A method for increasing the density of airfoil pressure distribution test results

Abstract

The present invention discloses a method for densifying the test results of airfoil pressure distribution, which relates to the field of wind tunnel test. It first gives uniformly densified pressure measurement point distribution coordinates, lists the constraint conditions that the integral result of the airfoil pressure coefficient is equal to the force measurement result, and then smoothly fits the measurement point results of the original pressure measurement test, and uses them as the initial value of the pressure coefficient of the target point, gives a reasonable target function model of the densified point pressure distribution, and uses an optimization algorithm to solve the densified point pressure distribution with the least overall offset from the fitted smooth result. The present invention has high reliability, does not need to increase the test content or numerical simulation workload, is highly economical, has a simple and easy process, and is easy to implement through programming and rapid implementation. In addition, it can effectively improve the density of the pressure wind tunnel test results of the two-dimensional airfoil during application, so that aircraft designers can better evaluate the aerodynamic characteristics of the airfoil, and further support the aerodynamic shape optimization design work.

Description

Technical Field

[0001] The invention relates to the field of wind tunnel test, and in particular to a method for increasing the density of airfoil pressure distribution test results. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] In the design of aircraft aerodynamic shape, the design and selection of the cross-sectional shape (airfoil) of each wing surface is very important. It is the most basic factor that determines the aerodynamic characteristics of the aircraft. Wind tunnel testing is an important and reliable data source for obtaining the aerodynamic characteristics of airfoils. The force test results of the airfoil are relatively accurate, but they reflect the aerodynamic integration results of the model as a whole and cannot depict the detailed distribution characteristics of the flow on the surface. The pressure test results can give the surface pressure distribution, but due to the small space of the scaled-down test model, the number of pressure measurement points that can be arranged on the surface is limited, and only approximate pressure distribution characteristics can be obtained.

[0004] At present, the method of obtaining high-density airfoil surface pressure distribution mainly relies on computational fluid dynamics (CFD) simulation method. This method uses geometric grid points to divide the airfoil surface, can arbitrarily change the division density, and obtain the pressure results of each grid point, generating flow characteristic distribution results close to continuous distribution. However, as a simulation method, the reliability of the CFD method cannot be fully guaranteed, and it needs to be verified by wind tunnel test results. In addition, it is difficult to match the pressure measurement results and force measurement results with the CFD simulation results at the same time. Verifying one type of result alone reduces the credibility of this method. Another method is to rely only on the results of the pressure measurement test points, interpolate the sparse results, and obtain the densified test results. This method cannot guarantee the rationality of the interpolation results, and the aerodynamic force integrated by the pressure measurement results is difficult to match the force measurement results. Therefore, it is necessary to invent a method for densifying the test results of two-dimensional airfoil pressure distribution based on force measurement results to obtain a richer and more reliable two-dimensional airfoil surface pressure distribution to support the aerodynamic shape design of aircraft. Summary of the invention

[0005] The purpose of the present invention is to provide a method for densifying the test results of airfoil pressure distribution in a wind tunnel test. The method provides a method for densifying the test results of airfoil pressure distribution, provides reasonable sample point distribution coordinates, takes the smooth fitting results of the sparse test results of the pressure measurement test as the initial values ​​of the pressure coefficients of the sample points, takes the airfoil force measurement test results as the constraints for the integration of the pressure measurement results, provides a reasonable target function model for the pressure distribution of the densified points, and uses an optimization algorithm to solve the pressure of the target coordinate points with the least overall offset from the smooth fitting results of the pressure measurement sample points, thereby solving the above problems.

