Method, device, equipment and medium for determining characteristic values ​​of boundary layer instability of aircraft

Abstract

The present application discloses a method, apparatus, device, and medium for determining the eigenvalues ​​of boundary layer instability of an aircraft, and relates to the field of transition prediction, including: initializing on a grid surface of a three-dimensional hypersonic boundary layer of an aircraft based on a preset initialization strategy; determining a source point from grid points on the grid surface, comparing the quantitative difference in instability characteristics between the source point and adjacent grid points, and obtaining a first eigenvalue result based on a first comparison result and an initialization result; determining a target point from grid points on the object surface, comparing the quantitative difference in instability characteristics between the target point and adjacent grid points, and obtaining a second eigenvalue result based on a second comparison result and the first eigenvalue result; and determining a target eigenvalue result based on a third comparison result, the first eigenvalue result, and the second eigenvalue result by comparing the frequency difference in instability characteristics between all adjacent grid points, to complete transition prediction. The present application improves the efficiency of eigenvalue determination and the efficiency of transition prediction.

Description

Technical Field

[0001] The present invention relates to the field of transition prediction, and in particular to a method, device, equipment and medium for determining characteristic values ​​of boundary layer instability of an aircraft. Background Art

[0002] Currently, when applying the 3D eN method for transition prediction, boundary layer stability analysis typically involves solving for characteristic values ​​such as frequency, streamwise wavenumber, and spanwise wavenumber at all grid points on a boundary layer profile at a specific point on the surface. Traditional implementations require discretizing the stability equations at the grid point boundary layer profile, scattering a large number of points across the spectral space of the eigenvalues, and then manually selecting eigenvalues ​​that meet physical requirements. This approach is time-consuming, labor-intensive, and difficult to master, requiring a high level of analyst experience. Furthermore, since real-world geometries typically have tens or hundreds of thousands of surface grid points, completing a complete stability analysis of all these points could take days, making coupled flow field analysis even more challenging, far from meeting the requirements of aircraft design and development. Summary of the Invention

[0003] In view of this, the present invention aims to provide a method, apparatus, device, and medium for determining eigenvalues ​​of boundary layer instability for aircraft. These methods avoid the adverse effects of manual intervention and extensive spectral space searches in existing solutions, significantly improving the efficiency of eigenvalue determination while ensuring accuracy. This, in turn, improves the efficiency of predicting transitions in the three-dimensional hypersonic boundary layer of an aircraft, thereby meeting the needs of aircraft design and development. The specific solution is as follows:

[0004] In a first aspect, the present application provides a method for determining characteristic values ​​of boundary layer instability of an aircraft, comprising:

[0005] Based on a preset initialization strategy, eigenvalue initialization and non-physical eigenvalue identification and elimination are performed on the mesh surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft to determine the initialization result;

[0006] determining a plurality of source points from each object plane grid point on the grid surface, and comparing a difference in quantity of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result;

[0007] After obtaining the first eigenvalue result, determining a plurality of target points from the object plane grid points, and comparing the difference in the number of instability features between each of the target points and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result;

[0008] After obtaining the second eigenvalue result, the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane are compared, and a target eigenvalue result is determined based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result.

[0009] Optionally, the step of sequentially performing eigenvalue initialization and identifying and eliminating non-physical eigenvalues ​​on a grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy to determine an initialization result includes:

[0010] Based on the number of CPU cores, several initial guess points are set on the mesh surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft;

[0011] Scattering points in the eigenvalue spectrum space of the initial guess points, and guessing the initial eigenvalues ​​of the initial guess points based on the scattered points in the eigenvalue spectrum space, so as to determine the initial eigenvalues ​​corresponding to the initial guess points;

[0012] Invalid non-physical eigenvalues ​​in the initial eigenvalues ​​are determined based on a preset non-physical eigenvalue identification strategy, and a non-physical eigenvalue elimination operation is triggered to determine an initialization result.

[0013] Optionally, determining invalid non-physical eigenvalues ​​in the initial eigenvalues ​​based on a preset non-physical eigenvalue identification strategy and triggering a non-physical eigenvalue removal operation includes:

[0014] Performing a eigenvalue validity check on each of the initial eigenvalues ​​and determining whether each of the initial eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding first check result, thereby completing a first non-physical eigenvalue elimination operation and obtaining corresponding first remaining eigenvalue information;

[0015] Performing an eigenvalue validity check on the first eigenvalues ​​in the first remaining eigenvalue information, and determining whether each of the first eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding second check result, thereby completing a second non-physical eigenvalue elimination operation and obtaining corresponding second remaining eigenvalue information;

[0016] Performing a grid encryption test on the second eigenvalue in the second remaining eigenvalue information, and determining whether the second eigenvalue belongs to the non-physical eigenvalue based on a corresponding third test result, thereby completing a third non-physical eigenvalue elimination operation and obtaining corresponding third remaining eigenvalue information;

[0017] The eigenvalue with the highest instability in the third remaining eigenvalue information is determined and retained based on a preset eigenvalue processing rule to determine the initialization result.

[0018] Optionally, determining a plurality of source points from each object plane grid point on the grid surface, and comparing a difference in quantity of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result, includes:

[0019] By analyzing the eigenvalues ​​of each of the object plane grid points on the grid surface, the object plane grid points with valid eigenvalues ​​are used as source points;

[0020] Comparing the number of instability features of each source point with each adjacent object plane grid point to determine a first comparison result;

[0021] If the first comparison result indicates that there are several first target adjacent grid points whose number of instability features is smaller than the number of instability features of the corresponding source point, then taking the first target adjacent grid point as the target point;

[0022] Assigning the characteristic value information of the corresponding source point to the target point based on the initialization result to obtain a first target point after assignment, and triggering a corresponding marking operation on the first target point;

[0023] Adding the first target point to a task queue to be solved to determine a corresponding first target task queue;

[0024] Threads are allocated to each of the first target points in the first target task queue according to the number of cores of the central processing unit, and characteristic values ​​of each of the first target points are solved in parallel based on each thread to determine a first characteristic value result.

