Method for predicting multi-target point buffeting response of aircraft tail based on elastic similarity transformation

Abstract

The present application belongs to the technical field of aircraft buffet wind tunnel test, and discloses a method for predicting multi-target point buffet response of aircraft tail wing based on elastic similarity conversion. The present application determines a new similarity relationship and constructs an elastic similarity conversion model based on structural dynamics equation and elastic similarity principle, aiming at multiple non-reference aircraft target flight states. The elastic similarity conversion model generates the buffet acceleration response under the "equivalent wind tunnel test" by combining the fluctuating pressure and buffet acceleration response measured by the "rigid / elastic combined" buffet wind tunnel test model. According to the new similarity relationship satisfied by the elastic similarity conversion model, the buffet acceleration response measured under the "equivalent wind tunnel test" is converted to multiple non-reference actual aircraft scale target flight states. The present application generalizes the "equivalent wind tunnel test" buffet response data of the elastic similarity conversion model through the buffet wind tunnel test data under a single state, and realizes the prediction of multi-target point buffet response of aircraft tail wing.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of aircraft flutter wind tunnel test, and relates to a flutter response prediction method for a multi-target point of a tail wing of an aircraft based on elastic similarity conversion. BACKGROUND

[0002] When a twin-tail wing edge wing layout aircraft is in a high angle of attack maneuver flight, a tail flutter problem occurs, which can cause fatigue damage of the tail wing structure, shorten the service life of the tail wing and increase the maintenance cost. The flutter dynamic response and dynamic load problem of the tail wing need to be analyzed and designed in detail in the aircraft model design stage. In the aircraft model design stage, the flutter wind tunnel test technology based on a "rigid / elastic combination" model is the main technical means to determine the flutter dynamic response and dynamic load of the tail wing. The so-called "rigid / elastic combination" flutter wind tunnel test model is that the fuselage, wings and one side tail wing of the test model device in the full aircraft state adopt a geometrically similar rigid model. While ensuring that the aerodynamic shape and flow field characteristics of the fuselage, wings and single side tail wing are similar, the flutter pulsating pressure is measured by arranging pulsating pressure sensors on the rigid tail wing. While ensuring that the structural dynamics characteristics of the tail wing are similar, the flutter acceleration response is measured by arranging acceleration sensors on the elastic tail wing. Finally, the flutter pulsating pressure and flutter acceleration response are simultaneously measured in the full aircraft state. Then, the flutter pulsating pressure and acceleration response results of the actual aircraft scale are obtained by converting the wind tunnel test results according to the similarity conversion relationship between the wind tunnel test state and the flight state of the actual aircraft scale, which are used to guide the tail wing stiffness design, so that the natural frequency avoids the dominant excitation frequency of the out-of-body vortex as much as possible, thereby reducing the flutter response and improving the fatigue resistance of the structure.

[0003] However, the elastic tail wing of the traditional "rigid / elastic combination" flutter wind tunnel test model is uniquely determined according to the scaling similarity relationship between the wind tunnel test state and the target flight state (scale , altitude and Mach number ). If the test state or the target flight state changes, the test data cannot be directly extrapolated to any target design point through similarity conversion. Since the actual flight speed of a fighter aircraft far exceeds the flutter starting speed boundary, and there are a large number of flutter dynamic strength design points in the flight envelope that need to be checked, the flutter wind tunnel test based on a single "rigid / elastic combination" model device cannot meet the multi-target point flutter dynamic response and dynamic strength design requirements. Therefore, it is urgent to develop a flutter response prediction method for a multi-target point of a tail wing of an aircraft, so as to realize the flutter dynamic response generalization from a single wind tunnel test state data to multiple target flight states, and improve the utilization efficiency of the flutter wind tunnel test data of the aircraft. SUMMARY

[0004] To solve the above problems, the application provides an aircraft tail multi-target point buffeting response prediction method based on elastic similarity conversion. For input of multiple non-reference actual aircraft scale target flight states, i.e. flight states not conforming to direct similarity conversion, a new similarity relationship is determined from a structural dynamics equation and an elastic similarity principle, and an elastic similarity conversion model is constructed. In combination with the actual wind tunnel test measured fluctuating pressure and acceleration response of the "rigid / elastic combined" model, the acceleration response of the elastic similarity conversion model under "equivalent wind tunnel test" is generated, and according to the new similarity relationship satisfied by the elastic similarity conversion model, the buffeting response measured under "equivalent wind tunnel test" is converted to multiple non-reference actual aircraft scale target flight states. The application obtains the buffeting response data of the "equivalent wind tunnel test" of the elastic similarity conversion model through the buffeting wind tunnel test data of a single state, and realizes the aircraft tail multi-target point buffeting response prediction.

