coefficient, and combines the design variables to establish the following airfoil optimization model:

Objective function:

f(x)=f(C _L ,C _L /C _D ,C _D ,C _pmax )

Restrictions:

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 00</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 00</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 00</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 01</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 01</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 01</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; m</span>}$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; no</span>}$

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; m</span>}$

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; no</span>}$

Among them, C _L , C _L /C _D , _CD and C _p are lift coefficient, lift-to-drag ratio, drag coefficient and maximum pressure coefficient at any angle of attack, respectively, all of which are functions of the design variable x. and are the lower bounds of leading edge, trailing edge, control point abscissa on the upper surface of the airfoil, ordinate ordinate of the control point on the upper surface of the airfoil, abscissa of the control point on the lower surface of the airfoil, and ordinate of the control point on the lower surface of the airfoil, and are the upper bounds of the leading edge, the trailing edge, the abscissa of the control point on the upper surface of the airfoil, the ordinate of the control point on the upper surface of the airfoil, the abscissa of the control point on the lower surface of the airfoil, and the ordinate of the control point on the lower surface of the airfoil. m and n are the number of control points of the upper and lower airfoil curves of the hydrofoil respectively. The control point design domain 7 of the control point 6 on the airfoil curve 2 of the hydrofoil 1 is the abscissa interval of the control point 6 on the upper surface of the airfoil and the ordinate interval Or the abscissa interval of control point 6 on the lower surface of the airfoil and the ordinate interval The enclosed rectangular range, the control point 6 changes within this range, and the optimal value is calculated.

The objective function f(x) can be any combination of hydrodynamic performance and pressure coefficient, and can be flexibly selected according to the actual airfoil design. The optional objective function types are as follows:

1)f(x)＝w ₁ C _L +w ₂ C _L /C _D +w ₃ C _D +w ₄ C _pmax

where w _i (i=1...4) are the weights of lift coefficient, lift-to-drag ratio, drag coefficient and maximum pressure coefficient respectively, and satisfy and 0≤w _i ≤1 (i=1, 2, 3), which can be flexibly selected according to design requirements in actual airfoil design.

2)f(x)＝(w ₁ C _L +w ₂ C _L /C _D +w ₃ C _D )C _pmax

The objective function is the product of airfoil hydrodynamic performance and pressure coefficient, where w _i (i=1...3) are the weights of lift coefficient, lift-to-drag ratio and drag coefficient respectively, and satisfy and 0≤w _i ≤1 (i=1, 2, 3), which can be flexibly selected according to design requirements in actual airfoil design.

The specific objective function is not limited to the above three types, and can be flexibly selected according to the needs of the actual sea area. And the lift coefficient, drag coefficient, lift-to-drag ratio, and pressure coefficient can be a single arbitrary angle of attack, or a combined function g(x) of each hydrodynamic coefficient and pressure coefficient function under multiple angles of attack as shown in the following formula .

$\mathrm{<span\; class="notranslate">\; g</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; g</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; f</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>}_{{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>}_{{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>}_{{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; v</span>}}}<span\; class="notranslate">\; )</span>$

Among them, α _u is the angle of attack of the hydrofoil, is the hydrodynamic performance objective function when the angle of attack is α _u , v is the number of angles of attack selected in the objective function, the combination function g(x) can comprehensively consider the hydrodynamic performance parameters under any angle of attack, and can take For any type of combination, preferably, the weighted summation method shown in the following formula can be adopted.

$\mathrm{<span\; class="notranslate">\; g</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; v</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; u</span>}}\mathrm{<span\; class="notranslate">\; f</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>}_{{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; u</span>}}}$

where ω _u is the weight coefficient, and satisfies

The second step is to determine the calculation method of hydrodynamic coefficient and pressure coefficient and the fitness function of genetic algorithm.

