Pneumatic data acquisition method and device, equipment and medium thereof

Abstract

The present application discloses a method for acquiring aerodynamic data and its device, equipment, and medium, the method comprising: acquiring airfoil aerodynamic data corresponding to each operating condition, wherein each operating condition includes a first simulation operating condition under a target Reynolds number, and a test operating condition and a second simulation operating condition under a reference Reynolds number; determining the aerodynamic characteristic parameter matrix and adjoint matrix under each operating condition according to the airfoil aerodynamic data corresponding to each operating condition; determining the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under each operating condition; inverting based on the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number to obtain the target airfoil aerodynamic data under the target Reynolds number. According to the embodiments of the present application, the accuracy of the airfoil aerodynamic data under high Reynolds number conditions can be improved, ensuring accurate evaluation of aerodynamic performance during blade design.

Description

Technical Field

[0001] The present application belongs to the field of wind power generation technology, and in particular relates to a method for acquiring aerodynamic data and a device, equipment, and medium thereof. Background Art

[0002] Airfoil aerodynamic data is the basic input parameter for blade aerodynamic design. Accurate airfoil aerodynamic data is the basis for accurately predicting the aerodynamic efficiency, power generation and load characteristics of the blade. At present, due to the limitations of wind tunnel test conditions and resources, the Reynolds number Re of wind turbine airfoil test conditions is generally low. As the unit capacity of wind turbines continues to increase, the size of wind rotor blades (including span length and chord size) has also increased significantly, making the Reynolds number condition for 100-meter blades exceed 10 million. This Reynolds number condition is difficult to achieve in conventional low-speed wind tunnels.

[0003] In the related art, in order to obtain the aerodynamic data of the airfoil under the high Reynolds number condition, the aerodynamic test data of the airfoil under the low Reynolds number condition is generally used as the basic data, and the aerodynamic coefficient of the airfoil under the same angle of attack is directly linearly superimposed on the basic data due to the change of the Reynolds number to obtain the aerodynamic data of the airfoil under the high Reynolds number condition. However, for the case where the difference in the stall angle of attack of the airfoil under the low Reynolds number condition and the high Reynolds number condition is large, and the Reynolds number changes greatly, the above simple data linear superposition method is very likely to obtain non-physical results, that is, the corrected aerodynamic data of the airfoil under the high Reynolds number condition is not accurate enough, which will affect the accurate evaluation of the aerodynamic performance during blade design. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide an aerodynamic data acquisition method and its device, equipment, and medium, which can improve the accuracy of airfoil aerodynamic data under high Reynolds number conditions and ensure accurate evaluation of aerodynamic performance during blade design.

[0005] In a first aspect, an embodiment of the present application provides an aerodynamic data acquisition method, the method comprising: acquiring airfoil aerodynamic data corresponding to each operating condition, wherein each operating condition includes a first simulation condition under a target Reynolds number, and a test condition and a second simulation condition under a reference Reynolds number; determining an aerodynamic characteristic parameter matrix and an adjoint matrix under each operating condition according to the airfoil aerodynamic data corresponding to each operating condition; determining a target aerodynamic characteristic parameter matrix and a target adjoint matrix under a target Reynolds number according to the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition; performing inversion based on the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number to obtain the target airfoil aerodynamic data under the target Reynolds number.

[0006] In some implementable methods of the first aspect, the airfoil aerodynamic data includes an aerodynamic performance curve, which is used to characterize the changing relationship between the aerodynamic coefficient and the angle of attack. According to the airfoil aerodynamic data corresponding to each operating condition, the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition are determined, including: for each operating condition, obtaining the airfoil characteristic parameter points and their flow characteristics in the aerodynamic performance curve under the operating condition; constructing an aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve; dividing the aerodynamic performance curve into multiple characteristic regions based on the airfoil characteristic parameter points and their flow characteristics; determining the sub-adjoint matrix corresponding to each characteristic region; and merging the sub-adjoint matrices corresponding to multiple characteristic regions to obtain the adjoint matrix.

[0007] In some implementations of the first aspect, the airfoil characteristic parameter points include characteristic parameter points corresponding to the minimum drag coefficient, as well as the linear region end point, critical stall point, stall recovery point, and deep stall point corresponding to the positive angle of attack and the negative angle of attack, respectively.

[0008] In some implementations of the first aspect, the multiple characteristic regions include four characteristic regions with different flow characteristics corresponding to positive angles of attack and negative angles of attack, respectively, the characteristic regions corresponding to the positive angle of attack include a first linear region, a first near-stall region, a first stall region, and a first deep stall region, and the characteristic regions corresponding to the negative angle of attack include a second linear region, a second near-stall region, a second stall region, and a second deep stall region; wherein the flow characteristics of the first linear region and the second linear region are an attached flow state, the flow characteristics of the first near-stall region and the second near-stall region are a state between the development of trailing edge separation and stall separation, the flow characteristics of the first stall region and the second stall region are a state of stall separation and complete separation of the leading edge, and the flow characteristics of the first deep stall region and the second deep stall region are a state of continued development after complete separation of the leading edge.

[0009] In some implementations of the first aspect, determining the sub-adjoint matrix corresponding to each characteristic region includes: establishing the sub-adjoint matrix corresponding to the characteristic region based on the average change rate distribution of the aerodynamic coefficient in each characteristic region.

[0010] In some implementable methods of the first aspect, a target aerodynamic characteristic parameter matrix and a target adjoint matrix under a target Reynolds number are determined based on the aerodynamic characteristic parameter matrix and adjoint matrix under each operating condition, including: adjusting the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition based on the aerodynamic characteristic parameter matrix and adjoint matrix of the first simulation condition and the second simulation condition to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

[0011] In some implementable methods of the first aspect, a target aerodynamic characteristic parameter matrix and a target adjoint matrix under a target Reynolds number are determined based on the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition, including: determining the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of a first simulation condition and a second simulation condition; based on the Reynolds number effect, adjusting the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number.

[0012] In some implementable methods of the first aspect, the Reynolds number effect is determined by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition, including: linearly subtracting the aerodynamic characteristic parameter matrix of the first simulation condition from that of the second simulation condition to obtain a first matrix; linearly subtracting the adjoint matrix of the first simulation condition from that of the second simulation condition to obtain a second matrix; multiplying the first matrix by a first relaxation factor to obtain a third matrix, and multiplying the second matrix by a second relaxation factor to obtain a fourth matrix; wherein the third matrix is ​​used to characterize the degree of influence of the Reynolds number change on the aerodynamic characteristic parameter matrix in the Reynolds number effect, and the fourth matrix is ​​used to characterize the degree of influence of the Reynolds number change on the adjoint matrix in the Reynolds number effect.

[0013] In some implementable methods of the first aspect, based on the Reynolds number effect, the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition are adjusted to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number, including: linearly adding the third matrix to the aerodynamic characteristic parameter matrix of the test condition to obtain the target aerodynamic characteristic parameter matrix; linearly adding the fourth matrix to the adjoint matrix of the test condition to obtain the target adjoint matrix.