[0005] The aircraft tail multi-target point buffeting response prediction method based on elastic similarity conversion has the following steps:

[0006] Step 1: "Rigid / elastic combined" buffeting wind tunnel test model design

[0007] The "rigid / elastic combined" buffeting wind tunnel test system comprises a "rigid / elastic combined" buffeting wind tunnel test model device, a main support rod, a tail support rod piece, a main support rod angle adapting mechanism and a tail support rod angle adapting mechanism. The main support rod angle adapting mechanism and the tail support rod angle adapting mechanism are arranged on the main support rod and the tail support rod piece respectively, and the main support rod and the tail support rod piece are used to support the "rigid / elastic combined" buffeting wind tunnel test model device.

[0008] The "rigid / elastic combined" buffeting wind tunnel test model device comprises a rigid fuselage, a rigid wing, a rigid tail, an elastic tail, a fluctuating pressure sensor and an acceleration sensor. The rigid tail comprises a rigid wing surface structure and a cover plate, the cover plate is buckled with the rigid wing surface structure to form a rigid tail model device, and the rigid tail model device is fixed to the rigid fuselage. The rigid tail is designed according to the geometric shape of the real aircraft structure, and the fluctuating pressure sensors are arranged on both sides of the rigid tail for measuring the buffeting fluctuating pressure during the buffeting wind tunnel test. The elastic tail comprises an elastic tail model device, a metal core plate and a shape maintaining foam. The metal core plate is located in the middle of the elastic tail to provide elastic support. The shape maintaining foam is covered on the metal core plate to maintain the aerodynamic shape of the tail. The metal core plate and the shape maintaining foam together form the elastic tail model device and are installed on the rigid fuselage. The elastic tail is designed according to the elastic structural dynamics scaling, and the acceleration sensors are arranged on the elastic tail for measuring the buffeting acceleration response of the elastic tail during the buffeting wind tunnel test.

[0009] The elastic tail is designed according to the elastic structural dynamics scaling, and the basis for similarity conversion is that the Strouhal number of the elastic tail is equal to that of the real aircraft structure:

[0010] (1)

[0011] wherein, is the Strouhal number, and is the reduced frequency; is the circular frequency; is the characteristic length; is the air flow velocity; the three scales used in the elastic tail design according to the elastic structural dynamics scaling are:

[0012] (2)

[0013] (3)

[0014] (4)

[0015] wherein, is the length scale, is the velocity scale, is the density scale, are the length, the air flow velocity and the air density of the "rigid / elastic combination" flutter wind tunnel test model, respectively; are the length, the air flow velocity and the air density of the real aircraft structure, respectively; from the scales of equations (2)-(4), the derived scales are as follows:

[0016] (5)

[0017] (6)

[0018] (7)

[0019] wherein, , and are the mass ratio, the stiffness ratio and the frequency ratio of the elastic tail to the real aircraft structure, respectively; are the mass, the stiffness and the circular frequency of the elastic tail, respectively; are the mass, the stiffness and the circular frequency of the real aircraft structure, respectively;

[0020] In the design of the elastic tail, firstly, the length , the air flow velocity and the air density of the "rigid / elastic combination" flutter wind tunnel test model are determined according to the size of the wind tunnel and the test wind speed limit; then, the length , the air flow velocity and the air density of the real aircraft structure are determined, and the scales 、 and then the derived scale is obtained according to formula (5)~(7) 、 and so as to determine the mass of the "rigid / elastic combination" buffet wind tunnel test model including the elastic tail wing , the stiffness and the circular frequency ;

[0021] The elastic tail wing model designed according to formula (2)~(7) for the reference target flight state is defined as the reference buffet wind tunnel test model, and the reference buffet wind tunnel test model corresponds to the altitude and Mach number of the reference flight state; the elastic tail wing after the target flight state is changed is defined as the elastic similarity conversion model;

[0022] Step 2: buffet wind tunnel test of the reference buffet wind tunnel test model;