[0025] Optionally, determining a plurality of target points from the object plane grid points, and comparing a difference in quantity of instability features between each target point and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result, includes:

[0026] After completing the first eigenvalue determination operation, screening out all the object plane grid points on the grid surface that have not been assigned a value, and using them as the target points;

[0027] Comparing the number of instability features of each target point with each adjacent object plane grid point to determine a second comparison result;

[0028] If the second comparison result indicates that there are a number of second target adjacent grid points whose number of instability features is greater than the number of instability features of the target point, then taking the second target adjacent grid points as the source points;

[0029] Assigning the eigenvalue information of the corresponding source point to the corresponding target point based on the first eigenvalue result to obtain a second target point after assignment, and triggering a corresponding marking operation on the second target point;

[0030] Adding the second target point to a task queue to be solved to determine a corresponding second target task queue;

[0031] A thread is allocated to each second target point in the second target task queue according to the number of cores of the central processing unit, and the characteristic value of each second target point is solved in parallel based on each thread to determine a second characteristic value result.

[0032] Optionally, comparing the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane, and determining the target eigenvalue result based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, includes:

[0033] After completing the second eigenvalue determination operation, for each object plane grid point on the grid surface, triggering a frequency difference of an instability feature between each object plane grid point and a corresponding adjacent object plane grid point to determine a third comparison result;

[0034] If the third comparison result indicates that there are a number of adjacent object plane grid points having target characteristic values ​​with different frequencies from the corresponding object plane grid points, then the adjacent object plane grid points are used as the source points, and the corresponding object plane grid points are used as the target points;

[0035] Assigning the target eigenvalues ​​with different frequencies in the source points to the target points based on the first eigenvalue results and the second eigenvalue results to obtain a third target point after assignment, and triggering a corresponding marking operation on the third target point;

[0036] Adding the third target point to the task queue to be solved to determine the corresponding third target task queue;

[0037] Allocating threads to each of the third target points in the third target task queue according to the number of cores of the central processing unit, and solving the characteristic values ​​of each of the third target points in parallel based on the threads to determine a target characteristic value result;

[0038] The target characteristic value results include the target frequency value, target streamwise wave value and target spanwise wave value of each object surface grid point on the grid surface.

[0039] In a second aspect, the present application provides a device for determining a characteristic value of boundary layer instability of an aircraft, comprising:

[0040] An initialization module is used to perform eigenvalue initialization and identification and elimination of non-physical eigenvalues ​​on the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy to determine an initialization result;

[0041] a first eigenvalue determination module, configured to determine a plurality of source points from each object plane grid point on the grid surface, and compare a difference in the number of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result;

[0042] a second eigenvalue determination module, configured to, after obtaining the first eigenvalue result, determine a plurality of target points from the object plane grid points, and compare the difference in the quantity of instability features between each of the target points and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result;

[0043] A target eigenvalue determination module is configured to, after obtaining the second eigenvalue result, compare the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane, and determine a target eigenvalue result based on a corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result.

[0044] Optionally, the initialization module includes:

[0045] A guess point setting unit, configured to set a number of initial guess points on a grid surface of a three-dimensional hypersonic boundary layer corresponding to the aircraft based on the number of CPU cores;

[0046] a point scattering guessing unit, configured to scatter points in the eigenvalue spectrum space of the initial guessed points, and guess the initial eigenvalues ​​of the initial guessed points based on the scattered points in the eigenvalue spectrum space, so as to determine the initial eigenvalues ​​corresponding to the initial guessed points;

[0047] The initialization result determination unit is used to determine invalid non-physical eigenvalues ​​in the initial eigenvalues ​​based on a preset non-physical eigenvalue identification strategy, and trigger a non-physical eigenvalue elimination operation to determine an initialization result.

[0048] In a third aspect, the present application provides an electronic device, comprising:

[0049] Memory, used to store computer programs;

[0050] The processor is configured to execute the computer program to implement the steps of the aforementioned method for determining characteristic values ​​of boundary layer instability of an aircraft.

[0051] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the steps of the aforementioned method for determining characteristic values ​​of boundary layer instability of an aircraft.

[0052] It can be seen that in the present application, based on the preset initialization strategy, eigenvalue initialization and identification and elimination of non-physical eigenvalues ​​are performed in sequence on the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft to determine the initialization result; a number of source points are determined from each object surface grid point on the grid surface, and the quantitative difference of the instability characteristics between each source point and the adjacent object surface grid point is compared to perform a first eigenvalue determination operation based on the corresponding first comparison result and the initialization result; after obtaining the first eigenvalue result, a number of target points are determined from the object surface grid points, and the quantitative difference of the instability characteristics between each target point and the adjacent object surface grid point is compared to perform a second eigenvalue determination operation based on the corresponding second comparison result and the first eigenvalue result; after obtaining the second eigenvalue result, the frequency difference of the instability characteristics between all adjacent object surface grid points on the grid surface is compared, and a target eigenvalue result is determined based on the corresponding third comparison result, the first eigenvalue result and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result. That is, the present application first initializes the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy. Then, based on the quantitative difference in instability eigenvalues ​​between adjacent object surface grid points and the initialization result, the corresponding eigenvalue is determined to complete the first eigenvalue determination operation and the second eigenvalue determination operation. The frequency difference in instability characteristics between all adjacent object surface grid points on the grid surface is then compared to determine the target eigenvalue result, which can then be used to predict the transition of the three-dimensional hypersonic boundary layer corresponding to the aircraft. This avoids the adverse effects of manual intervention and extensive spectral space searches in existing solutions, greatly improves the efficiency of eigenvalue determination while ensuring accuracy, and thus improves the efficiency of transition prediction of the three-dimensional hypersonic boundary layer of the aircraft, thereby meeting the needs of aircraft design and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0054] Figure 1A flow chart of a method for determining characteristic values ​​of boundary layer instability of an aircraft provided in this application;