[0014] In some implementable methods of the first aspect, a target aerodynamic characteristic parameter matrix and a target adjoint matrix under a target Reynolds number are determined based on the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition, including: linearly or nonlinearly superimposing the aerodynamic characteristic parameter matrix under each operating condition to obtain a target aerodynamic characteristic parameter matrix; linearly or nonlinearly superimposing the adjoint matrix under each operating condition to obtain a target adjoint matrix.

[0015] In a second aspect, an embodiment of the present application provides an aerodynamic data acquisition device, which includes: an acquisition module, used to acquire airfoil aerodynamic data corresponding to each operating condition, wherein each operating condition includes a first simulation condition under a target Reynolds number, and a test condition and a second simulation condition under a reference Reynolds number; a determination module, used to determine the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition based on the airfoil aerodynamic data corresponding to each operating condition; the determination module is also used to determine the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number based on the aerodynamic characteristic parameter matrix and the adjoint matrix under each operating condition; an inversion module, used to perform inversion based on the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number to obtain the target airfoil aerodynamic data under the target Reynolds number.

[0016] In some implementable embodiments of the second aspect, the airfoil aerodynamic data includes an aerodynamic performance curve, which is used to characterize the changing relationship between the aerodynamic coefficient and the angle of attack. The determination module includes: an acquisition unit, which is used to acquire the airfoil characteristic parameter points and their flow characteristics in the aerodynamic performance curve under each working condition; a construction unit, which is used to construct an aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve; a division unit, which is used to divide the aerodynamic performance curve into multiple characteristic regions based on the airfoil characteristic parameter points and their flow characteristics; a determination unit, which is used to determine the sub-companion matrix corresponding to each characteristic region; and a merging unit, which is used to merge the sub-companion matrices corresponding to multiple characteristic regions to obtain a companion matrix.

[0017] In some implementations of the second aspect, the airfoil characteristic parameter points include characteristic parameter points corresponding to the minimum drag coefficient, as well as the end point of the linear region, the critical stall point, the stall recovery point, and the deep stall point corresponding to the positive angle of attack and the negative angle of attack, respectively.

[0018] In some implementations of the second aspect, the multiple characteristic regions include four characteristic regions with different flow characteristics corresponding to positive angles of attack and negative angles of attack, respectively, the characteristic regions corresponding to the positive angle of attack include a first linear region, a first near-stall region, a first stall region, and a first deep stall region, and the characteristic regions corresponding to the negative angle of attack include a second linear region, a second near-stall region, a second stall region, and a second deep stall region; wherein the flow characteristics of the first linear region and the second linear region are an attached flow state, the flow characteristics of the first near-stall region and the second near-stall region are a state between the development of trailing edge separation and stall separation, the flow characteristics of the first stall region and the second stall region are a state of stall separation and complete separation of the leading edge, and the flow characteristics of the first deep stall region and the second deep stall region are a state of continued development after complete separation of the leading edge.

[0019] In some implementations of the second aspect, the determination unit is specifically used to: establish a sub-adjoint matrix corresponding to the characteristic region based on the average change rate distribution of the aerodynamic coefficient in each characteristic region.

[0020] In some implementable embodiments of the second aspect, the determination module is specifically used to: adjust the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition according to the aerodynamic characteristic parameter matrix and adjoint matrix of the first simulation condition and the second simulation condition, so as to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

[0021] In some implementable embodiments of the second aspect, the determination module includes: a determination unit, used to determine the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition; an adjustment unit, used to adjust the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition based on the Reynolds number effect, to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number.

[0022] In some implementable methods of the second aspect, the determination unit is specifically used to: linearly subtract the aerodynamic characteristic parameter matrix of the first simulation condition from that of the second simulation condition to obtain a first matrix; linearly subtract the adjoint matrix of the first simulation condition from that of the second simulation condition to obtain a second matrix; multiply the first matrix by the first relaxation factor to obtain a third matrix, and multiply the second matrix by the second relaxation factor to obtain a fourth matrix; wherein the third matrix is ​​used to characterize the degree of influence of the Reynolds number change on the aerodynamic characteristic parameter matrix in the Reynolds number effect, and the fourth matrix is ​​used to characterize the degree of influence of the Reynolds number change on the adjoint matrix in the Reynolds number effect.

[0023] In some implementations of the second aspect, the adjustment unit is specifically used to: linearly add the third matrix to the aerodynamic characteristic parameter matrix of the test condition to obtain a target aerodynamic characteristic parameter matrix; linearly add the fourth matrix to the companion matrix of the test condition to obtain a target companion matrix.

[0024] In some implementable embodiments of the second aspect, the determination module is specifically used to: linearly superimpose or nonlinearly superimpose the aerodynamic characteristic parameter matrices under various working conditions to obtain a target aerodynamic characteristic parameter matrix; linearly superimpose or nonlinearly superimpose the adjoint matrices under various working conditions to obtain a target adjoint matrix.

[0025] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the steps of the pneumatic data acquisition method of the first aspect are implemented.

[0026] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the steps of the pneumatic data acquisition method of the first aspect are implemented.

[0027] In a fifth aspect, an embodiment of the present application provides a computer program product, which is stored in a non-volatile storage medium and is executed by at least one processor to implement the steps of the pneumatic data acquisition method of the first aspect.

[0028] In a sixth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the pneumatic data acquisition method of the first aspect.

[0029] The present application provides an aerodynamic data acquisition method and its device, equipment, and medium. After acquiring the aerodynamic data of the airfoil corresponding to each working condition, the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are determined according to the aerodynamic data of the airfoil corresponding to each working condition. Since the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are the inversion matrix of the aerodynamic performance curve under the working condition, the aerodynamic coefficient of the airfoil under the working condition can be reflected. The change of the aerodynamic coefficient of the airfoil with the angle of attack under the working condition. In addition, each working condition includes a first simulation working condition under the target Reynolds number and a second simulation working condition under the reference Reynolds number. Through the aerodynamic characteristic parameter matrix and the adjoint matrix under the first simulation working condition and the second simulation working condition, the change of the aerodynamic characteristics of the airfoil caused by the change of the Reynolds number, that is, the Reynolds number effect, can be more accurately reflected. Based on this, according to the aerodynamic characteristic parameter matrix and adjoint matrix under each working condition, the Reynolds number effect can be superimposed on the aerodynamic characteristic parameter matrix and adjoint matrix of the test working condition under the reference Reynolds number, so as to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number, that is, to obtain the inversion matrix of the aerodynamic performance curve under the target Reynolds number. In this way, based on the inversion matrix, the target airfoil aerodynamic data under the target Reynolds number can be accurately established. Compared with the scheme of directly linearly superimposing the aerodynamic coefficient of the airfoil under the same attack angle on the airfoil aerodynamic test data under the lower Reynolds number working condition in the related technology, the non-physical results caused by the existing extrapolation technology can be avoided, so that the target airfoil aerodynamic data obtained is more in line with the physical law of the airfoil changing with the attack angle under the target Reynolds number, and then when the aerodynamic design of the blade is performed through the aerodynamic data of the target airfoil, the aerodynamic performance can be accurately evaluated and the reliability of the aerodynamic design of the blade can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application.