[0023] The reference buffet wind tunnel test model is designed and processed, and the buffet wind tunnel test of the reference buffet wind tunnel test model is carried out; the incoming flow velocity of the buffet wind tunnel test is set as according to the elastic structure dynamics reduced scale, the angle of attack range of the "rigid / elastic combination" buffet wind tunnel test model is adjusted through the main support rod and the tail support rod , wherein m is the number of changes of the angle of attack of the buffet wind tunnel test, and the buffet wind tunnel test state is determined; the buffet wind tunnel test of the reference buffet wind tunnel test model is completed, and the buffet fluctuating pressure of the fluctuating pressure sensor and the buffet acceleration response of the acceleration sensor are recorded;

[0024] Step 3: constructing the elastic similarity conversion model;

[0025] Without considering the fluid-structure coupling effect, the buffet response motion equation of the reference buffet wind tunnel test model is:

[0026] (8)

[0027] wherein, is the mass matrix, the damping matrix and the stiffness matrix of the reference buffet wind tunnel test model corresponding to the reference target flight state designed in step 1, and the reference buffet wind tunnel test model is obtained by carrying out finite element modeling on the actually designed reference buffet wind tunnel test model; the superscript 0 indicates the reference buffet wind tunnel test model; is the displacement, velocity and acceleration of the reference buffet wind tunnel test model in the physical space; is the buffet fluctuating pressure load vector measured by the wind tunnel test, and is measured by the fluctuating pressure sensor;

[0028] According to the modal superposition principle Equation (8) is then transformed into the generalized dynamic response equation in modal space:

[0029] (9)

[0030] in, For the generalized mass matrix, For the generalized damping matrix, For generalized stiffness matrix, This is the generalized pulsating pressure load vector. It is the mass-normalized mode matrix. These are displacement, velocity, and acceleration in modal space;

[0031] Given a fixed actual aircraft structure, it is assumed that the modal shapes of the baseline flutter wind tunnel test model and the elastic similarity transformation model after the target flight state changes are consistent, and the structural damping remains unchanged. The construction of the elastic similarity transformation model is based on the flutter wind tunnel test data of the baseline flutter wind tunnel test model, and the length scales of the two are equal. , where superscript The velocity ratio and density ratio represented by equations (3) and (4), and the mass ratio, stiffness ratio, and frequency ratio represented by equations (5)-(7) of the elastic similarity transformation model need to be re-determined according to the new target flight state; based on equations (5)-(7), and the mass normalized mode matrix of the benchmark flutter wind tunnel test model Generalized mass matrix and generalized stiffness matrix Construct the generalized mass matrix of the elastic similarity transformation model under the new target flight state. and generalized stiffness matrix :

[0032] (10)

[0033] (11)

[0034] (12)

[0035] In equations (10) to (12) , and Let represent the generalized mass matrix, generalized stiffness matrix, and frequency of the elastic similarity transformation model, respectively. , and These represent the density ratio, velocity ratio, and frequency ratio of the elastic similarity transformation model, respectively; the lengths of the benchmark buffeting wind tunnel test model and the elastic similarity transformation model are consistent. With the aerodynamic shape of the actual aircraft structure remaining unchanged, the generalized pulsating pressure load vector before and after the elastic similarity transformation... The damping remains unchanged; it is assumed that the damping of the elastic similarity transformation model is consistent with that of the benchmark buffeting wind tunnel test model. Then, the generalized mass matrix based on the elastic similarity transformation model Generalized damping matrix Generalized stiffness matrix and generalized pulsating pressure load vector The response motion equations of the elastic similarity transformation model are as follows:

[0036] (13)

[0037] Equation (13) was solved using different time integration methods to obtain the chattering acceleration response that satisfies the elastic similarity transformation model under the new target flight state.

[0038] Step 4: Generation of buffeting response from "equivalent wind tunnel test";

[0039] Assume the buffeting acceleration response obtained from the buffeting wind tunnel test of the benchmark buffeting wind tunnel model is as follows: The generalized pulsating pressure load vector obtained from the actual measurement of pulsating pressure. Solve (9) to obtain the acceleration. Then, based on the principle of modal superposition... To obtain the acceleration response in physical space The acceleration response obtained by solving the elastic similarity transformation model is: The buffeting acceleration response measured in the "equivalent wind tunnel test" using the elastic similarity transformation model is defined as follows: The four variables satisfy the following relationship:

[0040] (14)

[0041] in, To take the root mean square; then:

[0042] (15)

[0043] According to the principle of dimensional analysis, the response history times of the benchmark buffeting wind tunnel test model and the elastic similarity transformation model are related as follows:

[0044] (16)

[0045] in, and These represent the response history times of the benchmark buffeting wind tunnel test model and the elastic phase transition model, respectively. and These represent the time ratios of the benchmark buffeting wind tunnel test model and the elastic phase transition model, respectively. and This represents the frequency ratio between the benchmark buffeting wind tunnel test model and the elastic similarity transformation model; and These represent the velocity ratios of the baseline buffeting wind tunnel test model and the elastic similarity transformation model, respectively.