[0055] Figure 2 A schematic diagram of the eigenvalue propagation and diffusion process provided in this application;

[0056] Figure 3 A schematic diagram of the frequency difference comparison and propagation diffusion of a characteristic value provided in this application;

[0057] Figure 4 A schematic diagram of the structure of a device for determining characteristic values ​​of boundary layer instability of an aircraft provided in this application;

[0058] Figure 5 This is a structural diagram of an electronic device provided in this application. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] Currently, when applying the 3D eN method for transition prediction, boundary layer stability analysis typically involves solving for characteristic values ​​such as frequency, streamwise wavenumber, and spanwise wavenumber at all grid points on a boundary layer profile at a specific point on the surface. Traditional implementations require discretizing the stability equations at the grid point boundary layer profile, scattering a large number of points across the spectral space of the eigenvalues, and then manually selecting eigenvalues ​​that meet physical requirements. This approach is time-consuming, labor-intensive, and difficult to master, requiring a high level of analyst experience. Furthermore, since real-world geometries typically have tens or hundreds of thousands of surface grid points, completing a complete stability analysis of all these points could take days, making coupled flow field analysis even more challenging, far from meeting the requirements of aircraft design and development.

[0061] To this end, the present application provides a solution for determining the characteristic values ​​of boundary layer instability of an aircraft, which effectively improves the efficiency of characteristic value determination and the efficiency of transition prediction.

[0062] See also Figure 1 As shown, an embodiment of the present invention discloses a method for determining a characteristic value of boundary layer instability of an aircraft, comprising:

[0063] Step S11: Based on a preset initialization strategy, eigenvalue initialization and identification and elimination of non-physical eigenvalues ​​are performed in sequence on the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft to determine an initialization result.

[0064] In this embodiment, before determining eigenvalues, initialization measures are required. Initial eigenvalues ​​are then estimated by setting a number of initial guess points (generally equal to the number of CPU cores) on the mesh surface to be determined. Initial eigenvalues ​​are then estimated by scattering these initial guess points within the eigenvalue spectrum space. Non-physical eigenvalues ​​are then eliminated, and the most unstable eigenvalues ​​are retained. The specific steps are as follows: Initially, a number of initial guess points are set on the mesh surface corresponding to the three-dimensional hypersonic boundary layer of the aircraft based on the number of CPU cores; points are scattered within the eigenvalue spectrum space of these initial guess points, and initial eigenvalues ​​are estimated for these initial guess points based on the scattered points within the eigenvalue spectrum space to determine the initial eigenvalues ​​corresponding to each initial guess point; Invalid non-physical eigenvalues ​​within these initial eigenvalues ​​are identified based on a pre-set non-physical eigenvalue identification strategy, and a non-physical eigenvalue elimination process is triggered to determine the initialization results.

[0065] Furthermore, regarding the determination of the initial eigenvalues, in the eigenvalue spectrum space of these initial guess points, for each point selected within the space, the corresponding imaginary part is solved based on the real part value of the initial flow wave value and the real part value of the initial span wave value at that point. Then, the complete initial flow wave value and initial span wave value for each initial guess point are determined in combination with the obtained imaginary part. It can be understood that the set of initial eigenvalues ​​corresponding to each initial guess point includes the initial perturbation frequency value, the initial flow wave value, and the initial span wave value. The initial perturbation frequency value is a real number, and the initial flow wave value and the initial span wave value are complex numbers. The real part represents the wave number in the flow direction and span direction, respectively, while the imaginary part represents the amplitude growth rate.