[0031] Figure 1 It is a flowchart of a method for acquiring pneumatic data provided by an embodiment of the present application;

[0032] Figure 2is a flow chart of a method for acquiring pneumatic data provided by another embodiment of the present application;

[0033] Figure 3 is an exemplary schematic diagram of an aerodynamic performance curve corresponding to a lift coefficient provided in an embodiment of the present application;

[0034] Figure 4 is an exemplary schematic diagram of an aerodynamic performance curve corresponding to a drag coefficient provided in an embodiment of the present application;

[0035] Figure 5 is an exemplary schematic diagram of a characteristic area provided by an embodiment of the present application;

[0036] Figure 6 is a flow chart of a method for acquiring pneumatic data provided in yet another embodiment of the present application;

[0037] Figure 7 is a flow chart of a method for acquiring pneumatic data provided in yet another embodiment of the present application;

[0038] Figure 8 is a structural schematic diagram of a pneumatic data acquisition device provided in an embodiment of the present application;

[0039] Fig. 9 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0041] First, the technical terms involved in the technical solutions provided in the embodiments of the present application are introduced:

[0042] Aerodynamic performance curve: refers to the polar coordinate performance curve of the airfoil, which is the characteristic curve of the aerodynamic coefficients (lift coefficient, drag coefficient and pitch moment coefficient) of the airfoil as the angle of attack changes. The physical nature of the polar coordinate performance curve characteristics of the airfoil is determined by the flow characteristics of the airfoil. The aerodynamic data corresponding to the aerodynamic performance curve is the aerodynamic performance data.

[0043] Reynolds number: A dimensionless constant of the flow similarity criterion, defined as the ratio of the inertial force of the fluid to the viscous force. In general, the Reynolds number can be used as a criterion parameter for the flow state of the fluid, and it can be considered that the flow states of fluids with similar Reynolds numbers are similar. Therefore, the Reynolds number corresponding to the aerodynamic data of the basic airfoil used in the aerodynamic design of the blade should be similar to the Reynolds number of the corresponding airfoil when the blade is running.

[0044] Reynolds number effect: Reynolds number effect is also called scale effect, which means the change of aerodynamic characteristics of airfoil caused by the change of Reynolds number. Generally speaking, for relatively low thickness aviation airfoils and wind turbine airfoils, the increase of Reynolds number will increase the slope of linear area of ​​polar coordinate performance curve of airfoil lift coefficient, increase stall angle of attack, increase maximum lift coefficient, and make the drop of lift coefficient in post-stall area more drastic; at the same time, it will reduce the minimum drag coefficient of airfoil and reduce the range of low drag area.

[0045] Flow separation: A flow phenomenon in which the fluid no longer adheres to the surface of an object as it develops along the surface of the object; it is often accompanied by backflow, larger-scale vortex motion, and flow mixing; large-scale flow separation on an airfoil can lead to a decrease in aerodynamic lift, a sharp increase in drag, and stall, which can significantly reduce aerodynamic efficiency.

[0046] Airfoil aerodynamic data is the basic input parameter for blade aerodynamic design. Accurate airfoil aerodynamic data is the basis for accurately predicting the aerodynamic efficiency, power generation and load characteristics of blades. The accuracy of the data requires not only that the airfoil aerodynamic data applied to the blade design must be verified by wind tunnel testing, but also that the test condition-Reynolds number corresponding to the airfoil aerodynamic data must be close to the design operating Reynolds number of the blade, so as to reduce the uncertainty of blade performance caused by the Reynolds number effect and improve the reliability of blade aerodynamic design. At present, due to the limitations of wind tunnel test conditions and resources, the test condition Reynolds number Re of wind turbine airfoils is generally low, usually not higher than 6.0E+06. As the unit capacity of wind turbines continues to increase, the size of wind rotor blades (including span length and chord size) has also increased significantly, making the Reynolds number condition of 100-meter blades exceed 10 million. This Reynolds number condition is difficult to achieve in conventional low-speed wind tunnels.

[0047] In the related art, in order to obtain the aerodynamic data of the airfoil under the high Reynolds number condition, the aerodynamic test data of the airfoil under the low Reynolds number condition is generally used as the basic data, and the influence of the change of the Reynolds number is calculated with the help of numerical tools such as CFD, and the aerodynamic coefficient of the airfoil under the same angle of attack is directly linearly superimposed on the basic data to obtain the aerodynamic data of the airfoil under the high Reynolds number condition. This method is also relatively accurate for the case where the span of the Reynolds number is not large. However, for the case where the difference in the stall angle of the airfoil between the low Reynolds number condition and the high Reynolds number condition is large, and the Reynolds number changes greatly, the Reynolds number effect is more obvious. The above simple data linear superposition method is very easy to obtain non-physical results, such as the linear region of the lift curve ends prematurely or multiple stall phenomena, that is, the corrected aerodynamic data of the airfoil under the high Reynolds number condition is not accurate enough, which will affect the accurate evaluation of the aerodynamic performance during blade design.

[0048] In order to improve the problems in the related art, the embodiment of the present application provides an aerodynamic data acquisition method. After obtaining the aerodynamic data of the airfoil corresponding to each working condition, the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are determined according to the aerodynamic data of the airfoil corresponding to each working condition. Since the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are the inversion matrix of the aerodynamic performance curve under the working condition, the change of the aerodynamic coefficient of the airfoil with the angle of attack under the working condition can be reflected. In addition, each working condition includes a first simulation working condition under the target Reynolds number and a second simulation working condition under the reference Reynolds number. Through the aerodynamic characteristic parameter matrix and the adjoint matrix under the first simulation working condition and the second simulation working condition, the change of the aerodynamic characteristics of the airfoil caused by the change of the Reynolds number, that is, the Reynolds number effect, can be more accurately reflected. Based on this, according to the aerodynamic characteristic parameter matrix and adjoint matrix under each working condition, the Reynolds number effect can be superimposed on the aerodynamic characteristic parameter matrix and adjoint matrix of the test working condition under the reference Reynolds number, so as to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number, that is, to obtain the inversion matrix of the aerodynamic performance curve under the target Reynolds number. In this way, based on the inversion matrix, the target airfoil aerodynamic data under the target Reynolds number can be accurately established. Compared with the scheme of directly linearly superimposing the aerodynamic coefficient of the airfoil under the same attack angle on the airfoil aerodynamic test data under the lower Reynolds number working condition in the related technology, the non-physical results caused by the existing extrapolation technology can be avoided, so that the target airfoil aerodynamic data obtained is more in line with the physical law of the airfoil changing with the attack angle under the target Reynolds number, and then when the aerodynamic design of the blade is performed through the aerodynamic data of the target airfoil, the aerodynamic performance can be accurately evaluated and the reliability of the aerodynamic design of the blade can be improved.