After the optimization model is established, the next step is to apply the optimal design to the established model. In order to accurately evaluate the hydrodynamic performance of the hydrofoil 1, FLUENT or CFX or XFOIL numerical simulation programs are used to calculate the lift coefficient, drag coefficient, lift-to-drag ratio and pressure distribution. The specific numerical calculation method can be flexibly selected according to the design needs. In order to obtain the best hydrofoil 1 airfoil curve 2, a genetic algorithm with global search capability is used. During the process of genetic algorithm, the evaluation of the fitness function of each design scheme has an important impact on the optimization results and calculation process.

The fitness function is a key factor in evaluating the hydrodynamics of the hydrofoil 1 airfoil, which involves the optimization process. In the optimization process, the solutions with high fitness are retained according to the fitness function, and the solutions with poor fitness are eliminated. The present invention adopts the fitness function shown in the following formula.

$\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>}{\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; ss</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>}$

Where h(s) is the fitness of the sth design scheme, ss is the number of design schemes in the population, and f(x _s ) is the objective function of the sth design scheme.

The third step is to generate the initial population and fit the hydrofoil 1 airfoil curve 2 .

According to the design variables and their upper and lower bounds, randomly ss initial design schemes (ss is greater than or equal to 10), this group of initial design schemes is the initial population. Generate and fit this group of initial design schemes into hydrofoil 1 airfoil curve 2 . In order to accurately describe the airfoil without sacrificing too much geometric information, the selection of the fitting curve is very important, and the polynomial spline curve can significantly reduce the number of design variables. The present invention mainly adopts the cubic spline curve, which is different from the general cubic spline curve fitting method. The present invention proposes to fit the cubic spline curve with the abscissa and ordinate, the leading edge and the trailing edge tangent of the control point 6 , so as to achieve the purpose of maintaining good hydrodynamic performance of the airfoil by controlling the size of the leading edge and trailing edge tangent. However, the method of fitting the curve is not limited in the specific implementation, and any other curve fitting method may also be used. In order to expand the search space as much as possible, select as many control points 6 as possible on the airfoil curve 2, use the abscissa and ordinate of each point as the design variable, and pass the points on the airfoil curve 2 and the leading edge and trailing edge tangent to fit the airfoil curve 2. Furthermore, the airfoil curve 2 of the hydrofoil 1 is generated.

The fourth step is to generate the hydrofoil 1 airfoil fluid area grid model, calculate and output the hydrodynamic performance, and output information such as lift, drag and pressure.

Process the generated hydrofoil 1 airfoil curve 2 in geometric processing software such as AUTOCAD or CATIA to generate a geometric model. Import the generated geometric model into the grid generation software such as ICEMCFD or GRIDGEN or GAMBIT, and establish the grid model of the hydrofoil 1 airfoil fluid area in the software. Import the generated grid file into fluid dynamics software such as FLUENT or CFX, and calculate the corresponding lift, drag and pressure, and output it as the basis for calculating the objective function. In the present invention, in order to improve calculation efficiency, XFOIL software can also be used. This software only needs geometric curve information and does not need complicated geometric CAD information and grid process, so the calculation efficiency can be greatly improved.

The fifth step is to calculate the objective function according to the hydrodynamic coefficient and the pressure coefficient, evaluate according to the fitness function, and judge whether it is converged, and if it converges, the optimization will end; otherwise, a new population will be generated, and the return to the third step will be performed.

Extract the calculation results and calculate the objective function of different design schemes in the population, evaluate the fitness of ss different design schemes according to the fitness function, and sort each design scheme according to the fitness, according to the fitness of each design scheme in the population and the number of iterations to judge whether it converges. If it converges, the calculation ends, and the design scheme with the highest fitness in the population is taken as the optimal solution of the hydrofoil 1 airfoil curve 2 . If it does not converge, you need to regenerate a new population according to the following method.