[0066] Further, regarding the triggering of the non-physical eigenvalue elimination operation, in this embodiment, the first non-physical eigenvalue elimination operation is completed by first performing an eigenvalue validity check on each of the initial eigenvalues, and judging whether each of the initial eigenvalues ​​belongs to the non-physical eigenvalue based on the corresponding first check result, so as to obtain the corresponding first remaining eigenvalue information; the second non-physical eigenvalue elimination operation is completed by performing an eigenvalue validity check on the first eigenvalue in the first remaining eigenvalue information, and judging whether each of the first eigenvalues ​​belongs to the non-physical eigenvalue based on the corresponding second check result, so as to obtain the corresponding second remaining eigenvalue information; the third non-physical eigenvalue elimination operation is completed by performing a grid encryption check on the second eigenvalue in the second remaining eigenvalue information, and judging whether the second eigenvalue belongs to the non-physical eigenvalue based on the corresponding third check result, so as to obtain the corresponding third remaining eigenvalue information; the eigenvalue with the highest instability in the third remaining eigenvalue information is determined and retained based on the preset eigenvalue processing rules to determine the initialization result. It is understandable that since the initial eigenvalues ​​obtained initially contain non-physical eigenvalues, only a small number of eigenvalues ​​are real. The initial eigenvalue solutions obtained in this way cannot be directly used to solve real physical problems, and therefore require some processing. Non-physical eigenvalues, i.e., unreal values, can be considered invalid eigenvalues. It is important to understand that the first validity test in the above process tests whether the perturbation growth rate of the perturbation wave corresponding to each set of initial eigenvalues ​​(each initial guess point has one set) is greater than a first preset value. If so, the set of initial eigenvalues ​​is used as the non-physical eigenvalue. The first preset value can be a threshold value or a preset multiple of the maximum value among several groups of flow directions, spanwise wavenumbers, and perturbation frequencies corresponding to the perturbation wave. The second validity check in the above process is to determine the non-physical eigenvalue by using the validity check of the characteristic function (where the initial eigenvalue has a corresponding characteristic function, which can be determined when the eigenvalue is obtained using the eigenvalue spectrum space), and to check whether the maximum value of the absolute value of the first function value corresponding to the initial velocity characteristic function in the characteristic function corresponding to the first eigenvalue is greater than the second preset value, and / or the number of fluctuations of the second function value corresponding to the initial density characteristic function is greater than the third preset value. If so, it is determined to be a non-physical eigenvalue. The second grid encryption test in the above process first increases the number of grids and obtains the target characteristic function of each group of second eigenvalues ​​based on the new grid, and then uses the correlation between the characteristic function corresponding to each group of second eigenvalues ​​and the target characteristic function to determine several invalid groups of non-physical eigenvalues.

[0067] At the same time, after eliminating all non-physical eigenvalues, the target disturbance frequency and target spanwise wavenumber when the disturbance growth rate meets the preset conditions can be determined through the disturbance frequency in each valid group of third eigenvalues ​​in the third remaining eigenvalue information and the spanwise wavenumber in the spanwise complex wavenumber in each group of third eigenvalues, and the corresponding target eigenvalues ​​can be obtained based on the target disturbance frequency and the target spanwise wavenumber, so that several groups of eigenvalues ​​with the highest instability (i.e., the local maximum growth rate) can be obtained, and these several groups of eigenvalues ​​with the highest instability can be used as initialization results to participate in subsequent operations.

[0068] In addition, it should be understood that when the 3D eN method is used for transition prediction, it is assumed that there are disturbance waves of the following form in the boundary layer: :

[0069] .

[0070] Where x is the coordinate of the stream direction, y is the coordinate of the wall normal, z is the coordinate of the span direction, and t represents time. are the eigenvalues ​​of the stability equations. is the perturbation frequency, a real number. 、 is a complex number, the real part represents the wave number in the stream direction and span direction respectively, while the imaginary part represents the amplitude growth rate, i is the imaginary unit, is the disturbance distribution function, which is a function of y only, A is the disturbance amplitude, is the complex conjugate. A combination of determines a disturbance wave, and the existence of the corresponding characteristic function solution is related to the set of eigenvalues. When small disturbance waves of various frequencies in the boundary layer propagate downstream, they will be amplified when entering the unstable region. Starting from the time the disturbance wave enters the unstable region, the cumulative linear amplification factor is calculated by integrating along the downstream direction. :

[0071] .

[0072] in is the position where the disturbance starts to grow, S is the arc length of the disturbance propagation path, is the growth rate along the disturbance propagation path. The value is for all frequencies and wave number The envelope of the N value obtained , the position where the cumulative amplification reaches a given threshold is the location where the transition occurs. Substituting the above-mentioned small perturbation in the form of a traveling wave into the NS equations (Navier-Stokes equations) and numerically discretizing it using the Malik method (i.e., the Perona-Malik equations) yields a set of linear equations containing the perturbation wave number:

[0073] .

[0074] When predicting transitions, it is necessary to solve this equation to determine the corresponding eigenvalue. In this embodiment, a simple modification is made to the serial procedure for solving the eigenvalue of the stability equation. The specific eigenvalue solution process based on the initialization result will be described later.

[0075] Step S12: determining a plurality of source points from each object surface grid point on the grid surface, and comparing the difference in the number of instability features between each source point and the adjacent object surface grid points, so as to perform a first eigenvalue determination operation based on the corresponding first comparison result and the initialization result.

[0076] Combine Figure 2 The partial grid surface shown in the figure (the red points in the figure are source points, and the green points are target points). After determining the initialization result, this embodiment first propagates and diffuses the eigenvalue information, that is, by analyzing the eigenvalues ​​of each object surface grid point on the grid surface, the object surface grid point with a valid eigenvalue is used as the source point; each source point is compared with each adjacent object surface grid point in terms of the number of instability features to determine a first comparison result; if the first comparison result indicates that there are several first target adjacent grid points with a smaller number of instability features than the corresponding source point, the first target adjacent grid point is used as the target point; based on the initialization result, the eigenvalue information of the corresponding source point is assigned to the target point to obtain a first target point after assignment, and a corresponding marking operation is triggered for the first target point; the first target point is added to a task queue to be solved to determine a corresponding first target task queue; threads are allocated to each first target point in the first target task queue according to the number of CPU cores, and the eigenvalues ​​of each first target point are solved in parallel based on each thread to determine a first eigenvalue result. That is to say, all the surface grid points on the grid surface are traversed, and points with valid eigenvalues ​​are screened out as source points, that is, the surface grid points corresponding to each set of valid eigenvalues ​​in the initialization result. For each source point, if the number of unstable eigenvalues ​​of one of its neighboring points is less than that of the source point, then the neighboring point is used as the target point, and the eigenvalue of the source point is assigned to the target point from the initialization result. The target point is added to the task queue to be solved and marked as processed. The task queues of all the target points that have been added are constructed into a thread pool, and threads are allocated according to the number of CPU cores to solve the eigenvalue problems of each target point in the task queue in parallel. This process is repeated until no target point to be processed is found. It should be understood that when executing the eN method for three-dimensional flow fields, each surface grid point corresponds to a boundary layer profile. Each target point corresponds to a thread.