[0049] The pneumatic data acquisition method provided in the embodiment of the present application is described in detail below through specific embodiments and application scenarios in conjunction with the accompanying drawings.

[0050] The first aspect of the present application provides a pneumatic data acquisition method, which can be applied to electronic equipment. It should be noted that the above-mentioned execution subject does not constitute a limitation on the present application.

[0051] Figure 1 The flowchart of the pneumatic data acquisition method provided in one embodiment of the present application is shown in FIG. Figure 1 As shown, the pneumatic data acquisition method may include steps 110 to 140.

[0052] Step 110, obtaining airfoil aerodynamic data corresponding to each working condition.

[0053] Among them, each working condition includes a first simulation working condition under a target Reynolds number, and a test working condition and a second simulation working condition under a reference Reynolds number.

[0054] Step 120, determining the aerodynamic characteristic parameter matrix and adjoint matrix under each operating condition according to the airfoil aerodynamic data corresponding to each operating condition.

[0055] Step 130, determining a target aerodynamic characteristic parameter matrix and a target adjoint matrix at a target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under various operating conditions.

[0056] Step 140 , performing inversion based on the target aerodynamic characteristic parameter matrix and the target adjoint matrix at the target Reynolds number to obtain the target airfoil aerodynamic data at the target Reynolds number.

[0057] The aerodynamic data acquisition method provided in the embodiment of the present application, after obtaining the aerodynamic data of the airfoil corresponding to each working condition, determines the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition according to the aerodynamic data of the airfoil corresponding to each working condition. Since the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are the inversion matrix of the aerodynamic performance curve under the working condition, it can reflect the change of the aerodynamic coefficient of the airfoil under the working condition with the angle of attack. In addition, each working condition includes the first simulation working condition under the target Reynolds number and the second simulation working condition under the reference Reynolds number. Through the aerodynamic characteristic parameter matrix and the adjoint matrix under the first simulation working condition and the second simulation working condition, the change of the aerodynamic characteristics of the airfoil caused by the change of the Reynolds number can be more accurately reflected, that is, the Reynolds number effect. Based on this, according to the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition, the Reynolds number effect can be superimposed on the aerodynamic characteristic parameter matrix and the adjoint matrix of the test working condition under the reference Reynolds number, so as to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number, that is, to obtain the inversion matrix of the aerodynamic performance curve under the target Reynolds number. In this way, by performing inversion based on the inversion matrix, the target airfoil aerodynamic data under the target Reynolds number can be accurately established. Compared with the scheme of directly linearly superimposing the change of the airfoil aerodynamic coefficient under the same angle of attack on the airfoil aerodynamic test data under lower Reynolds number conditions in the related technology, the non-physical results caused by the existing extrapolation technology can be avoided, so that the obtained target airfoil aerodynamic data is more in line with the physical law of the change of the airfoil with the angle of attack under the target Reynolds number. Then, when the aerodynamic design of the blade is performed through the aerodynamic data of the target airfoil, the aerodynamic performance can be accurately evaluated, and the reliability of the aerodynamic design of the blade can be improved.

[0058] The specific implementation of the above steps will be described in detail below in conjunction with specific embodiments.

[0059] Involving step 110, aerodynamic data of the airfoil corresponding to each working condition is obtained.

[0060] Specifically, the airfoil aerodynamic data is used to characterize the changing relationship between the aerodynamic coefficients and the angle of attack AOA. The aerodynamic coefficients include the lift coefficient cl, the drag coefficient cd and the moment coefficient cm. The angle of attack is measured in degrees. The lift coefficient, drag coefficient and moment coefficient are all dimensionless aerodynamic coefficients. The angle of attack range of the airfoil aerodynamic data must cover the airfoil stall zone in the positive and negative directions, and the angle of attack in the rear stall zone must be greater than the critical stall angle of attack by more than 3 degrees.

[0061] The aerodynamic data of the airfoil corresponding to the first simulation condition and the second simulation condition are calculated for the same airfoil using CFD tools or simplified physical model tools, and the aerodynamic data of the airfoil corresponding to the test condition are aerodynamic data obtained through wind tunnel testing under the base Reynolds number (Re_base).

[0062] The baseline Reynolds number is a lower Reynolds number, the target Reynolds number is a high Reynolds number, the baseline Reynolds number is less than the target Reynolds number, and both the baseline Reynolds number and the target Reynolds number can be specifically set according to actual needs, for example, the baseline Reynolds number is set to 6 million, 8 million, etc., and the target Reynolds number is set to 10 million, etc. This application does not make specific limitations on this.

[0063] It should be noted that the reference Reynolds number may include at least one.

[0064] Exemplarily, the target Reynolds number is 10 million, and the benchmark Reynolds numbers may include 4 million and 6 million. Therefore, the present application can establish target airfoil aerodynamic data at 10 million through the airfoil aerodynamic data corresponding to the test condition and the second simulation condition at 4 million, the test condition and the second simulation condition at 6 million, and the first simulation condition at 10 million.

[0065] In step 120, based on the airfoil aerodynamic data corresponding to each working condition, the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are determined.

[0066] In some embodiments of the present application, the airfoil aerodynamic data includes an aerodynamic performance curve, which is used to characterize the changing relationship between the aerodynamic coefficient and the angle of attack, and the aerodynamic characteristic parameter matrix is ​​constructed from the airfoil characteristic parameter points in the aerodynamic performance curve.

[0067] In some embodiments of the present application, in order to construct the aerodynamic characteristic parameter matrix and adjoint matrix under each working condition, Figure 2 is a flow chart of a method for acquiring pneumatic data provided by another embodiment of the present application. The above step 120 may include Figure 2 Steps 210 to 250 are shown.

[0068] Step 210, for each working condition, obtaining airfoil characteristic parameter points and flow characteristics in the aerodynamic performance curve under the working condition;

[0069] Step 220, constructing an aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve;

[0070] Step 230, dividing the aerodynamic performance curve into a plurality of characteristic regions based on the airfoil characteristic parameter points and flow characteristics thereof;

[0071] Step 240, determining the sub-adjoint matrix corresponding to each feature region;

[0072] Step 250: merge the sub-adjoint matrices corresponding to the multiple feature regions to obtain an adjoint matrix.

[0073] Specifically, the airfoil characteristic parameter points may include characteristic parameter points corresponding to the minimum drag coefficient, and linear region end points, critical stall points, stall recovery points, and deep stall points corresponding to positive angles of attack and negative angles of attack, respectively.

[0074] It should be noted that the aerodynamic coefficients include the lift coefficient, the drag coefficient and the moment coefficient. Therefore, each aerodynamic coefficient corresponds to an aerodynamic performance curve. There are three aerodynamic performance curves, but the characteristic parameter points in the three aerodynamic performance curves have the same horizontal coordinate, that is, they correspond to the same angle of attack.

