Fluid-solid coupling analysis method and device for near-water-surface moving object and storage medium

Abstract

The invention discloses a fluid-solid coupling analysis method and device for a near-water-surface moving object and a storage medium, and the method comprises the steps: obtaining the initial motion data of the near-water-surface moving object, processing the initial motion data through employing an immersion boundary method, obtaining the snapshot data of a flow field, and obtaining the snapshot data of the flow field; and carrying out eigenorthogonal decomposition according to the snapshot data of the flow field to obtain modal data and the like. According to the method, the POD is applied to processing the flow field snapshot data obtained through the IBM, and further dimensionality reduction can be performed on the IBM processing result, so that the IBM can be enhanced to reduce the complexity of grid generation and reduce the calculation amount, main features in the flow field or structural motion can be efficiently extracted, and the accuracy of the flow field or structural motion is improved. Therefore, the main modality of the system composed of the water surface moving object and the water is obtained, the degree of freedom of a fluid or structural system can be reduced, and the calculation complexity is reduced. The method is widely applied to the technical field of computational fluid mechanics.

Description

Technical Field

[0001] The invention relates to the technical field of computational fluid dynamics, and in particular to a method, a device and a storage medium for analyzing fluid-solid coupling of a moving object near a water surface. Background Art

[0002] In the field of marine engineering, there are many complex phenomena of fluid-structure interaction. To study the effects of wind, waves, and currents on offshore structures, it is necessary to accurately simulate the motion interaction between fluids and structures. However, general fluid-structure coupling problems have certain nonlinear characteristics. The motion response of the structure will significantly affect the various values ​​of the flow field, and the changes in the flow field will in turn affect the motion response of the structure. In order to achieve accurate simulation, the traditional fluid-structure coupling method has high computational complexity and requires a huge amount of computing resources. Summary of the invention

[0003] In view of the technical problems of the current fluid-structure coupling analysis technology, such as high computational complexity and huge consumption of computing resources, the purpose of the present invention is to provide a fluid-structure coupling analysis method, device and storage medium for a near-water surface moving object.

[0004] On the one hand, an embodiment of the present invention includes a fluid-solid coupling analysis method for a moving object near a water surface, and the fluid-solid coupling analysis method for a moving object near a water surface includes the following steps:

[0005] Acquire initial motion data of objects moving near the water surface;

[0006] Using the immersed boundary method to process the initial motion data, to obtain flow field snapshot data;

[0007] The intrinsic orthogonal decomposition is performed on the flow field snapshot data to obtain modal data.

[0008] Furthermore, the using of the immersed boundary method to process the initial motion data to obtain flow field snapshot data includes:

[0009] Generate a fixed background fluid grid;

[0010] Setting the fixed background fluid grid using the initial motion data;

[0011] Applying a virtual force in the fixed background fluid grid using a feedback force method, thereby converting the initial motion data to obtain a virtual boundary condition;

[0012] The structural dynamics equation is solved according to the virtual boundary condition and the initial motion data to obtain the flow field snapshot data.

[0013] Furthermore, solving the structural dynamics equation according to the virtual boundary condition and the initial motion data to obtain the flow field snapshot data includes:

[0014] Establishing the structural dynamics equation according to the virtual boundary condition and the initial motion data;

[0015] Solving the structural dynamics equation to obtain motion data of the near-water surface moving object corresponding to a corresponding time step;

[0016] Advancing the time step based on the overlapping grid technology to update the motion data of the near-water surface moving object;

[0017] The flow field snapshot data are composed of the motion data of the near-water surface moving object corresponding to each time step.

[0018] Further, solving the structural dynamics equation includes:

[0019] obtaining the structural dynamics equation in the form of an ordinary differential equation;

[0020] The structural dynamics equations are solved using the fourth-order Runge-Kutta method.

[0021] Further, performing intrinsic orthogonal decomposition according to the flow field snapshot data to obtain modal data includes:

[0022] Acquire a data matrix according to the flow field snapshot data;

[0023] Performing intrinsic orthogonal decomposition on the data moments to obtain a left singular matrix, a diagonal matrix and a right singular matrix;

[0024] The modal data is obtained according to the diagonal matrix.

[0025] Further, obtaining a data matrix according to the flow field snapshot data includes:

[0026] Obtaining a grid sequence corresponding to each motion data in the flow field snapshot data;

[0027] Arrange the motion data in the flow field snapshot data according to the corresponding time step sequence and grid sequence to obtain the data matrix; in the data matrix, the motion data corresponding to the same time step form the same column vector or row vector, and the motion data in the same column vector or row vector are sorted according to the corresponding grid sequence.

[0028] Further, the acquiring the modal data according to the diagonal matrix includes:

[0029] Extracting energy components corresponding to each mode of the near-water-surface moving object from the diagonal matrix;

[0030] Determine energy proportions corresponding to multiple modes according to each of the energy components;

[0031] The energy proportion is used as the modal data.

[0032] Furthermore, determining the energy proportions corresponding to the multiple modes according to the energy components includes:

[0033] Determine the interception accuracy;

[0034] Determining, from all modes of the near-water-surface moving object, a plurality of front modes whose number corresponds to the interception accuracy;

[0035] Obtain energy proportions corresponding to the front multiple modes.

[0036] On the other hand, an embodiment of the present invention also includes a computer device, including a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the fluid-solid coupling analysis method for near-water surface moving objects in the embodiment.