[0077] Step S13: After obtaining the first eigenvalue result, determine several target points from the object surface grid points, and compare the difference in the number of instability characteristics between each target point and the adjacent object surface grid points, so as to perform a second eigenvalue determination operation based on the corresponding second comparison result and the first eigenvalue result.

[0078] In this embodiment, after the propagation and diffusion of the eigenvalues ​​are completed, the eigenvalues ​​are aggregated and supplemented. The specific steps are as follows: after completing the first eigenvalue determination operation, all the object surface grid points on the grid surface that have not been assigned values ​​are screened out and used as the target points; the number of instability features of each target point is compared with the number of instability features of each adjacent object surface grid point to determine a second comparison result; if the second comparison result shows that the number of instability features of several second target adjacent grid points is greater than the number of instability features of the target point, the second target adjacent grid point is used as the source point; based on the first eigenvalue result, the eigenvalue information of the corresponding source point is assigned to the corresponding target point to obtain the assigned second target point, and the corresponding marking operation is triggered for the second target point; the second target point is added to the task queue to be solved to determine the corresponding second target task queue; threads are allocated to each second target point in the second target task queue according to the number of CPU cores, and the eigenvalues ​​of each second target point are solved in parallel based on each thread to determine the second eigenvalue result. In other words, after traversing all object surface grid points and filtering out the points obtained in step S12, all remaining unprocessed points are designated as target points. For each target point, its neighboring points are searched. If a neighboring point has more eigenvalues ​​than the target point, the neighboring point is marked as a source point, and the source point's eigenvalue is assigned to the target point from the first eigenvalue result. All task queues containing target points are constructed into a thread pool, with threads allocated based on the number of CPU cores to solve the eigenvalue problem for each target point in the task queue in parallel. This update process is repeated until no unprocessed target points are found.

[0079] Step S14: After obtaining the second eigenvalue result, by comparing the frequency differences of the instability characteristics between all adjacent object surface grid points on the grid surface, and determining a target eigenvalue result based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, the transition prediction of the three-dimensional hypersonic boundary layer is completed based on the target eigenvalue result.

[0080] Combine Figure 3As shown, after completing the aggregation and supplementation of the eigenvalues, the frequency diffusion of the eigenvalues ​​is performed. The specific relevant steps are as follows: after completing the second eigenvalue determination operation, for each of the object surface grid points on the grid surface, the frequency difference of the instability characteristics between each of the object surface grid points and the corresponding adjacent object surface grid points is triggered to determine a third comparison result; if the third comparison result shows that there are several adjacent object surface grid points with target eigenvalues ​​different from the frequency of the corresponding object surface grid point, then the adjacent object surface grid points are used as the source points and the corresponding object surface grid points are used as the target points; based on the first eigenvalue result and the third eigenvalue result, the frequency difference of the instability characteristics between each of the object surface grid points and the corresponding object surface grid points is triggered to determine a third comparison result; if the third comparison result shows that there are several adjacent object surface grid points with target eigenvalues ​​different from the frequency of the corresponding object surface grid points, then the adjacent object surface grid points are used as the source points and the corresponding object surface grid points are used as the target points. The target eigenvalue result is assigned to the target point with a different frequency from the source point to obtain a third target point after the assignment, and a corresponding marking operation is triggered for the third target point. The third target point is added to a task queue to be solved to determine the corresponding third target task queue. Threads are allocated to each of the third target points in the third target task queue based on the number of CPU cores, and the eigenvalues ​​of each of the third target points are solved in parallel based on each thread to determine a target eigenvalue result. The target eigenvalue result includes the target frequency value, target streamwise wavenumber value, and target spanwise wavenumber value for each object surface grid point on the grid surface. In other words, all object surface grid points are traversed, and the eigenvalue frequency difference between each grid point and its neighboring points is compared. If a neighboring point is found to have an eigenvalue with a different frequency, the neighboring point is marked as a source point, the point is marked as a target point, the eigenvalue of the different frequency from the source point is assigned to the target point, and the target point is marked as processed. All task queues for the added target points are constructed into a thread pool, and threads are allocated based on the number of CPU cores to solve the eigenvalue problem for each target point in the task queue in parallel. This updating process is repeated until no unprocessed target points are found.

[0081] In summary, this embodiment employs the principle of neighboring propagation and diffusion of eigenvalue information. By comparing the number and frequency of effective eigenvalues ​​between adjacent grid points, the eigenvalue information is iteratively calculated between local adjacent grid points to achieve eigenvalue propagation and diffusion. This avoids the spectral space calculation of matrix eigenvalues ​​at each grid point and the extensive manual screening process. Furthermore, a parallel computing strategy is utilized to gradually update and solve the eigenvalues ​​of different surface grid points across the entire three-dimensional flow field. This significantly improves the speed of three-dimensional eigenvalue solution by simply modifying the serial procedure for solving the stability equation eigenvalues. Furthermore, this embodiment's solution can significantly shorten the time required for complex three-dimensional eN stability analysis and transition prediction to within a few hours.