[0075] For example, Figure 3 is the aerodynamic performance curve corresponding to the lift coefficient, the horizontal axis is the angle of attack, and the vertical axis is the lift coefficient; Figure 4 is the aerodynamic performance curve corresponding to the drag coefficient, the horizontal axis is the angle of attack, and the vertical axis is the drag coefficient; Figure 3 and Figure 4 In the figure, the dotted line is the actual data line, and the solid line is the line between the airfoil characteristic parameter points. Figure 3 and Figure 4 The airfoil characteristic parameter points shown may include the following eight: P0 is the characteristic parameter point at the angle of attack corresponding to the minimum drag coefficient of the airfoil; PA1 is the point where the linear region of the lift curve ends at the positive angle of attack in the linear region (in the direction of increasing the angle of attack from the P0 point); PN1 is the point where the linear region of the lift curve ends at the negative angle of attack in the linear region (in the direction of decreasing the angle of attack from the P0 point); PA2 is the critical stall point at the positive angle of attack in the linear region (in the direction of increasing the angle of attack from the P0 point); PN2 is the critical stall point at the negative angle of attack in the linear region (in the direction of decreasing the angle of attack from the P0 point); =PA3 is the stall recovery point at the positive angle of attack in the linear zone (in the direction of increasing the angle of attack from the P0 point), that is, the critical inflection point of the lift curve after the stall; PN3 is the stall recovery point at the negative angle of attack in the linear zone (in the direction of decreasing the angle of attack from the P0 point), that is, the critical inflection point of the lift curve after the stall; PA4 is the deep stall point at the positive angle of attack in the linear zone (in the direction of increasing the angle of attack from the P0 point); PN4 is the deep stall point at the negative angle of attack in the linear zone (in the direction of decreasing the angle of attack from the P0 point).

[0076] It should be noted that the above-mentioned 8 airfoil characteristic parameter points are used as an example and do not constitute a specific limitation on the present application. The present application can define any number of airfoil characteristic parameter points such as 6, 9 or 10, and the present application does not specifically limit the number of airfoil characteristic parameter points.

[0077] Depend on Figure 3 , Figure 4 It can be seen that there are 8 airfoil characteristic parameter points in the aerodynamic performance curves corresponding to the lift coefficient and the drag coefficient, and the airfoil characteristic parameter points in the two aerodynamic performance curves correspond to the same horizontal coordinate, that is, to the same angle of attack.

[0078] As a specific example, the form of the aerodynamic characteristic parameter matrix A can be shown as formula (1):

[0079] A=[AOA(Pi),cl(Pi), cd(Pi), cm(Pi)] (1)

[0080] Among them, Pi is the characteristic parameter point of the airfoil, AOA(Pi) is the angle of attack of Pi, cl(Pi) is the lift coefficient of Pi, cd(Pi) is the drag coefficient of Pi, and cm(Pi) is the moment coefficient of Pi.

[0081] Based on the above formula (1), the aerodynamic characteristic parameter matrix of each working condition can be constructed, specifically including: the aerodynamic characteristic parameter matrix A_test_Re_base under the test condition at the reference Reynolds number, the aerodynamic characteristic parameter matrix A_simu_Re_obj under the first simulation condition, and the aerodynamic characteristic parameter matrix A_simu_Re_base under the second simulation condition.

[0082] In some embodiments of the present application, in order to improve the accuracy of the aerodynamic performance represented by the characteristic parameter matrix, the present application may also increase the dimension of the characteristic parameter matrix.

[0083] In some embodiments of the present application, multiple characteristic regions may include four characteristic regions with different flow characteristics corresponding to positive angles of attack and negative angles of attack, respectively. The characteristic regions corresponding to the positive angle of attack include a first linear region, a first near-stall region, a first stall region, and a first deep stall region; the characteristic regions corresponding to the negative angle of attack include a second linear region, a second near-stall region, a second stall region, and a second deep stall region.

[0084] Among them, the flow characteristics of the first linear zone and the second linear zone are the attached flow state, the flow characteristics of the first near-stall zone and the second near-stall zone are the state between the trailing edge separation and the stall separation, the flow characteristics of the first stall zone and the second stall zone are the state of stall separation and complete separation of the leading edge, and the flow characteristics of the first deep stall zone and the second deep stall zone are the continued development state after the leading edge is completely separated.

[0085] In some examples, Figure 3 For example, in Figure 3 After dividing the aerodynamic performance curve shown in Figure 58 characteristic regions are shown as follows: the first linear region RA1, defined by points P0-PA1, is a linear region at a positive angle of attack, and the corresponding flow is an attachment flow; the first near-stall region RA2, defined by points PA1-PA2, is a near-stall region at a positive angle of attack, and the corresponding flow is generally a state between the development of trailing edge separation and stall separation; the first stall region RA3, defined by points PA2-PA3, is a linear region at a positive angle of attack, and the corresponding flow is generally a state of stall separation and complete separation of the leading edge; the first deep stall region RA4, defined by points PA3-PA4, is a linear region at a positive angle of attack, and the corresponding flow is generally a state of continued development after complete separation of the leading edge (which may include local separation and reattachment); similarly, taking point P0 as the reference point, the angle of attack The reduced directional characteristic curve can also be divided into the above four characteristic areas: the second linear zone RN1, defined by the points P0-PN1, is a linear zone at a negative angle of attack, and the corresponding flow is an attachment flow; the second near-stall zone RN2, defined by the points PN1-PN2, is a near-stall zone at a negative angle of attack, and the corresponding flow is generally a state between the development of trailing edge separation and stall separation; the second stall zone RN3, defined by the points PN2-PN3, is a linear zone at a negative angle of attack, and the corresponding flow is generally a state of stall separation and complete separation of the leading edge; the second deep stall zone RN4, defined by the points PN3-PN4, is a linear zone at a negative angle of attack, and the corresponding flow is generally a state of continued development after complete separation of the leading edge (which may include local separation and reattachment).

[0086] In some embodiments of the present application, the above step 240 of determining the sub-adjoint matrix corresponding to each characteristic region may include: establishing the sub-adjoint matrix corresponding to the characteristic region based on the average change rate distribution of the aerodynamic coefficient in each characteristic region.

[0087] As a specific example, a sub-adjoint matrix BR can be established in each feature area. Taking the RA1 area as an example, the angle of attack range of the area is divided into i parts, and the angle of attack coordinate vector of j=i+1 dimension is obtained. Then, the sub-adjoint matrix BRA1 of the feature area RA1 is established based on the average change rate distribution of the lift coefficient, drag coefficient, and moment coefficient at the angle of attack coordinate of i+1 dimensions as the angle of attack changes. The form of the sub-adjoint matrix BRA1 can be shown as formula (2):

[0088] BRA1=[AOA_RA1(j),dcl / dAOA(j),dcd / dAOA(j),dcd / dAOA(j),dcm / dAOA(j)](2)

[0089] Among them, AOA_RA1(j) is the distribution of angle of attack in the j dimension in the RA1 area, dcl / dAOA(j) is the average change rate distribution of the lift coefficient with the change of angle of attack in the j dimension in the RA1 area, dcd / dAOA(j) is the average change rate distribution of the drag coefficient with the change of angle of attack in the j dimension in the RA1 area, and dcm / dAOA(j) is the average change rate distribution of the moment coefficient with the change of angle of attack in the j dimension in the RA1 area.