[0006] The technical solution of the present invention is as follows:

[0007] A method for increasing airfoil pressure distribution test results, comprising:

[0008] Step S1: Obtain normalized airfoil coordinates , horizontal coordinate of moment reference point , Airfoil pressure test results , Normal force coefficient of airfoil force test and the pitching moment coefficient ;in, is the horizontal coordinate of the airfoil pressure measuring point, is the pressure coefficient value at the corresponding measuring point;

[0009] Step S2: Select equally spaced steps or number of partition blocks , thereby obtaining the horizontal coordinate of the encrypted target point ;

[0010] Step S3: Based on airfoil coordinates , Airfoil pressure test results and the horizontal axis , get the encrypted target point airfoil coordinates And the preliminary pressure distribution results after encryption ,in Indicates the initial pressure after encryption;

[0011] Step S4: According to the airfoil coordinates of the target point , find the gradient of each target point of the airfoil ; Based on the preliminary pressure distribution results , and the pressure gradient change on the airfoil surface is obtained ;

[0012] Step S5: For each target point, the horizontal coordinate , the airfoil pressure test results In the The horizontal coordinate of the nearest airfoil pressure measuring point Corresponding points and calculate the distance between the two points ;

[0013] Step S6: Calculate the horizontal coordinate To the horizontal coordinate of the moment reference point The distance between ;

[0014] Step S7: According to the horizontal coordinate , target point airfoil coordinates ,gradient , find the equivalent step length distribution of the normal direction integral of the pressure at each target point on the airfoil ,in, It represents the equivalent step length of the normal direction integration of the target point pressure on the airfoil;

[0015] Step S8: Test the normal force coefficient according to the airfoil force , give the constraint condition 1 of the integral normal force;

[0016] Step S9: According to the pitch moment coefficient , giving the constraint condition 2 of the integral pitching moment;

[0017] Step S10: Based on the preliminary pressure distribution results , give the maximum and minimum estimated values ​​of the pressure coefficient of the target point as constraint condition 3;

[0018] Step S11: According to the gradient , Changes in pressure gradient on the airfoil surface ,distance The variable distribution and initial value of , list the cost function ;

[0019] Step S12: According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, the optimization result is obtained;

[0020] Step S13: Draw a comparison chart between the optimization results and the pressure coefficient distribution data of the original test points. If the optimized results are smoothly connected with the test results and the pressure distribution law is reasonable, the data densification is considered to be successful, and the optimized pressure distribution results are output; if the data connectivity is poor, return to step S12 and compare the optimization results again until the connectivity requirements are met.

[0021] Furthermore, the step S2 comprises:

[0022] Horizontal axis .

[0023] Furthermore, the step S3 comprises:

[0024] In airfoil coordinates In the The closest horizontal coordinate The corresponding two points are ordinate Linear interpolation of , thus obtaining the encrypted target point airfoil coordinates ;

[0025] Pressure test results Use smooth curve fitting method to interpolate to the horizontal axis The preliminary pressure distribution results after encryption are obtained .

[0026] Furthermore, the gradient of each target point of the airfoil in step S4 Calculated by the following formula:

[0027]

[0028] The airfoil surface pressure gradient changes in step S4 Calculated by the following formula:

[0029]

[0030] in:

[0031] is the symbol of partial derivative.

[0032] Furthermore, the distance in step S5 Calculated by the following formula:

[0033]

[0034] Then the horizontal coordinates of each target point and the horizontal coordinate set of the nearest test point is expressed as , in which to remove point.

[0035] Furthermore, the horizontal coordinate in step S6 To the horizontal coordinate of the moment reference point The distance between Calculated by the following formula:

[0036]

[0037] Then the horizontal coordinates of each target point To the horizontal coordinate of the moment reference point The distance distribution of .

[0038] Furthermore, in step S7, The equivalent step length of the normal direction integral of the pressure at each target point on the airfoil is calculated by the following formula:

[0039]

[0040] in:

[0041] Indicates The equivalent step length of the normal direction integration of the pressure at each target point on the airfoil;

[0042] Indicates airfoil The gradient of the target point;

[0043] Indicates The vertical coordinate of the target point;

[0044] Indicates The vertical coordinate of the target point.