[0082] As can be seen, the present application first initializes the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy. Then, based on the quantitative difference in instability eigenvalues ​​between adjacent object surface grid points and the initialization result, the corresponding eigenvalue is determined to complete the first eigenvalue determination operation and the second eigenvalue determination operation. The frequency difference in instability characteristics between all adjacent object surface grid points on the grid surface is then compared to determine the target eigenvalue result, so that the target eigenvalue result can be used to predict the transition of the three-dimensional hypersonic boundary layer corresponding to the aircraft. This avoids the adverse effects of manual intervention and extensive spectral space searches in existing solutions, greatly improves the efficiency of eigenvalue determination while ensuring accuracy, and thus improves the efficiency of transition prediction of the three-dimensional hypersonic boundary layer of the aircraft, thereby meeting the needs of aircraft design and development.

[0083] See also Figure 4 As shown, the embodiment of the present application also discloses a device for determining a characteristic value of boundary layer instability of an aircraft, including:

[0084] An initialization module 11 is configured to perform eigenvalue initialization and identification and elimination of non-physical eigenvalues ​​on a grid surface of a three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy to determine an initialization result;

[0085] a first eigenvalue determining module 12, configured to determine a plurality of source points from each object plane grid point on the grid surface, and compare a quantity difference of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determining operation based on a corresponding first comparison result and the initialization result;

[0086] a second eigenvalue determination module 13 configured to, after obtaining the first eigenvalue result, determine a plurality of target points from the object plane grid points, and compare the difference in the number of instability features between each of the target points and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on the corresponding second comparison result and the first eigenvalue result;

[0087] The target eigenvalue determination module 14 is configured to, after obtaining the second eigenvalue result, compare the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane, and determine a target eigenvalue result based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result.

[0088] As can be seen, the present application first initializes the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy. Then, based on the quantitative difference in the instability eigenvalues ​​between adjacent object surface grid points and the initialization result, the corresponding eigenvalue is determined to complete the first eigenvalue determination operation and the second eigenvalue determination operation. Then, the frequency difference of the instability characteristics between all adjacent object surface grid points on the grid surface is compared to determine the target eigenvalue result, so that the target eigenvalue result can be used to predict the transition of the three-dimensional hypersonic boundary layer corresponding to the aircraft. In this way, the adverse effects caused by manual intervention and large-scale spectral space searches in existing solutions can be avoided. While ensuring accuracy, the efficiency of eigenvalue determination is improved, thereby improving the efficiency of transition prediction of the three-dimensional hypersonic boundary layer of the aircraft to meet the needs of aircraft design and development.

[0089] In some specific embodiments, the initialization module 11 may specifically include:

[0090] A guess point setting unit, configured to set a number of initial guess points on a grid surface of a three-dimensional hypersonic boundary layer corresponding to the aircraft based on the number of CPU cores;

[0091] a point scattering guessing unit, configured to scatter points in the eigenvalue spectrum space of the initial guessed points, and guess the initial eigenvalues ​​of the initial guessed points based on the scattered points in the eigenvalue spectrum space, so as to determine the initial eigenvalues ​​corresponding to the initial guessed points;

[0092] The initialization result determination unit is used to determine invalid non-physical eigenvalues ​​in the initial eigenvalues ​​based on a preset non-physical eigenvalue identification strategy, and trigger a non-physical eigenvalue elimination operation to determine an initialization result.

[0093] In some specific embodiments, the initialization result determination unit may specifically include:

[0094] a first elimination subunit, configured to perform an eigenvalue validity check on each of the initial eigenvalues ​​and determine whether each of the initial eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding first test result, so as to complete a first non-physical eigenvalue elimination operation and obtain corresponding first remaining eigenvalue information;

[0095] a second elimination subunit, configured to perform an eigenvalue validity check on the first eigenvalues ​​in the first remaining eigenvalue information, and determine whether each of the first eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding second verification result, so as to complete a second non-physical eigenvalue elimination operation and obtain corresponding second remaining eigenvalue information;

[0096] a third elimination subunit, configured to perform a grid encryption test on the second eigenvalue in the second remaining eigenvalue information, and determine whether the second eigenvalue belongs to the non-physical eigenvalue based on a corresponding third test result, so as to complete a third non-physical eigenvalue elimination operation and obtain corresponding third remaining eigenvalue information;

[0097] A result determination subunit is configured to determine and retain the eigenvalue with the highest instability in the third remaining eigenvalue information based on a preset eigenvalue processing rule to determine the initialization result.

[0098] In some specific embodiments, the first feature value determination module 12 may specifically include:

[0099] a first source point determination unit, configured to analyze the eigenvalues ​​of the object plane grid points on the grid surface and select the object plane grid points with valid eigenvalues ​​as source points;

[0100] a first comparison unit, configured to compare the number of instability features between each source point and each adjacent object plane grid point to determine a first comparison result;

[0101] a target point determining unit, configured to use the first target adjacent grid point as the target point if the first comparison result indicates that there are several first target adjacent grid points whose number of instability features is smaller than the number of instability features of the corresponding source point;

[0102] a first assignment unit, configured to assign the feature value information of the corresponding source point to the target point based on the initialization result to obtain a first target point after assignment, and trigger a corresponding marking operation on the first target point;

[0103] A first task queue determining unit, configured to add the first target point to a task queue to be solved, so as to determine a corresponding first target task queue;

[0104] The first eigenvalue determining unit is configured to allocate threads to each of the first target points in the first target task queue according to the number of cores of the central processing unit, and solve the eigenvalues ​​of each of the first target points in parallel based on each thread to determine a first eigenvalue result.