[0090] By merging the sub-companion matrices of the above characteristic regions, the (aerodynamic performance) companion matrix of the airfoil under a specific working condition can be obtained, which may specifically include: the aerodynamic characteristic parameter matrix BR_test_Re_base under the test condition at the benchmark Reynolds number, the aerodynamic characteristic parameter matrix BR_simu_Re_obj under the first simulation condition, and the aerodynamic characteristic parameter matrix BR_simu_Re_base under the second simulation condition.

[0091] In step 130, a target aerodynamic characteristic parameter matrix and a target adjoint matrix under a target Reynolds number are determined according to the aerodynamic characteristic parameter matrix and the adjoint matrix under various working conditions.

[0092] Specifically, the electronic device can adjust the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition according to the aerodynamic characteristic parameter matrix and adjoint matrix of the first simulation condition and the second simulation condition to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

[0093] In some embodiments of the present application, Figure 6 is a flow chart of a method for acquiring pneumatic data provided by another embodiment of the present application. The above step 130 may include Figure 6 Step 610 and step 620 are shown.

[0094] Step 610, determining the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition;

[0095] Step 620, based on the Reynolds number effect, the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition are adjusted to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number.

[0096] Specifically, the electronic device can linearly superimpose the Reynolds number effect, or nonlinearly superimpose it on the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

[0097] In some embodiments of the present application, Figure 7 is a flow chart of a method for acquiring pneumatic data provided by another embodiment of the present application. The above step 610 may include Figure 7 Steps 710 - 730 are shown.

[0098] Step 710, linearly subtracting the aerodynamic characteristic parameter matrices of the first simulation condition and the second simulation condition to obtain a first matrix;

[0099] Step 720, linearly subtract the adjoint matrices of the first simulation condition and the second simulation condition to obtain a second matrix;

[0100] Step 730: multiply the first matrix by the first relaxation factor to obtain a third matrix, and multiply the second matrix by the second relaxation factor to obtain a fourth matrix.

[0101] Among them, the third matrix is ​​used to characterize the influence of the Reynolds number change on the aerodynamic characteristic parameter matrix in the Reynolds number effect, and the third matrix is ​​used to characterize the influence of the Reynolds number change on the adjoint matrix in the Reynolds number effect.

[0102] In some embodiments of the present application, the above step 520 may specifically include the following steps:

[0103] Linearly add the third matrix to the aerodynamic characteristic parameter matrix of the test condition to obtain a target aerodynamic characteristic parameter matrix;

[0104] The fourth matrix is ​​linearly added to the adjoint matrix of the test condition to obtain the target adjoint matrix.

[0105] In some embodiments of the present application, the above step 130 determines the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and the adjoint matrix under various working conditions, and may specifically include the following steps:

[0106] Perform linear or nonlinear superposition on the aerodynamic characteristic parameter matrices under various working conditions to obtain a target aerodynamic characteristic parameter matrix;

[0107] The adjoint matrices under various working conditions are linearly or nonlinearly superimposed to obtain the target adjoint matrix.

[0108] Specifically, step 130 may use the following formula (3) to determine the target aerodynamic characteristic parameter matrix A_testCor_Re_obj, and use the following formula (4) to determine the target adjoint matrix:

[0109] A_testCor_Re_obj=A_test_Re_base+k(A_simu_Re_obj-A_simu_Re_base) (3)

[0111] BR_testCor_Re_obj=BR_test_Re_base+m(BR_simu_Re_obj-BR_simu_Re_base)(4)

[0112] Wherein, k is the first relaxation factor and m is the second relaxation factor.

[0113] It should be noted that when the precision and accuracy of the numerical simulation calculation tool for the airfoil aerodynamic performance is high, the values ​​of k and m are 1. When the accuracy is reduced, the values ​​of k and m need to be reduced.

[0114] Involving step 140, inversion is performed based on the target aerodynamic characteristic parameter matrix and the target adjoint matrix at the target Reynolds number to obtain the target airfoil aerodynamic data at the target Reynolds number.

[0115] Specifically, according to the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number, the aerodynamic data in each characteristic region of the airfoil can be inverted and the aerodynamic data in each characteristic region can be combined to obtain the aerodynamic data of the target airfoil.

[0116] For example, taking the inversion of the lift curve in the RA1 characteristic region as an example, RA1 is divided into i parts, and j=i+1 dimensions are obtained. The lift coefficient cl(n) in this region can be determined by formulas (5) and (6):

[0117] cl(n)=cl(n-1)+ dcl / dAOA(n)*(AOA(n)- AOA(n-1)) (5)

[0118] cl(0)=cl(P0) (6)

[0119] Wherein, n=1…,j, cl(n) is the lift coefficient in the nth dimension, cl(n-1) is the lift coefficient in the n-1th dimension, dcl / dAOA(n) is the local average change rate distribution of the lift coefficient in the nth dimension, AOA(n) is the angle of attack in the nth dimension, AOA(n-1) is the angle of attack in the n-1th dimension, cl(0) is the lift coefficient when the angle of attack is zero, and cl(P0) is the horizontal coordinate angle of attack of the characteristic parameter point P0.

[0120] The electronic equipment uses the same method to obtain the values ​​of the drag coefficient and torque coefficient in the RA1 characteristic area. By combining the various characteristic areas, the complete aerodynamic data at the target Reynolds number can be obtained.

[0121] It is understandable that the pneumatic data acquisition method provided in the embodiment of the present application can be executed by an electronic device or a control module in a pneumatic data acquisition device for executing the pneumatic data acquisition method. The pneumatic data acquisition device is described in detail below.

[0122] Figure 8 Schematic diagram of the structure of a pneumatic data acquisition device provided in an embodiment of the present application. Figure 8 As shown, the pneumatic data acquisition device 800 may include: an acquisition module 810 , a determination module 820 and an inversion module 830 .

[0123] Among them, the acquisition module 810 is used to obtain the airfoil aerodynamic data corresponding to each working condition, wherein each working condition includes a first simulation working condition under a target Reynolds number, and a test working condition and a second simulation working condition under a reference Reynolds number; the determination module 820 is used to determine the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition according to the airfoil aerodynamic data corresponding to each working condition; the determination module 820 is also used to determine the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition; the inversion module 830 is used to perform inversion based on the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number to obtain the target airfoil aerodynamic data under the target Reynolds number.