[0045] Furthermore, the constraint condition 1 given in step S8 is as follows:

[0046]

[0047] in:

[0048] Indicates that the first Initial estimate of the pressure coefficient value at each target point or in subsequent iterations The pressure coefficient value of each target point;

[0049] Indicates the number of target points, that is, the number of separation blocks;

[0050] The constraint condition 2 given in step S9 is as follows:

[0051]

[0052] in:

[0053] Indicates The horizontal coordinate of the target point To the horizontal coordinate of the moment reference point The distance between.

[0054] Furthermore, the cost function listed in step S11 as follows:

[0055]

[0056] in:

[0057] Indicates The horizontal coordinate of the target point The distance between the horizontal coordinate of the nearest test point;

[0058] Indicates The pressure gradient on the airfoil surface at each target point;

[0059] , , , , is an adjustable weight parameter.

[0060] Furthermore, the step S12 includes:

[0061] For the cost function Assign initial values ​​to the adjustable weight parameters in;

[0062] According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, we can get The pressure coefficient value when it is minimum The distribution of

[0063] The step S13 comprises:

[0064] If the data connectivity is poor, return to step S12, adjust the adjustable weight parameters, and compare the optimization results again until the connectivity requirements are met.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] 1. The present invention uses the fitting value of the wind tunnel test pressure measurement result as the initial result, and the normal force and pitch moment results of the force measurement test as the constraint conditions. The two sets of test results are integrated to predict the pressure distribution of more measuring points, and the results are more accurate and reliable. This method is completely based on the original wind tunnel test results, does not need to increase the test content or the workload of numerical simulation, is highly economical, has a simple and easy process, and is easy to program and implement quickly.

[0067] 2. The present invention can effectively improve the density of pressure wind tunnel test results of two-dimensional airfoils during application, so that aircraft designers can better evaluate the aerodynamic characteristics of the airfoils and further support the optimization design of aerodynamic shapes. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of a method for increasing the airfoil pressure distribution test results in the present invention;

[0069] Figure 2 It is a distribution diagram of coordinate points on the upper and lower surfaces of a typical airfoil according to an airfoil pressure distribution test result densification method in the present invention;

[0070] Figure 3 It is a measurement result diagram of direct measurement points of pressure coefficient distribution on upper and lower wing surfaces of a typical airfoil of a method for increasing the airfoil pressure distribution test results in the present invention;

[0071] Figure 4 This is a comparison example of the pressure distribution of an airfoil section before and after densification drawn by a method for densifying the test results of an airfoil pressure distribution in the present invention. DETAILED DESCRIPTION

[0072] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0073] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0074] Embodiment 1

[0075] The classic NACA0012 airfoil is selected as the object in this embodiment, and the airfoil parameters and test data are selected from the NASA-TP-2485 report, which gives M =0.76, angle of attack α =2.05°, Reynolds number per unit chord length Re =6.3×10 6 Due to the limited model space, only 40 measuring points were arranged on the upper and lower surfaces of the airfoil, and the pressure distribution results were relatively sparse.

[0076] Therefore, in view of the above problems, this embodiment proposes a method for increasing the density of airfoil pressure distribution test results. Figure 1 , specifically including the following steps:

[0077] Step S1: Obtain normalized airfoil coordinates , horizontal coordinate of moment reference point , Airfoil pressure test results , Normal force coefficient of airfoil force test and the pitching moment coefficient ;in, is the horizontal coordinate of the airfoil pressure measuring point, is the pressure coefficient value at the corresponding measuring point; it should be noted that all coordinate data are processed separately for the upper and lower wing surfaces of the airfoil; among them, and Between 0 and 1; specifically, as in this example Figure 2 , the horizontal coordinate of the moment reference point ; As in this example Figure 2 and Figure 3 As shown, , .