According to the fitness of ss different design schemes in the population, the design schemes with low fitness are eliminated according to a certain ratio (5%-20%), and then each design scheme in the population is coded with binary numbers. All 2m + 2n + 2 design variables of the code are coded into a binary number and arranged in the order of leading edge tangent, airfoil upper surface curve abscissa and ordinate, airfoil lower surface curve abscissa and ordinate, trailing edge tangent . According to a certain ratio (5%-20%), the retained better design scheme is mutated and hybridized to obtain a new solution, so as to ensure that the population size ss remains unchanged. The binary number encoded into each design scheme is shown in the following formula:

P=[the m abscissas and ordinates of the upper surface of the leading edge tangent airfoil n abscissas and ordinates of the lower surface of the airfoil trailing edge tangent]]

The leading edge tangent, the abscissa and ordinate of the airfoil upper surface curve, the abscissa and ordinate of the airfoil lower surface curve, and the trailing edge tangent are represented by a binary number respectively. The specific expression is as follows. The first row represents the converted binary number, and the second row represents the number of the design variable in the coded binary number. There are 2m+2n+2 design variables in total, and the first one is the leading edge tangent x ₀₀ , the 2nd to 2m+1 are the abscissa and ordinate of the upper surface curve of the airfoil, and are arranged in the order of (x ₁₁ ,y ₁₁ )(x ₁₂ ,y ₁₂ )...(x _1m ,y _1m ) , the 2m+2 to 2m+2n+1 are the abscissa and ordinate of the lower surface curve of the airfoil, and according to (x ₂₁ ,y ₂₁ )(x ₂₂ ,y ₂₂ )...(x _2m ,y _2m ) , the last one is the trailing edge tangent x ₀₁ .

Decode the designs in the new population from binary codes to decimal numbers and return to step 3, ignoring the step in which the new population is generated.

Example 1:

In order to verify the design method proposed by the present invention, the hydrofoil airfoil curves in different design situations are optimally designed. For tidal energy turbines, different positions of the blade along the span direction have different design requirements. Near the wing tip, a thin airfoil with a higher lift-to-drag ratio is a better choice, and in a wider range of attack angles, it must be It has a high lift coefficient and lift-to-drag ratio, and the drag coefficient should be as small as possible. Since the root bears a large load, in order to ensure that the blade has sufficient structural rigidity and strength, the root airfoil is required to have a large thickness. Furthermore, avoiding cavitation may lead to the selection of thicker airfoils. In order to avoid cavitation, the maximum pressure coefficient should be reduced as much as possible. Therefore, in order to comprehensively evaluate the tidal energy turbine airfoil design method proposed by the present invention, the Reynold number is 1e6, and the objective function is the lift coefficient, drag coefficient, lift-to-drag ratio and pressure coefficient when the angle of attack is 3°. Take three control points on the upper and lower airfoil curves, a total of six control points, each control point has two design variables of abscissa and ordinate, plus the tangent of the leading edge and trailing edge, a total of eight design variables, The initial population size is 10.

Based on the optimization model and solution method proposed by the present invention, several airfoil curves under various conditions with different design requirements are finally obtained, as shown in FIG. 5 . It can be seen from the figure that when the drag coefficient is minimized and the lift coefficient is maximized, the airfoil curve is relatively close. When the lift-drag ratio is maximized, the maximum thickness is located at 35% from the leading edge of the airfoil, and the maximum thickness is 8.8% of the chord length; the minimum In the case of optimized drag coefficient, the maximum thickness is 35% from the leading edge, and the maximum thickness is 8.3% of the chord length. For the water turbine, since the larger lifting force is the thrust perpendicular to the plane of the water turbine, the proportion of the axial rotation force converted into the water turbine is relatively small. Different from the lift coefficient, the reduction of the drag coefficient can significantly improve the hydrodynamic performance, so the drag coefficient plays a more important role in the turbine design. Different from the first two airfoils, the airfoils obtained by maximizing the lift coefficient and minimizing the minimum pressure coefficient are quite different. In the case of maximizing the lift coefficient, the front part of the airfoil is thicker, and the thickness of the airfoil decreases at the trailing edge, the maximum thickness is located at 39% from the leading edge of the airfoil, and the maximum thickness is 11.4% of the chord length; while for the minimum Negative pressure coefficient, the maximum thickness is located at 52% from the leading edge of the airfoil, and the maximum thickness is 8.8% of the chord length.