[0124] The aerodynamic data acquisition device provided by the present application, after acquiring the aerodynamic data of the airfoil corresponding to each working condition, determines the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition according to the aerodynamic data of the airfoil corresponding to each working condition. Since the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are the inversion matrix of the aerodynamic performance curve under the working condition, the aerodynamic coefficient of the airfoil under the working condition can be reflected with the change of the angle of attack. In addition, each working condition includes the first simulation working condition under the target Reynolds number and the second simulation working condition under the reference Reynolds number. Through the aerodynamic characteristic parameter matrix and the adjoint matrix under the first simulation working condition and the second simulation working condition, the change of the aerodynamic characteristics of the airfoil caused by the change of the Reynolds number can be more accurately reflected, that is, the Reynolds number effect. Based on this, according to the aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition, the Reynolds number effect can be superimposed on the aerodynamic characteristic parameter matrix and the adjoint matrix of the test working condition under the reference Reynolds number, so as to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number, that is, to obtain the inversion matrix of the aerodynamic performance curve under the target Reynolds number. In this way, by performing inversion based on the inversion matrix, the target airfoil aerodynamic data under the target Reynolds number can be accurately established. Compared with the scheme of directly linearly superimposing the change of the airfoil aerodynamic coefficient under the same angle of attack on the airfoil aerodynamic test data under lower Reynolds number conditions in the related technology, the non-physical results caused by the existing extrapolation technology can be avoided, so that the obtained target airfoil aerodynamic data is more in line with the physical law of the change of the airfoil with the angle of attack under the target Reynolds number. Then, when the aerodynamic design of the blade is performed through the aerodynamic data of the target airfoil, the aerodynamic performance can be accurately evaluated, and the reliability of the aerodynamic design of the blade can be improved.

[0125] In some embodiments of the present application, the airfoil aerodynamic data includes an aerodynamic performance curve, which is used to characterize the changing relationship between the aerodynamic coefficient and the angle of attack. The determination module 820 includes: an acquisition unit, which is used to acquire the airfoil characteristic parameter points and their flow characteristics in the aerodynamic performance curve under each working condition; a construction unit, which is used to construct an aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve; a division unit, which is used to divide the aerodynamic performance curve into multiple characteristic regions based on the airfoil characteristic parameter points and their flow characteristics; a determination unit, which is used to determine the sub-companion matrix corresponding to each characteristic region; and a merging unit, which is used to merge the sub-companion matrices corresponding to multiple characteristic regions to obtain a companion matrix.

[0126] In some embodiments of the present application, the airfoil characteristic parameter points include characteristic parameter points corresponding to the minimum drag coefficient, as well as the linear region end point, critical stall point, stall recovery point, and deep stall point corresponding to the positive angle of attack and the negative angle of attack, respectively.

[0127] In some embodiments of the present application, the plurality of characteristic regions include four characteristic regions with different flow characteristics corresponding to positive angles of attack and negative angles of attack, respectively. The characteristic regions corresponding to the positive angle of attack include a first linear region, a first near-stall region, a first stall region, and a first deep stall region. The characteristic regions corresponding to the negative angle of attack include a second linear region, a second near-stall region, a second stall region, and a second deep stall region. The flow characteristics of the first linear region and the second linear region are an attached flow state, the flow characteristics of the first near-stall region and the second near-stall region are a state between the development of trailing edge separation and stall separation, the flow characteristics of the first stall region and the second stall region are a state of stall separation and complete separation of the leading edge, and the flow characteristics of the first deep stall region and the second deep stall region are a state of continued development after complete separation of the leading edge.

[0128] In some embodiments of the present application, the determination unit is specifically used to: establish a sub-adjoint matrix corresponding to the characteristic region based on the average change rate distribution of the aerodynamic coefficient in each characteristic region.

[0129] In some embodiments of the present application, the determination module 820 is specifically used to adjust the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition according to the aerodynamic characteristic parameter matrix and adjoint matrix of the first simulation condition and the second simulation condition to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

[0130] In some embodiments of the present application, the determination module 820 includes: a determination unit, used to determine the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition; an adjustment unit, used to adjust the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition based on the Reynolds number effect, to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number.

[0131] In some embodiments of the present application, the determination unit is specifically used to: linearly subtract the aerodynamic characteristic parameter matrices of the first simulation condition from those of the second simulation condition to obtain a first matrix; linearly subtract the adjoint matrices of the first simulation condition from those of the second simulation condition to obtain a second matrix; multiply the first matrix by the first relaxation factor to obtain a third matrix, and multiply the second matrix by the second relaxation factor to obtain a fourth matrix; wherein the third matrix is ​​used to characterize the degree of influence of the Reynolds number change on the aerodynamic characteristic parameter matrix in the Reynolds number effect, and the fourth matrix is ​​used to characterize the degree of influence of the Reynolds number change on the adjoint matrix in the Reynolds number effect.

[0132] In some embodiments of the present application, the adjustment unit is specifically used to: linearly add the third matrix to the aerodynamic characteristic parameter matrix of the test condition to obtain a target aerodynamic characteristic parameter matrix; linearly add the fourth matrix to the companion matrix of the test condition to obtain a target companion matrix.

[0133] In some embodiments of the present application, the determination module 820 is specifically used to: linearly superimpose or nonlinearly superimpose the aerodynamic characteristic parameter matrix under each working condition to obtain a target aerodynamic characteristic parameter matrix; linearly superimpose or nonlinearly superimpose the adjoint matrix under each working condition to obtain a target adjoint matrix.

[0134] The pneumatic data acquisition device provided in the embodiment of the present application can achieve Figure 1-7 The various processes implemented by the electronic device in the method embodiment can achieve the same technical effect, and to avoid repetition, they will not be described here.

[0135] Fig. 9 It is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0136] like Fig. 9 As shown, the electronic device 900 in this embodiment may include a processor 901 and a memory 902 storing computer program instructions.

[0137] Specifically, the processor 901 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0138] The memory 902 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 902 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 902 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 902 may be inside or outside the integrated gateway disaster recovery system or device. In a specific embodiment, the memory 902 is a non-volatile solid-state memory. The memory may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium system, a device, an optical storage medium system, a device, a flash memory system, a device, an electrical, optical, or other physical / tangible memory storage system, a device. Therefore, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory systems, devices) having software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to the embodiments of the present application.

[0139] The processor 901 implements any one of the pneumatic data acquisition methods in the above embodiments by reading and executing computer program instructions stored in the memory 902 .

[0140] In one example, the electronic device 900 may further include a communication interface 903 and a bus 910. Fig. 9 As shown, the processor 901, the memory 902, and the communication interface 903 are connected via a bus 910 and communicate with each other.

[0141] The communication interface 903 is mainly used to implement communication between various modules, devices, controllers and / or systems and equipment in the embodiments of the present application.

[0142] Bus 910 includes hardware, software or both, and the parts of online data flow billing system and equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 910 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0143] The electronic device provided in the embodiment of the present application can realize Figure 1-7 The various processes implemented by the electronic device in the method embodiment can achieve the same technical effect, and to avoid repetition, they will not be described here.

[0144] In combination with the pneumatic data acquisition method in the above embodiment, the present application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, the steps of any one of the pneumatic data acquisition methods in the above embodiment are implemented.

[0145] In combination with the pneumatic data acquisition method in the above embodiment, the present application embodiment can provide a computer program product for implementation. The (computer) program product is stored in a non-volatile storage medium, and when the program product is executed by at least one processor, the steps of any one of the pneumatic data acquisition methods in the above embodiment are implemented.