[0046] Measured acceleration response of the benchmark buffeting wind tunnel test model in a buffeting wind tunnel. Based on this, the wind tunnel test data of the benchmark buffeting wind tunnel test model are analyzed using equation (15). Amplitude scaling is performed, and the wind tunnel test response of the benchmark buffeting wind tunnel test model is evaluated using equation (16). By scaling the time, the buffeting acceleration response of the elastic similarity transformation model in the equivalent wind tunnel test is obtained. ;

[0047] Experimental acceleration response of elastic similarity transformation model Based on the test data of the benchmark buffeting wind tunnel test model Based on this, calculations were performed using equations (15) and (16), without conducting new experimental tests for the new target flight state; through the analysis of... The transformation is performed to obtain the actual aircraft-scale acceleration response under the new target flight state corresponding to the elastic similarity transformation model;

[0048] Step 5: Predict the multi-target point buffeting response of a real aircraft structure;

[0049] The acceleration response of the elastic similarity transformation model and the actual flight state satisfy the following proportional relationship:

[0050] (17)

[0051] (18)

[0052] in, The proportional relationship between the RMS values ​​of the acceleration response. This represents the proportional relationship of the acceleration response power spectral density function.

[0053] The beneficial effects of this invention are as follows: The multi-objective point response prediction method proposed in this invention can effectively convert a baseline wind tunnel test model into multiple new target design point flight states. This method avoids the need to design multiple elastic similarity models to adapt to different target point flight states, thus avoiding the problems of increased cost and decreased efficiency in wind tunnel testing, and significantly improving the flexibility and economy of the testing work. Furthermore, this method achieves multi-objective point response prediction by constructing a modified model that satisfies similarity relationships, and it also has certain applicability to elastic models with overweight coefficients, providing theoretical support and technical reference for practical engineering applications. This method is also applicable to the multi-objective point prediction needs of other dynamic responses and loads such as displacement, velocity, bending moment, and torque, and has strong versatility and scalability. Attached Figure Description

[0054] Figure 1 This is a flowchart of a multi-objective point chattering response prediction method based on elastic similarity transformation.

[0055] Figure 2 This is a schematic diagram of the structure of the "rigid / elastic combination" buffeting wind tunnel test system.

[0056] Figure 3 This is a schematic diagram of the structure of the "rigid / elastic combination" buffeting wind tunnel test model device.

[0057] Figure 4 This is a schematic diagram of the rigid tail fin.

[0058] Figure 5 This is a schematic diagram of the flexible tail fin.

[0059] Figure 6 The time-domain signal of the pulsating pressure of the rigid vertical tail at an angle of attack of 20° is used as the reference fluttering wind tunnel test model (measuring point 1, measuring point 5, measuring point 9).

[0060] Figure 7 The time-domain signal of the acceleration response of the elastic vertical tail tip at an angle of attack of 20° is used as the benchmark fluttering wind tunnel test model.

[0061] Figure 8 The finite element model of the elastic tail fin is used as the benchmark fluttering wind tunnel test model.

[0062] Figure 9 A scatter plot showing the relative error distribution of the response before and after correction.

[0063] Figure 10 The acceleration response PSD before and after correction is compared with the control group (flight state 1).

[0064] In the figure, 1 is the "rigid / elastic combination" flutter wind tunnel test model device, 2 is the main support rod, 3 is the tail support rod, 4 is the main support rod angle of attack adaptation mechanism, 5 is the tail support rod angle of attack adaptation mechanism, 11 is the rigid fuselage, 12 is the rigid wing, 13 is the rigid tail fin, 14 is the elastic tail fin, 15 is the pulsating pressure sensor, 16 is the acceleration sensor, 131 is the rigid tail fin model device, 132 is the cover plate, 133 is the rigid airfoil structure, 141 is the elastic tail fin model device, 142 is the metal core plate, and 143 is the 3D foam. Detailed Implementation

[0065] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and technical solutions.