The surface pressure coefficients of four different airfoils at an angle of attack of 3° are shown in Figure 6. It can be seen from the figure that the pressure distribution is the most uniform when the pressure coefficient is minimized, and the minimum value is around -0.5. It can be seen that the minimum pressure coefficient can be The pressure distribution on the surface of the airfoil is greatly improved, and the generation of cavitation can be avoided as much as possible. The minimum pressure coefficient of the airfoil under the conditions of minimizing the drag coefficient and maximizing the lift-to-drag ratio is about -1.1, and the two are relatively close. In the case of maximizing the lift coefficient, the peak value of the minimum pressure coefficient is the smallest, reaching about -1.5, which is most likely to cause cavitation problems more easily.

The lift coefficient, drag coefficient and lift-drag ratio under different design objective functions are shown in Fig. 7-9. Similar to the airfoil data results, the two airfoils obtained by minimizing the drag coefficient and maximizing the lift-to-drag ratio have very close hydrodynamic performance. When the negative pressure coefficient is used as the objective function, the lift coefficient is much smaller than the other three cases, and the drag coefficient is close to the case of minimizing the drag coefficient. Although the maximum lift coefficient has a large lift coefficient, the drag coefficient is significantly greater than other airfoils, and although the airfoil has the largest lift coefficient at a 3° angle of attack, as the angle of attack increases, the maximum Lift-to-drag ratio and an airfoil with a greater lift coefficient when the drag coefficient is minimized. Therefore, when designing the airfoil, the hydrodynamic performance at one angle of attack cannot only be considered, but a comprehensive design is required.

It can be concluded from the examples that the design method of hydrofoil airfoil of the turbine proposed by the present invention can not only significantly improve the lift coefficient, drag coefficient and lift-to-drag ratio, but also reduce the maximum pressure coefficient, thereby improving hydrodynamic performance and avoiding cavitation the goal of.

The above-mentioned embodiments should be understood that these embodiments are only used to illustrate the present invention more clearly, and are not intended to limit the scope of the present invention. After reading the present invention, those skilled in the art will understand the various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

Claims (8)

1. A method for designing a blade airfoil of a tidal current energy water turbine is characterized by comprising the following steps:

the method comprises the following steps: determining design variables and an objective function according to design requirements, and establishing a hydrofoil wing section optimization model;

wherein,

an objective function:

f(x)＝f(C_L,C_L/C_D,C_D,C_pmax)

designing variables:

x＝(x₀₀,x₁₁,y₁₁,x₁₂,y₁₂,...,x_1m,y_1m,x₂₁,x₂₁,x₂₂,y₂₂,...,x_2n,y_2n,x₀₁)

constraint conditions are as follows:

<math> <mrow> <msubsup> <mi>x</mi> <mn>00</mn> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>x</mi> <mn>00</mn> </msub> <mo>&le;</mo> <msubsup> <mi>x</mi> <mn>00</mn> <mi>U</mi> </msubsup> </mrow> </math>

<math> <mrow> <msubsup> <mi>x</mi> <mn>01</mn> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>x</mi> <mn>01</mn> </msub> <mo>&le;</mo> <msubsup> <mi>x</mi> <mn>01</mn> <mi>U</mi> </msubsup> </mrow> </math>

<math> <mrow> <msubsup> <mi>x</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>x</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> </msub> <mo>&le;</mo> <msubsup> <mi>x</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> <mi>U</mi> </msubsup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

<math> <mrow> <msubsup> <mi>x</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>x</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msub> <mo>&le;</mo> <msubsup> <mi>x</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> <mi>U</mi> </msubsup> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>n</mi> </mrow> </math>