[0146] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned pneumatic data acquisition method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0147] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0148] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0149] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), appropriate firmware, plug-in, function card, etc. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier. "Machine-readable medium" may include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory systems, devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0150] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0151] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0152] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and controller described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for acquiring pneumatic data, It is characterized in that The method comprises: Acquire airfoil aerodynamic data corresponding to each operating condition, wherein each operating condition includes a first simulation operating condition at a target Reynolds number, and a test operating condition and a second simulation operating condition at a reference Reynolds number; Determine the aerodynamic characteristic parameter matrix and adjoint matrix under each of the working conditions according to the airfoil aerodynamic data corresponding to each of the working conditions; Determine the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under the various working conditions; Inversion is performed based on a target aerodynamic characteristic parameter matrix and a target adjoint matrix at the target Reynolds number to obtain a target airfoil aerodynamic data at the target Reynolds number; The airfoil aerodynamic data includes an aerodynamic performance curve, and the aerodynamic performance curve is used to characterize the relationship between the aerodynamic coefficient and the angle of attack. The aerodynamic characteristic parameter matrix and the adjoint matrix under each working condition are determined according to the airfoil aerodynamic data corresponding to each working condition, including: For each working condition, obtaining airfoil characteristic parameter points and flow characteristics in the aerodynamic performance curve under the working condition; Constructing the aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve; Based on the characteristic parameter points of the airfoil and the flow characteristics thereof, the aerodynamic performance curve is divided into a plurality of characteristic regions; Determine a sub-adjoint matrix corresponding to each of the feature regions; The sub-adjoint matrices corresponding to the plurality of feature regions are combined to obtain the adjoint matrix.

2. The method according to claim 1, It is characterized in that The airfoil characteristic parameter points include characteristic parameter points corresponding to the minimum drag coefficient, and linear region end points, critical stall points, stall recovery points, and deep stall points corresponding to positive angle of attack and negative angle of attack, respectively.

3. The method according to claim 1, It is characterized in that The multiple characteristic regions include four characteristic regions with different flow characteristics corresponding to positive angles of attack and negative angles of attack, respectively, wherein the characteristic regions corresponding to the positive angle of attack include a first linear region, a first near-stall region, a first stall region, and a first deep stall region, and the characteristic regions corresponding to the negative angle of attack include a second linear region, a second near-stall region, a second stall region, and a second deep stall region; Among them, the flow characteristics of the first linear zone and the second linear zone are an attached flow state, the flow characteristics of the first near-stall zone and the second near-stall zone are a state between trailing edge separation and stall separation, the flow characteristics of the first stall zone and the second stall zone are a state of stall separation and complete separation of the leading edge, and the flow characteristics of the first deep stall zone and the second deep stall zone are a state of continued development after complete separation of the leading edge.

4. The method according to claim 1, It is characterized in that The determining of the sub-adjoint matrix corresponding to each of the feature regions comprises: Based on the average change rate distribution of the aerodynamic coefficient in each characteristic region, a sub-adjoint matrix corresponding to the characteristic region is established.

5. The method according to claim 1, It is characterized in that Determining the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under the various working conditions includes: According to the aerodynamic characteristic parameter matrix and adjoint matrix of the first simulation condition and the second simulation condition, the aerodynamic characteristic parameter matrix and adjoint matrix of the test condition are adjusted to obtain the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number.

6. The method according to claim 1 or 5, It is characterized in that Determining the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under the various working conditions includes: Determine the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition; Based on the Reynolds number effect, the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition are adjusted to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number.

7. The method according to claim 6, It is characterized in that The determining of the Reynolds number effect by comparing the aerodynamic characteristic parameter matrix and the adjoint matrix of the first simulation condition and the second simulation condition comprises: Linearly subtract the aerodynamic characteristic parameter matrix of the first simulation condition from the aerodynamic characteristic parameter matrix of the second simulation condition to obtain a first matrix; Linearly subtract the adjoint matrices of the first simulation condition and the second simulation condition to obtain a second matrix; Multiplying the first matrix by a first relaxation factor to obtain a third matrix, and multiplying the second matrix by a second relaxation factor to obtain a fourth matrix; The third matrix is ​​used to characterize the influence of the Reynolds number change on the aerodynamic characteristic parameter matrix in the Reynolds number effect, and the fourth matrix is ​​used to characterize the influence of the Reynolds number change on the adjoint matrix in the Reynolds number effect.

8. The method according to claim 7, It is characterized in that The step of adjusting the aerodynamic characteristic parameter matrix and the adjoint matrix of the test condition based on the Reynolds number effect to obtain the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number includes: Linearly adding the third matrix to the aerodynamic characteristic parameter matrix of the test condition to obtain the target aerodynamic characteristic parameter matrix; The fourth matrix is ​​linearly added to the adjoint matrix of the test condition to obtain the target adjoint matrix.

9. The method according to claim 1, It is characterized in that Determining the target aerodynamic characteristic parameter matrix and target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and adjoint matrix under the various working conditions includes: Performing linear or nonlinear superposition on the aerodynamic characteristic parameter matrices under the various working conditions to obtain the target aerodynamic characteristic parameter matrix; The adjoint matrices under the various working conditions are linearly superimposed or nonlinearly superimposed to obtain the target adjoint matrix.

10. A pneumatic data acquisition device, It is characterized in that The device comprises: An acquisition module, used to acquire airfoil aerodynamic data corresponding to each operating condition, wherein each operating condition includes a first simulation operating condition under a target Reynolds number, and a test operating condition and a second simulation operating condition under a reference Reynolds number; A determination module, used to determine the aerodynamic characteristic parameter matrix and adjoint matrix under each working condition according to the airfoil aerodynamic data corresponding to each working condition; The determination module is further used to determine the target aerodynamic characteristic parameter matrix and the target adjoint matrix under the target Reynolds number according to the aerodynamic characteristic parameter matrix and the adjoint matrix under the various working conditions; An inversion module, used for performing inversion based on a target aerodynamic characteristic parameter matrix and a target adjoint matrix at the target Reynolds number to obtain aerodynamic data of a target airfoil at the target Reynolds number; The determining module is further specifically used for: For each working condition, obtaining airfoil characteristic parameter points and flow characteristics in the aerodynamic performance curve under the working condition; Constructing the aerodynamic characteristic parameter matrix based on the airfoil characteristic parameter points in the aerodynamic performance curve; Based on the characteristic parameter points of the airfoil and the flow characteristics thereof, the aerodynamic performance curve is divided into a plurality of characteristic regions; Determine a sub-adjoint matrix corresponding to each of the feature regions; The sub-adjoint matrices corresponding to the plurality of feature regions are combined to obtain the adjoint matrix.

11. An electronic device, It is characterized in that The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the steps of the pneumatic data acquisition method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of the pneumatic data acquisition method according to any one of claims 1 to 9 are implemented.

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