[0066] To verify the effectiveness of the invented multi-target point flutter response prediction method for aircraft tail fins based on elastic similarity transformation, this study focuses on... Figure 2 To address the tail flapping vibration problem of the fighter jet shown, a "rigid / missile combined" flapping wind tunnel test model device 1 was designed and tested. The flapping acceleration response at multiple target design points was predicted. The specific steps are as follows:

[0067] Step 1: Design of a "rigid / elastic combination" buffeting wind tunnel test model;

[0068] like Figure 3 As shown, the rigid fuselage 11 and rigid wing 12 of the "rigid / elastic combination" buffeting wind tunnel test model are made of 7075-T6 aluminum alloy to ensure geometric and flow field similarity. The tail component is a "rigid / elastic combination" design. The rigid tail wing 13 on the left is designed as a rigid structure, mainly used to measure the pulsating pressure on the surface of the tail component when buffeting occurs, and then used for dynamic aerodynamic load analysis. The elastic tail wing 14 on the right is a scaled-down elastic structure designed to obtain the dynamic response of the tail component under buffeting excitation.

[0069] Figure 3 In the middle, the rigid tail fin 13 is made of 30CrMnSiA high-strength steel and consists of two parts: the fin structure and the cover plate. Sixteen pairs (32 in total) of pressure measuring holes are symmetrically arranged along four chords on both sides of the fin, and pulsating pressure sensors 15 are installed at the corresponding positions to measure the pulsating pressure distribution on the surface of the tail fin component.

[0070] Figure 5 In this design, the flexible tail fin 14 is manufactured using a composite structure of a metal core plate 142 and a woven foam 143. The metal core plate 142 is made of 2mm thick 7075-T6 aluminum alloy and serves as the main load-bearing structure, providing the overall rigidity required for the flexible tail fin 14. The woven foam 143 is made of PMI-70 and is applied to the surface of the metal core plate 142 for flow straightening and shaping, ensuring that the flexible tail fin 14 has good aerodynamic geometric similarity to the actual tail fin structure in terms of shape.

[0071] H=8km and Ma=0.85 were selected as the target flight state points for the baseline design of the elastic tail fin 14, and the wind tunnel test wind speed V was used. m =40m / s, the three basic scales of the elastic tail fin 14 are as follows:

[0072] (19)

[0073] (20)

[0074] (twenty one)

[0075] Based on the three basic scales, the mass scale and frequency scale can be derived from equations (5) and (7):

[0076] (twenty two)

[0077] (twenty three)

[0078] Step 2: Buffeting wind tunnel test of the benchmark buffeting wind tunnel test model;

[0079] After completing the design and fabrication of the "rigid / elastic combination" buffeting wind tunnel test model, buffeting wind tunnel tests were conducted on the benchmark buffeting wind tunnel test model. The wind tunnel test section dimensions were 4m × 3m × 8m. The incoming flow velocity for the buffeting wind tunnel test was set according to the scaled-down version of elastic structure dynamics. =50m / s, to investigate the buffeting characteristics under high angle-of-attack flight conditions, the buffeting wind tunnel test started at an angle of attack of 20°, with a test condition set every 3°. Buffeting pulsation pressure data were recorded as follows: Figure 6 The data shown are the vibration acceleration response data. Figure 7 As shown.

[0080] Table 1 Actual wind tunnel test conditions

[0081]

[0082] Step 3: Construct a flexible similarity transformation model;

[0083] Establish a finite element model of the benchmark buffeting wind tunnel test model, such as Figure 8 As shown, modal analysis was performed on it. The modal frequency structure is shown in Table 2.

[0084] Table 2. Modal Frequency Table of Elastic Tail Fender (Baseline Flutter Wind Tunnel Test Model)

[0085]

[0086] based on Figure 8The finite element model shown outputs the mass normalized modal matrix, generalized mass matrix and generalized stiffness matrix, and together with the pulsating pressure of the benchmark buffeting wind tunnel test model, constructs the buffeting acceleration response equation of the benchmark buffeting wind tunnel test model shown in equation (9), and is used for subsequent transient response calculation.

[0087] Select the new target flight status, as shown in Table 3;

[0088] Table 3 Non-baseline actual flight conditions

[0089]

[0090] Based on Table 3 and equations (10) to (12), determine the generalized mass matrix and generalized stiffness matrix of the elastic similarity transformation model, and construct the vibration response motion equation (13) of the elastic similarity transformation model.