<math> <mrow> <msubsup> <mi>y</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>y</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> </msub> <mo>&le;</mo> <msubsup> <mi>y</mi> <mrow> <mn>1</mn> <mi>i</mi> </mrow> <mi>U</mi> </msubsup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

<math> <mrow> <msubsup> <mi>y</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> <mi>L</mi> </msubsup> <mo>&le;</mo> <msub> <mi>y</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msub> <mo>&le;</mo> <msubsup> <mi>y</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> <mi>U</mi> </msubsup> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>n</mi> </mrow> </math>

wherein, C_L、C_L/C_D、C_DAnd C_pmaxRespectively is a lift coefficient, a lift-drag ratio, a resistance coefficient and a maximum pressure coefficient under any attack angle condition, and are functions of a design variable x;

andrespectively is the lower boundary of the front edge, the tail edge, the abscissa of the control point of the upper surface of the wing profile, the ordinate of the control point of the upper surface of the wing profile, the abscissa of the control point of the lower surface of the wing profile and the ordinate of the control point of the lower surface of the wing profile, andthe control points are respectively the upper boundaries of the front edge, the tail edge, the abscissa of the control point on the upper surface of the wing profile, the ordinate of the control point on the upper surface of the wing profile, the abscissa of the control point on the lower surface of the wing profile and the ordinate of the control point on the lower surface of the wing profile;

m and n are the number of curve control points of the upper and lower wing profiles of the hydrofoil respectively;

x₀₀and x₀₁Are respectively tangent lines of the front edge and the rear edge of the hydrofoil airfoil (x)_1m,y_1m) And (x)_2n,y_2n) Respectively as the coordinates of control points, x, on the upper and lower airfoil profiles of the hydrofoil_2nAnd x_1mIs the abscissa of the control point of the upper and lower airfoil profiles of the hydrofoil, and y_1mAnd y_2nThe longitudinal coordinates of the curve control points of the upper and lower wing profiles of the hydrofoil are shown;

step two: determining a calculation method of hydrodynamic performance and pressure coefficient and a fitness function of a genetic algorithm;

step three: generating an initial population and fitting a hydrofoil profile curve;

step four: generating a hydrofoil airfoil fluid region grid model, calculating and outputting hydrodynamic performance, and outputting information such as lift force, resistance, pressure and the like;

step five: and calculating a target function according to the hydrodynamic coefficient and the pressure coefficient, evaluating according to the fitness function, judging whether convergence occurs or not, finishing optimization if convergence occurs, otherwise, generating a new population, and returning to the step three.

2. The method for designing the blade airfoil of the tidal current energy turbine as set forth in claim 1, wherein the objective function f (X) is in the form of:

f(x)＝w₁C_L+w₂C_L/C_D+w₃C_D+w₄C_pmax

wherein w_i(i 1.. 4) are weights of a lift coefficient, a lift-drag ratio, a drag coefficient, and a maximum pressure coefficient, respectively, and satisfyAnd 0. ltoreq. w_i≤1(i＝1,2,3)。

3. The method for designing the blade airfoil of the tidal current energy turbine as set forth in claim 1, wherein the objective function f (X) is in the form of:

f(x)＝(w₁C_L+w₂C_L/C_D+w₃C_D)C_pmax

the objective function is the product of the hydrodynamic performance and the pressure coefficient of the airfoil, where w_i(i 1.. 3) are weights of a lift coefficient, a lift-drag ratio, and a drag coefficient, respectively, and satisfyAnd 0. ltoreq. w_i≤1(i＝1,2,3)。

4. The method for designing the blade airfoil profile of the tidal current energy turbine as set forth in claim 1, wherein the objective function is a combined function g (x) of each hydrodynamic coefficient and pressure coefficient function at a plurality of attack angles as shown in the following formula,