[0078] Step S2: Select equally spaced steps or number of partition blocks , thereby obtaining the horizontal coordinate of the encrypted target point ; horizontal axis

[0079] like or number of partition blocks (equivalent to ) to obtain the encrypted horizontal coordinate of the target point ;Right now:

[0080] , , , …, , …, 1;

[0081] In this example, select or number of partition blocks , then the horizontal coordinate of the encrypted target point is obtained for:

[0082] , , , ,…,1.

[0083] Step S3: Based on airfoil coordinates , Airfoil pressure test results and the horizontal axis , get the encrypted target point airfoil coordinates And the preliminary pressure distribution results after encryption ;

[0084] In this embodiment, specifically, step S3 includes:

[0085] In airfoil coordinates In the The closest horizontal coordinate The corresponding two points are ordinate Linear interpolation of , thus obtaining the encrypted target point airfoil coordinates ;

[0086] Pressure test results Use smooth curve fitting method to interpolate to the horizontal axis The preliminary pressure distribution results after encryption are obtained ,in It represents the initial pressure after encryption; it should be noted that the smooth curve fitting method includes various methods such as spline interpolation and polynomial interpolation. In this embodiment, the cubic spline interpolation method is adopted.

[0087] Step S4: According to the airfoil coordinates of the target point , find the gradient of each target point of the airfoil ; Based on the preliminary pressure distribution results , and the pressure gradient change on the airfoil surface is obtained ;

[0088] In this embodiment, specifically, the gradient of each target point of the airfoil in step S4 is Calculated by the following formula:

[0089]

[0090] The airfoil surface pressure gradient changes in step S4 Calculated by the following formula:

[0091]

[0092] in:

[0093] is the symbol of partial derivative;

[0094] If the central difference method is used for the Target points:

[0095]

[0096]

[0097] Step S5: For each target point, the horizontal coordinate , the airfoil pressure test results In the The horizontal coordinate of the nearest airfoil pressure measuring point Corresponding points and calculate the distance between the two points ;

[0098] In this embodiment, specifically, the distance in step S5 Calculated by the following formula:

[0099]

[0100] Then the horizontal coordinates of each target point and the horizontal coordinate set of the nearest test point is expressed as , in which to remove point;

[0101] That is, for the target points, whose distance The calculation formula is as follows:

[0102]

[0103] in:

[0104] Indicates The horizontal coordinate of the target point The horizontal coordinate corresponding to the nearest test point.

[0105] Step S6: Calculate the horizontal coordinate To the horizontal coordinate of the moment reference point The distance between ;

[0106] In this embodiment, specifically, the horizontal coordinate in step S6 To the horizontal coordinate of the moment reference point The distance between Calculated by the following formula:

[0107]

[0108] Then the horizontal coordinates of each target point To the horizontal coordinate of the moment reference point The distance distribution of ;

[0109] That is, for the target points, whose distance The calculation formula is as follows:

[0110]

[0111] Step S7: According to the horizontal coordinate , target point airfoil coordinates ,gradient , find the equivalent step length distribution of the normal direction integral of the pressure at each target point on the airfoil ,in, It represents the equivalent step length of the normal direction integration of the target point pressure on the airfoil;

[0112] In this embodiment, specifically, in step S7, The equivalent step length of the normal direction integral of the pressure at each target point on the airfoil is calculated by the following formula:

[0113]

[0114] in:

[0115] Indicates The equivalent step length of the normal direction integration of the pressure at each target point on the airfoil;

[0116] Indicates airfoil The gradient of the target point;

[0117] Indicates The vertical coordinate of the target point;

[0118] Indicates The vertical coordinate of the target point.

[0119] Step S8: Test the normal force coefficient according to the airfoil force , give the constraint condition 1 of the integral normal force;

[0120] In this embodiment, specifically, the constraint condition 1 given in step S8 is as follows:

[0121]

[0122] in:

[0123] In step S3, the Initial estimate of the pressure coefficient value at each target point or in subsequent iterations The pressure coefficient value of each target point;

[0124] Indicates the number of target points, that is, the number of separation blocks.