[0091] Step 4: Generation of buffeting response from "equivalent wind tunnel test";

[0092] The buffeting pulsation pressure zones measured in the buffeting wind tunnel test of the benchmark buffeting wind tunnel model are loaded onto the benchmark buffeting wind tunnel test model and the elastic similarity transformation model to obtain... and Extract the acceleration response measured in the buffeting wind tunnel test of the benchmark buffeting wind tunnel test model. Based on the selected target flight state, according to the formula , Generate the acceleration response of the elastic similarity transformation model “equivalent wind tunnel test”.

[0093] Step 5: Predict the multi-target point buffeting response of a real aircraft structure;

[0094] Based on the selected target flight state, the pulsating pressure data measured by the rigid tail 13 in the flutter wind tunnel test was converted to the actual aircraft structural scale and applied as input load to the original-size finite element model. Subsequently, transient response was solved using finite element software to obtain the RMS value of the acceleration dynamic response at the vertical tail tip. This result served as the baseline reference data and was designated as the control group. Based on the acceleration response scale of the selected target flight state, the RMS value of the acceleration response directly measured in the flutter wind tunnel test of the baseline flutter wind tunnel test model was... A direct similarity transformation is performed to obtain the corresponding actual aircraft-scale response result, denoted as the uncorrected buffeting acceleration response. A multi-target point response prediction method is used to construct an elastic similarity transformation model, generating the buffeting wind tunnel test acceleration response of this elastic similarity transformation model, and obtaining the RMS value of the acceleration response. The corrected buffet acceleration response is then converted to the actual aircraft structural scale corresponding to the target flight state. Error analysis is performed on the buffet acceleration responses before and after correction with the control group's baseline reference value. The comparison results are shown in Table 4. The relative errors before and after correction are plotted together as a scatter plot. Figure 9 As shown:

[0095] Table 4 Comparison of RMS values ​​of acceleration response in elastic similarity transformation models

[0096]

[0097] PSD analysis of the acceleration time-domain response was performed to verify whether the response results obtained by the multi-target point response prediction method conformed to the expected characteristics in the frequency domain. The dominant frequency error comparison is shown in Table 5 below. The acceleration response PSDs before and after correction under flight condition 1 were plotted together with the control group PSDs. Figure 10 It can be seen that the characteristics of the chattering acceleration response predicted based on the elastic similarity transformation model in the frequency domain are in line with expectations.

[0098] Table 5 Comparison of PSD Dominant Frequency Errors in Elastic Similarity Transformation Models

[0099] .