[0105] In some specific embodiments, the second characteristic value determination module 13 may specifically include:

[0106] a target point screening unit, configured to screen out all the object plane grid points on the grid surface that have not been assigned a value after completing the first eigenvalue determination operation, and use them as the target points;

[0107] a second comparison unit, configured to compare the number of instability features of each target point with each adjacent object plane grid point to determine a second comparison result;

[0108] a second source point determining unit configured to use the second target adjacent grid points as the source points if the second comparison result indicates that there are a number of second target adjacent grid points whose number of instability features is greater than the number of instability features of the target point;

[0109] a second assigning unit, configured to assign the eigenvalue information of the corresponding source point to the corresponding target point based on the first eigenvalue result, so as to obtain a second target point after assignment, and trigger a corresponding marking operation on the second target point;

[0110] A second task queue determining unit, configured to add the second target point to a task queue to be solved, so as to determine a corresponding second target task queue;

[0111] The second eigenvalue determining unit is used to allocate threads to each second target point in the second target task queue according to the number of cores of the central processing unit, and solve the eigenvalue of each second target point in parallel based on each thread to determine a second eigenvalue result.

[0112] In some specific embodiments, the target feature value determination module 14 may specifically include:

[0113] a third comparing unit, configured to, after completing the second eigenvalue determination operation, trigger, for each object plane grid point on the grid surface, a frequency difference of an instability feature between each object plane grid point and a corresponding adjacent object plane grid point, to determine a third comparison result;

[0114] a point processing unit, configured to, if the third comparison result indicates that there are a number of adjacent object plane grid points having target characteristic values ​​different in frequency from the corresponding object plane grid point, use the adjacent object plane grid points as the source points and use the corresponding object plane grid points as the target points;

[0115] a third assignment unit, configured to assign the target eigenvalue with different frequencies in the source point to the target point based on the first eigenvalue result and the second eigenvalue result, so as to obtain a third target point after assignment, and trigger a corresponding marking operation on the third target point;

[0116] A third task queue determining unit, configured to add the third target point to the task queue to be solved, so as to determine a corresponding third target task queue;

[0117] a target characteristic value determining unit, configured to allocate threads to each of the third target points in the third target task queue according to the number of cores of the central processing unit, and solve the characteristic values ​​of each of the third target points in parallel based on the threads to determine a target characteristic value result;

[0118] The target characteristic value results include the target frequency value, target streamwise wave value and target spanwise wave value of each object surface grid point on the grid surface.

[0119] Furthermore, the embodiment of the present application also discloses an electronic device, Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram should not be considered as any limitation to the scope of application of the present application.

[0120] Figure 5 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the method for determining the characteristic value of boundary layer instability of an aircraft disclosed in any of the aforementioned embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0121] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0122] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0123] The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, and can be Windows Server, NetWare, Unix, Linux, etc. In addition to including a computer program capable of implementing the method for determining the characteristic value of boundary layer instability of an aircraft performed by the electronic device 20 as disclosed in any of the aforementioned embodiments, the computer program 222 may further include computer programs capable of implementing other specific tasks.

[0124] Furthermore, this application discloses a computer-readable storage medium for storing a computer program. When executed by a processor, the computer program implements the aforementioned method for determining characteristic values ​​of boundary layer instability of an aircraft. The specific steps of this method can be found in the aforementioned embodiments and are not further detailed here.

[0125] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0126] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0127] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0128] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0129] The above is a detailed introduction to the technical solution provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the ideas of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for determining characteristic values ​​of boundary layer instability of an aircraft, characterized in that: include: Based on a preset initialization strategy, eigenvalue initialization and non-physical eigenvalue identification and elimination are performed on the mesh surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft to determine the initialization result; determining a plurality of source points from each object plane grid point on the grid surface, and comparing a difference in quantity of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result; After obtaining the first eigenvalue result, determining a plurality of target points from the object plane grid points, and comparing the difference in the number of instability features between each of the target points and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result; After obtaining the second eigenvalue result, comparing the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane, and determining a target eigenvalue result based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result; The method of performing eigenvalue initialization and identifying and eliminating non-physical eigenvalues ​​on the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy to determine the initialization result includes: Based on the number of CPU cores, several initial guess points are set on the mesh surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft; Scattering points in the eigenvalue spectrum space of the initial guess points, and guessing the initial eigenvalues ​​of the initial guess points based on the scattered points in the eigenvalue spectrum space, so as to determine the initial eigenvalues ​​corresponding to the initial guess points; Invalid non-physical eigenvalues ​​in the initial eigenvalues ​​are determined based on a preset non-physical eigenvalue identification strategy, and a non-physical eigenvalue elimination operation is triggered to determine an initialization result.

2. The method for determining characteristic values ​​of boundary layer instability of an aircraft according to claim 1, characterized in that: The determining of invalid non-physical eigenvalues ​​in the initial eigenvalues ​​based on a preset non-physical eigenvalue identification strategy and triggering a non-physical eigenvalue elimination operation includes: Performing a eigenvalue validity check on each of the initial eigenvalues ​​and determining whether each of the initial eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding first check result, thereby completing a first non-physical eigenvalue elimination operation and obtaining corresponding first remaining eigenvalue information; Performing an eigenvalue validity check on the first eigenvalues ​​in the first remaining eigenvalue information, and determining whether each of the first eigenvalues ​​belongs to the non-physical eigenvalue based on a corresponding second check result, thereby completing a second non-physical eigenvalue elimination operation and obtaining corresponding second remaining eigenvalue information; Performing a grid encryption test on the second eigenvalue in the second remaining eigenvalue information, and determining whether the second eigenvalue belongs to the non-physical eigenvalue based on a corresponding third test result, thereby completing a third non-physical eigenvalue elimination operation and obtaining corresponding third remaining eigenvalue information; The eigenvalue with the highest instability in the third remaining eigenvalue information is determined and retained based on a preset eigenvalue processing rule to determine the initialization result.