[0125] Step S9: According to the pitch moment coefficient , giving the constraint condition 2 of the integral pitching moment;

[0126] In this embodiment, specifically, the constraint condition 2 given in step S9 is as follows:

[0127]

[0128] in:

[0129] Indicates The horizontal coordinate of the target point To the horizontal coordinate of the moment reference point The distance between.

[0130] Step S10: Based on the preliminary pressure distribution results , give the maximum and minimum estimated values ​​of the pressure coefficient of the target point as constraint condition 3; in this example, the minimum pressure coefficient is -2 and the maximum is 2.

[0131] Step S11: According to the gradient , Changes in pressure gradient on the airfoil surface ,distance The variable distribution and initial value of , list the cost function ;

[0132] In this embodiment, specifically, the cost function listed in step S11 is as follows:

[0133]

[0134] in:

[0135] Indicates The horizontal coordinate of the target point The distance between the horizontal coordinate of the nearest test point;

[0136] Indicates The pressure gradient on the airfoil surface at each target point;

[0137] , , , , is an adjustable weight parameter; in this example, , , , , .

[0138] Step S12: According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, the optimization result is obtained;

[0139] In this embodiment, specifically, step S12 includes:

[0140] For the cost function Assign initial values ​​to the adjustable weight parameters in;

[0141] According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, we can get The pressure coefficient value when it is minimum distribution; it should be noted that the optimization algorithm includes descent method, stochastic gradient descent method, sequential least squares method, Newton method, etc.; in this example, the sequential least squares method is used to solve the pressure coefficient value that satisfies the minimum cost function Distribution results.

[0142] Step S13: Draw a comparison chart of the optimization results and the pressure coefficient distribution data of the original test points. If the optimized results are smoothly connected with the test results and the pressure distribution law is reasonable, the data densification is considered to be successful, and the optimized pressure distribution results are output; as in this example Figure 4 As shown;

[0143] If the data connectivity is poor, return to step S12, adjust the adjustable weight parameters, and compare the optimization results again until the connectivity requirements are met.

[0144] The above-mentioned embodiments only express the specific implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the protection scope of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the technical solution concept of the present application, and these all belong to the protection scope of the present application.

[0145] This background section is provided to generally present the context of the invention, and the work of the presently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither explicitly nor implicitly admitted to be prior art to the present invention.

Claims

1. A method for increasing the results of airfoil pressure distribution tests, characterized in that: include: Step S1: Obtain normalized airfoil coordinates , horizontal coordinate of moment reference point , Airfoil pressure test results , Normal force coefficient of airfoil force test and the pitching moment coefficient ;in, is the horizontal coordinate of the airfoil pressure measuring point, is the pressure coefficient value at the corresponding measuring point; Step S2: Select equally spaced steps or number of partition blocks , thereby obtaining the horizontal coordinate of the encrypted target point ; Step S3: Based on airfoil coordinates , Airfoil pressure test results and the horizontal axis , get the encrypted target point airfoil coordinates And the preliminary pressure distribution results after encryption ,in Indicates the initial pressure after encryption; Step S4: According to the airfoil coordinates of the target point , find the gradient of each target point of the airfoil ; Based on the preliminary pressure distribution results , and the pressure gradient change on the airfoil surface is obtained ; Step S5: For each target point , the airfoil pressure test results In the The horizontal coordinate of the nearest airfoil pressure measuring point Corresponding points and calculate the distance between the two points ; Step S6: Calculate the horizontal coordinate To the horizontal coordinate of the moment reference point The distance between ; Step S7: According to the horizontal coordinate , target point airfoil coordinates ,gradient , find the equivalent step length distribution of the normal direction integral of the pressure at each target point on the airfoil ,in, It represents the equivalent step length of the normal direction integration of the target point pressure on the airfoil; Step S8: Test the normal force coefficient according to the airfoil force measurement , give the constraint condition 1 of the integral normal force; Step S9: According to the pitch moment coefficient , giving the constraint condition 2 of the integral pitching moment; Step S10: Based on the preliminary pressure distribution results , give the maximum and minimum estimated values ​​of the pressure coefficient of the target point as constraint condition 3; Step S11: According to the gradient , Changes in pressure gradient on the airfoil surface ,distance The variable distribution and initial value of , list the cost function ; Step S12: According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, the optimization result is obtained; Step S13: Draw a comparison chart between the optimization results and the pressure coefficient distribution data of the original test points. If the optimized results are smoothly connected with the test results and the pressure distribution law is reasonable, the data densification is considered to be successful, and the optimized pressure distribution results are output; if the data connectivity is poor, return to step S12 and compare the optimization results again until the connectivity requirements are met.