Claims

1. A method for predicting the multi-target point flutter response of an aircraft tail based on elastic similarity transformation, characterized in that, The steps are as follows: Step 1: Design of a "rigid / elastic combination" buffeting wind tunnel test model; The "rigid / elastic combination" buffeting wind tunnel test system includes a "rigid / elastic combination" buffeting wind tunnel test model device (1), a main support rod (2), a tail support rod (3), a main support rod angle of attack adaptation mechanism (4), and a tail support rod angle of attack adaptation mechanism (5). The main support rod angle of attack adaptation mechanism (4) and the tail support rod angle of attack adaptation mechanism (5) are respectively installed on the main support rod (2) and the tail support rod (3). The main support rod (2) and the tail support rod (3) are used to support the "rigid / elastic combination" buffeting wind tunnel test model device (1). Step 2: Buffeting wind tunnel test of the benchmark buffeting wind tunnel test model; Step 3: Construct a flexible similarity transformation model; Step 4: Generation of buffeting response from the elastic similarity transformation model "equivalent wind tunnel test"; Step 5: Predict the multi-target point flutter response at the actual aircraft scale; The "rigid / elastic combination" flutter wind tunnel test model device (1) includes a rigid fuselage (11), a rigid wing (12), a rigid tail (13), an elastic tail (14), a pulsating pressure sensor (15), and an acceleration sensor (16). The rigid tail (13) includes a rigid wing structure (133) and a cover plate (132). The cover plate (132) is interlocked with the rigid wing structure (133) to form a rigid tail model device (131). The rigid tail model device (131) is fixed to the rigid fuselage (11). The rigid tail (13) is designed according to the geometry of the real aircraft structure. Pulsating pressure sensors (15) are arranged on both sides of the tail to measure the flutter pulsation during the flutter wind tunnel test. Pressure; The elastic tail fin (14) includes an elastic tail fin model device (141), a metal core plate (142), and a woven foam (143), wherein the metal core plate (142) is located on the middle surface of the elastic tail fin (14) and provides elastic support; the woven foam (143) covers the metal core plate (142) and maintains the aerodynamic shape of the tail fin; the metal core plate (142) and the woven foam (143) together constitute the elastic tail fin model device (141), which is installed on the rigid fuselage (11); the elastic tail fin (14) is designed according to the scaled-down design of elastic structure dynamics, and an acceleration sensor (16) is arranged on the elastic tail fin (14) to measure the flutter acceleration response of the elastic tail fin (14) during the flutter wind tunnel test; The elastic tail (14) is designed on a scaled-down basis according to the dynamics of elastic structures. The basis for the similarity transformation is that the elastic tail (14) and the Strouhal number of the real aircraft structure are equal: （1）； In the formula, This represents the Strauhal number, which is the reduced frequency. Indicates angular frequency; Indicates the feature length; Indicates airflow velocity; the three scales used in the scaled design of the elastic tail fin (14) according to the dynamic scaling of the elastic structure are: （2）； （3）； （4）； in, For length ratio, For speed ratio, Density ratio, These are the length, inflow velocity, and air density of the "rigid / elastic combination" buffeting wind tunnel test model; These are the length of the actual aircraft structure, the incoming flow velocity, and the air density, respectively; from the scales of equations (2) to (4), the derived scales are as follows: （5）； （6）； （7）； in, , and These represent the mass ratio, stiffness ratio, and frequency ratio of the elastic tail (14) to the actual aircraft structure, respectively; These represent the mass, stiffness, and circular frequency of the elastic tail fin (14), respectively. These represent the mass, stiffness, and circular frequency of a real aircraft structure, respectively. When designing the elastic tail fin (14), the length of the "rigid / elastic combination" flutter wind tunnel test model is first determined based on the size of the wind tunnel and the test wind speed limit. Incoming flow velocity and air density Then, based on the length of the actual aircraft structure... Incoming flow velocity and air density Determine the scale in equations (2) to (4). , and Then, the derived scale is obtained according to equations (5) to (7). , and Thus, the mass of the "rigid / elastic combination" flutter wind tunnel test model, including the elastic tail fin (14), was determined. Stiffness Circular frequency ; The elastic tail model designed according to equations (2) to (7) for the reference target flight state is defined as the reference flutter wind tunnel test model, which corresponds to the altitude and Mach number of the reference flight state; the elastic tail (14) after the target flight state is changed is defined as the elastic similarity transformation model.

2. The method for predicting multi-target point flutter response of an aircraft tail based on elastic similarity transformation according to claim 1, characterized in that, The specific implementation process of step 2 is as follows: Complete the design and fabrication of the benchmark buffeting wind tunnel test model, and conduct buffeting wind tunnel tests on the benchmark buffeting wind tunnel test model; set the incoming flow velocity of the buffeting wind tunnel test according to the scale of elastic structure dynamics. The angle of attack range of the "rigid / elastic combination" buffeting wind tunnel test model is adjusted by the main support rod (2) and the tail support rod (3). , where m is the number of angle of attack changes in the buffeting wind tunnel test, and the buffeting wind tunnel test state is determined; the buffeting wind tunnel test of the benchmark buffeting wind tunnel test model is completed, and the buffeting pulsation pressure of the pulsation pressure sensor (15) and the buffeting acceleration response of the acceleration sensor (16) are recorded.