3. The method for determining characteristic values ​​of boundary layer instability of an aircraft according to claim 1, characterized in that: The determining of a plurality of source points from each object plane grid point on the grid surface, and comparing a quantity difference of instability features between each source point and an adjacent object plane grid point, to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result, includes: By analyzing the eigenvalues ​​of each of the object plane grid points on the grid surface, the object plane grid points having valid eigenvalues ​​are used as source points; Comparing the number of instability features of each source point with each adjacent object plane grid point to determine a first comparison result; If the first comparison result indicates that there are several first target adjacent grid points whose number of instability features is smaller than the number of instability features of the corresponding source point, then taking the first target adjacent grid point as the target point; Assigning the characteristic value information of the corresponding source point to the target point based on the initialization result to obtain a first target point after assignment, and triggering a corresponding marking operation on the first target point; Adding the first target point to a task queue to be solved to determine a corresponding first target task queue; Threads are allocated to each of the first target points in the first target task queue according to the number of cores of the central processing unit, and characteristic values ​​of each of the first target points are solved in parallel based on each thread to determine a first characteristic value result.

4. The method for determining characteristic values ​​of boundary layer instability of an aircraft according to claim 3, characterized in that: Determining a plurality of target points from the object plane grid points, and comparing a quantity difference of instability features between each target point and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result, includes: After completing the first eigenvalue determination operation, screening out all the object plane grid points on the grid surface that have not been assigned a value, and using them as the target points; Comparing the number of instability features of each target point with each adjacent object plane grid point to determine a second comparison result; If the second comparison result indicates that there are a number of second target adjacent grid points whose number of instability features is greater than the number of instability features of the target point, then taking the second target adjacent grid points as the source points; Assigning the eigenvalue information of the corresponding source point to the corresponding target point based on the first eigenvalue result to obtain a second target point after assignment, and triggering a corresponding marking operation on the second target point; Adding the second target point to a task queue to be solved to determine a corresponding second target task queue; A thread is allocated to each second target point in the second target task queue according to the number of cores of the central processing unit, and the characteristic value of each second target point is solved in parallel based on each thread to determine a second characteristic value result.

5. The method for determining characteristic values ​​of boundary layer instability of an aircraft according to claim 4, characterized in that: The step of comparing the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane and determining the target eigenvalue result based on the corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result includes: After completing the second eigenvalue determination operation, for each object plane grid point on the grid surface, triggering a frequency difference of an instability feature between each object plane grid point and a corresponding adjacent object plane grid point to determine a third comparison result; If the third comparison result indicates that there are a number of adjacent object plane grid points having target characteristic values ​​with different frequencies from the corresponding object plane grid points, then the adjacent object plane grid points are used as the source points, and the corresponding object plane grid points are used as the target points; Assigning the target eigenvalues ​​with different frequencies in the source points to the target points based on the first eigenvalue results and the second eigenvalue results to obtain a third target point after assignment, and triggering a corresponding marking operation on the third target point; Adding the third target point to the task queue to be solved to determine the corresponding third target task queue; Allocating threads to each of the third target points in the third target task queue according to the number of cores of the central processing unit, and solving the characteristic values ​​of each of the third target points in parallel based on the threads to determine a target characteristic value result; The target characteristic value results include the target frequency value, target streamwise wave value and target spanwise wave value of each object surface grid point on the grid surface.

6. A device for determining characteristic values ​​of boundary layer instability of an aircraft, characterized in that: include: An initialization module is used to perform eigenvalue initialization and identification and elimination of non-physical eigenvalues ​​on the grid surface of the three-dimensional hypersonic boundary layer corresponding to the aircraft based on a preset initialization strategy to determine an initialization result; a first eigenvalue determination module, configured to determine a plurality of source points from each object plane grid point on the grid surface, and compare a difference in the number of instability features between each source point and an adjacent object plane grid point, so as to perform a first eigenvalue determination operation based on a corresponding first comparison result and the initialization result; a second eigenvalue determination module, configured to, after obtaining the first eigenvalue result, determine a plurality of target points from the object plane grid points, and compare the difference in the quantity of instability features between each of the target points and an adjacent object plane grid point, so as to perform a second eigenvalue determination operation based on a corresponding second comparison result and the first eigenvalue result; a target eigenvalue determination module, configured to, after obtaining the second eigenvalue result, compare the frequency differences of the instability characteristics between all adjacent object plane grid points on the grid plane, and determine a target eigenvalue result based on a corresponding third comparison result, the first eigenvalue result, and the second eigenvalue result, so as to complete the transition prediction of the three-dimensional hypersonic boundary layer based on the target eigenvalue result; Wherein, the initialization module includes: A guess point setting unit, configured to set a number of initial guess points on a grid surface of a three-dimensional hypersonic boundary layer corresponding to the aircraft based on the number of CPU cores; a point scattering guessing unit, configured to scatter points in the eigenvalue spectrum space of the initial guessed points, and guess the initial eigenvalues ​​of the initial guessed points based on the scattered points in the eigenvalue spectrum space, so as to determine the initial eigenvalues ​​corresponding to the initial guessed points; The initialization result determination unit is used to determine invalid non-physical eigenvalues ​​in the initial eigenvalues ​​based on a preset non-physical eigenvalue identification strategy, and trigger a non-physical eigenvalue elimination operation to determine an initialization result.

7. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the method for determining a boundary layer instability characteristic value of an aircraft according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that Used to store a computer program, which, when executed by a processor, implements the method for determining the characteristic value of boundary layer instability of an aircraft according to any one of claims 1 to 5.

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