<math> <mrow> <mi>g</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>g</mi> <mrow> <mo>(</mo> <mi>f</mi> <msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <msub> <mi>&alpha;</mi> <mn>1</mn> </msub> </msub> <mo>,</mo> <mi>f</mi> <msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <msub> <mi>&alpha;</mi> <mn>2</mn> </msub> </msub> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mrow> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> <msub> <mi>&alpha;</mi> <mi>v</mi> </msub> </msub> <mo>)</mo> </mrow> </mrow> </math>

wherein alpha is_uThe size of the attack angle of the hydrofoil is the same,the angle of attack is alpha_uThe hydrodynamic performance objective function under the condition, v is the selected number of attack angles in the objective function, the combining function g (x) can comprehensively consider the hydrodynamic performance parameters under any attack angle, and can adopt any type of combining mode, and preferably can adopt a weighted summation method shown as the following formula:

<math> <mrow> <mi>g</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>u</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>v</mi> </munderover> <msub> <mi>&omega;</mi> <mi>u</mi> </msub> <mi>f</mi> <msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <msub> <mi>&alpha;</mi> <mi>u</mi> </msub> </msub> </mrow> </math>

wherein ω is_uIs a weight coefficient and satisfies

5. The method for designing the blade airfoil of the tidal current energy turbine as set forth in claim 1, wherein a lift coefficient, a drag coefficient, a lift-drag ratio and a pressure distribution are calculated by using a FLUENT or CFX or XFOIL numerical simulation program.

6. The method for designing the blade airfoil profile of the tidal current energy water turbine as set forth in claim 1, wherein the fitness function in the second step is in the form of:

<math> <mrow> <mi>h</mi> <mrow> <mo>(</mo> <mi>s</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>s</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>ss</mi> </munderover> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow> </math>

wherein h(s) is the fitness of the s-th design scheme, ss is the number of design schemes in the population, and f (x)_s) Is the objective function of the s-th design.

7. The method for designing the blade airfoil of the tidal current energy turbine as set forth in claim 1, wherein the abscissa and the ordinate of the control point on the airfoil curve of the hydrofoil, and the tangents of the leading edge and the trailing edge of the airfoil are used to fit the airfoil curve of the hydrofoil in the third step.

8. The method for designing the blade airfoil profile of the tidal current energy water turbine as claimed in claim 1, wherein the method for generating the new population in the fifth step is as follows:

according to the fitness of ss different design schemes in a population, eliminating the design schemes with low fitness according to the proportion of 5% -20%, then coding each design scheme in the population by adopting binary numbers, coding all 2m +2n +2 design variables in a certain design scheme into a binary number, and arranging according to the sequence of a leading edge tangent line, an abscissa and an ordinate of an upper surface curve of the wing profile, a trailing edge tangent line and an abscissa and an ordinate of a lower surface curve of the wing profile; the tangent of the front edge, the abscissa and the ordinate of the curve of the upper surface of the airfoil, the abscissa and the ordinate of the curve of the lower surface of the airfoil and the tangent of the rear edge are respectively represented by a binary number. The specific expression is as follows, the first row represents the binary number after conversion, the second row represents the number of the design variables in the coded binary number, there are 2m +2n +2 design variables in total, the 1 st is the leading edge tangent line x₀₀2 nd to 2m +1 th are the abscissa and ordinate of the upper surface curve of the airfoil profile and are in accordance with (x)₁₁,y₁₁)(x₁₂,y₁₂)...(x_1m,y_1m) In the order of (1), the 2m +2 to 2m +2n +1 are the abscissa and the ordinate of the lower surface curve of the airfoil profile and are in accordance with (x)₂₁,y₂₁)(x₂₂,y₂₂)...(x_2m,y_2m) In a sequence of which the last one is a trailing edge tangent x₀₁Numbered 2m +2n +2 in binary numbers,

the better design scheme is kept, and mutation and hybridization operations are carried out according to the proportion of 5% -20% to obtain a new solution, so that the population quantity ss is ensured to be unchanged.