3. The method for predicting the multi-target point flutter response of an aircraft tail based on elastic similarity transformation according to claim 2, characterized in that, The specific implementation process of step 3 is as follows: Without considering the fluid-structure interaction effect, the buffeting response equation of the benchmark buffeting wind tunnel test model is: （8）； in, These are the mass matrix, damping matrix, and stiffness matrix of the benchmark flutter wind tunnel test model corresponding to the benchmark target flight state designed in step 1. They are obtained by performing finite element modeling on the actual designed benchmark flutter wind tunnel test model; the superscript 0 indicates the benchmark flutter wind tunnel test model. The displacement, velocity, and acceleration of the baseline buffeting wind tunnel test model in physical space; It is the buffeting pulsating pressure load vector measured by wind tunnel test, which is obtained by pulsating pressure sensor (15); According to the principle of modal superposition Equation (8) is then transformed into the generalized dynamic response equation in modal space: （9）； in, For the generalized mass matrix, For the generalized damping matrix, For generalized stiffness matrix, This is the generalized pulsating pressure load vector. It is the mass-normalized mode matrix. These are displacement, velocity, and acceleration in modal space; Given a fixed actual aircraft structure, it is assumed that the modal shapes of the baseline flutter wind tunnel test model and the elastic similarity transformation model after the target flight state changes are consistent, and the structural damping remains unchanged. The construction of the elastic similarity transformation model is based on the flutter wind tunnel test data of the baseline flutter wind tunnel test model, and the length scales of the two are equal. , where superscript The velocity ratio and density ratio represented by equations (3) and (4), and the mass ratio, stiffness ratio, and frequency ratio represented by equations (5)-(7) of the elastic similarity transformation model need to be re-determined according to the new target flight state; based on equations (5)~(7), and the mass normalized mode matrix of the benchmark flutter wind tunnel test model Generalized mass matrix and generalized stiffness matrix Construct the generalized mass matrix of the elastic similarity transformation model under the new target flight state. and generalized stiffness matrix : （10）； （11）； （12）； In equations (10) to (12) , and Let represent the generalized mass matrix, generalized stiffness matrix, and frequency of the elastic similarity transformation model, respectively. , and These represent the density ratio, velocity ratio, and frequency ratio of the elastic similarity transformation model, respectively; the lengths of the benchmark buffeting wind tunnel test model and the elastic similarity transformation model are consistent. With the aerodynamic shape of the actual aircraft structure remaining unchanged, the generalized pulsating pressure load vector before and after the elastic similarity transformation... The damping remains unchanged; it is assumed that the damping of the elastic similarity transformation model is consistent with that of the benchmark buffeting wind tunnel test model. Then, the generalized mass matrix based on the elastic similarity transformation model Generalized damping matrix Generalized stiffness matrix and generalized pulsating pressure load vector The response motion equations of the elastic similarity transformation model are as follows: （13）； Equation (13) is solved using different time integration methods to obtain the buffeting acceleration response of the elastic similarity transformation model that satisfies the new target flight state.

4. The method for predicting multi-target point flutter response of an aircraft tail based on elastic similarity transformation according to claim 3, characterized in that, The specific implementation process of step 4 is as follows: Assume that the buffeting acceleration response obtained from the buffeting wind tunnel test of the benchmark buffeting wind tunnel model is... The generalized pulsating pressure load vector obtained from the actual measurement of pulsating pressure. Solve (9) to obtain the acceleration. Then, based on the principle of modal superposition... To obtain the acceleration response in physical space The acceleration response obtained by solving the elastic similarity transformation model is: The buffeting acceleration response measured in the "equivalent wind tunnel test" using the elastic similarity transformation model is defined as follows: The four variables satisfy the following relationship: （14）； in, To take the root mean square; then: （15）； According to the principle of dimensional analysis, the response history times of the benchmark buffeting wind tunnel test model and the elastic similarity transformation model are related as follows: （16）； in, and These represent the response history times of the benchmark buffeting wind tunnel test model and the elastic phase transition model, respectively. and These represent the time ratios of the benchmark buffeting wind tunnel test model and the elastic phase transition model, respectively. and This represents the frequency ratio between the benchmark buffeting wind tunnel test model and the elastic similarity transformation model; and These represent the velocity ratios of the baseline buffeting wind tunnel test model and the elastic similarity transformation model, respectively. Measured acceleration response of the benchmark buffeting wind tunnel test model in a buffeting wind tunnel. Based on this, the wind tunnel test data of the benchmark buffeting wind tunnel test model are analyzed using equation (15). Amplitude scaling is performed, and the wind tunnel test response of the benchmark buffeting wind tunnel test model is evaluated using equation (16). By scaling the time, the buffeting acceleration response of the elastic similarity transformation model in the equivalent wind tunnel test is obtained. ; Experimental acceleration response of elastic similarity transformation model Based on the test data of the benchmark buffeting wind tunnel test model Based on this, calculations were performed using equations (15) and (16), without conducting new experimental tests for the new target flight state; through the analysis of... The transformation is performed to obtain the actual aircraft-scale acceleration response under the new target flight state corresponding to the elastic similarity transformation model.

5. The method for predicting the multi-target point flutter response of an aircraft tail based on elastic similarity transformation according to claim 4, characterized in that, The specific implementation process of step 5 is as follows: The acceleration response of the elastic similarity transformation model and the actual flight state satisfy the following proportional relationship: （17）； （18）； in, The proportional relationship between the RMS values ​​of the acceleration response. This represents the proportional relationship of the acceleration response power spectral density function.

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