2. A method for increasing airfoil pressure distribution test results according to claim 1, characterized in that: The step S2 comprises: Horizontal axis .

3. A method for increasing airfoil pressure distribution test results according to claim 2, characterized in that: The step S3 comprises: In airfoil coordinates In the The closest horizontal coordinate The corresponding two points are ordinate Linear interpolation of , thus obtaining the encrypted target point airfoil coordinates ; Pressure test results Use smooth curve fitting method to interpolate to the horizontal axis The preliminary pressure distribution results after encryption are obtained .

4. The method for increasing the airfoil pressure distribution test results according to claim 1, characterized in that: The gradient of each target point of the airfoil in step S4 Calculated by the following formula: The airfoil surface pressure gradient changes in step S4 Calculated by the following formula: in: is the symbol of partial derivative.

5. The method for increasing the airfoil pressure distribution test results according to claim 1, characterized in that: The distance in step S5 Calculated by the following formula: Then the horizontal coordinates of each target point and the horizontal coordinate set of the nearest test point is expressed as , in which to remove point.

6. The method for increasing the airfoil pressure distribution test results according to claim 1, characterized in that: The horizontal coordinate in step S6 To the horizontal coordinate of the moment reference point The distance between Calculated by the following formula: Then the horizontal coordinates of each target point To the horizontal coordinate of the moment reference point The distance distribution of .

7. The method for increasing the airfoil pressure distribution test results according to claim 1, characterized in that: In step S7, The equivalent step length of the normal direction integral of the pressure at each target point on the airfoil is calculated by the following formula: in: Indicates The equivalent step length of the normal direction integration of the pressure at each target point on the airfoil; Indicates airfoil The gradient of the target point; Indicates The vertical coordinate of the target point; Indicates The vertical coordinate of the target point.

8. A method for increasing airfoil pressure distribution test results according to claim 7, characterized in that: The constraint condition 1 given in step S8 is as follows: in: Indicates that the first Initial estimate of the pressure coefficient value at each target point or in subsequent iterations The pressure coefficient value of each target point; Indicates the number of target points, that is, the number of separation blocks; The constraint condition 2 given in step S9 is as follows: in: Indicates The horizontal coordinate of the target point To the horizontal coordinate of the moment reference point The distance between.

9. A method for increasing airfoil pressure distribution test results according to claim 8, characterized in that: The cost function listed in step S11 as follows: in: Indicates The horizontal coordinate of the target point The distance between the horizontal coordinate of the nearest test point; Indicates The pressure gradient on the airfoil surface at each target point; , , , , is an adjustable weight parameter.

10. A method for increasing airfoil pressure distribution test results according to claim 9, characterized in that: The step S12 comprises: For the cost function Assign initial values ​​to the adjustable weight parameters in; According to the initial value , Constraint 1, Constraint 2, Constraint 3 and Cost Function , using the optimization algorithm, we can get The pressure coefficient value when it is minimum The distribution of The step S13 comprises: If the data connectivity is poor, return to step S12, adjust the adjustable weight parameters, and compare the optimization results again until the connectivity requirements are met.

Images