[0037] On the other hand, an embodiment of the present invention further includes a computer-readable storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to execute the fluid-solid coupling analysis method for a near-water surface moving object in the embodiment.

[0038] The beneficial effects of the present invention are: the fluid-solid coupling analysis method for near-water surface moving objects in the embodiment applies POD to process the flow field snapshot data obtained through IBM, which can further reduce the dimension of the processing results of IBM, thereby enhancing the role of IBM in reducing the complexity of grid generation and reducing the amount of calculation, and can efficiently extract the main features in the flow field or structural motion, thereby obtaining the main modes of the system composed of surface moving objects and water, which can reduce the degrees of freedom of the fluid or structural system, thereby reducing the computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Schematic diagram of the steps of the fluid-solid coupling analysis method for a moving object near a water surface in an embodiment;

[0040] Figure 2 A schematic diagram of a fixed background fluid grid in an embodiment;

[0041] Figure 3 A schematic diagram of the initial boundary conditions of a fixed background fluid grid in an embodiment;

[0042] Figure 4 A schematic diagram of a process of using the immersed boundary method to process initial motion data to obtain flow field snapshot data in an embodiment;

[0043] Figure 5 Schematic diagram of the principle of overlapping grid technology in the embodiment. DETAILED DESCRIPTION

[0044] Terminology explanation:

[0045] Immersed Boundary Method: IBM for short, is a method that uses a fixed background grid or overlapping grid to embed the boundary of the solid into the fluid grid to solve the motion data of objects moving near the water surface. This method does not need to constantly adjust the grid topology during the solution process.

[0046] Proper Orthogonal decomposition (POD) can reduce the dimension of data. In this embodiment, by combining the proper orthogonal decomposition with the immersed boundary method, the main modes of the object moving near the water surface can be extracted to reduce the degrees of freedom of the fluid or structural system, thereby reducing the computational complexity.

[0047] In this embodiment, refer to Figure 1 , the fluid-structure coupling analysis method for a moving object near the water surface includes the following steps:

[0048] S1. Obtaining initial motion data of a moving object near the water surface;

[0049] S2. Use the immersed boundary method to process the initial motion data to obtain flow field snapshot data;

[0050] S3. Perform intrinsic orthogonal decomposition based on the flow field snapshot data to obtain modal data.

[0051] In this embodiment, an elastically supported single-degree-of-freedom cylinder is used as an example of an object moving near the water surface for description.

[0052] Steps S1-S3 may be executed by a computer.

[0053] In step S1, initial motion data of the object moving near the water surface may be obtained by actual measurement or simulation, etc. Specifically, the initial motion data may include data such as initial displacement, initial velocity and initial acceleration of the object moving near the water surface.

[0054] In this embodiment, when executing step S2, that is, using the immersed boundary method to process the initial motion data to obtain the flow field snapshot data, the following steps are specifically performed:

[0055] S201. Generate a fixed background fluid grid;

[0056] S202. Setting the fixed background fluid grid using the initial motion data;

[0057] S203. Applying a virtual force in the fixed background fluid grid using a feedback force method, thereby obtaining a virtual boundary condition according to the initial motion data conversion;

[0058] S204. Solve the structural dynamics equations according to the virtual boundary conditions and the initial motion data to obtain flow field snapshot data.

[0059] The process of steps S201-S204 is as follows: Figure 4 shown.

[0060] In step S201, the following can be generated: Figure 2 Fixed background fluid grid shown.

[0061] In step S202, Figure 3 As shown in the figure, the initial boundary conditions of the fixed background fluid grid are set. The initial boundary conditions include the velocity inlet, the pressure outlet, the initial position and shape of the solid boundary, etc. At the same time, the fluid density ρ, viscosity ν, structural damping c and other conditions are set. The grid and boundary conditions are set as follows Figure 3 shown.

[0062] In step S203, a user defined function (UDF) program of Fluent may be run, and the UDF program automatically calls the initial motion data, combines the initial boundary data such as the displacement and velocity of the solid boundary, and automatically applies a virtual force in the fluid grid through the feedback force method, thereby converting these data into virtual boundary conditions in the fluid grid.

[0063] The feedback force method used in step S203 is to calculate the virtual force by introducing a feedback control mechanism. The form of the virtual force is usually:

[0064] f(x, t) = -α(u(x, t) - u s (X s (t)))·δ[xX s (t)]

[0065] Among them, α is the feedback gain coefficient, which controls the magnitude of the feedback force; u s (X s (t)) is the velocity at the structure boundary; u(x,t) is the velocity at the fluid grid point x; δ[xX s (t)] is a Dirac delta approximate smooth function used for the transfer between Lagrange variables and Eular variables. s (t)] is

[0066]

[0067] Where h = Δx = Δy, is the uniform grid spacing of the fluid, and satisfy

[0068]

[0069] The virtual boundary condition f(x, t) obtained in step S203 is then used in step S204 to solve the structural dynamics equation.

[0070] In step S204, the virtual boundary condition f(x, t) calculated in step S203 is combined with the initial motion data (including the initial value of displacement x, velocity The initial value and acceleration The initial value of the fluid grid, etc.) is combined, and the virtual force is applied to the source term of the fluid grid through a smooth function, thereby establishing the structural dynamics equation. Taking an elastically supported single-degree-of-freedom cylinder as an example of an object moving near the water surface, the structural dynamics equation can be written as:

[0071]

[0072] Where m is the mass of the object moving near the water surface, c is the structural damping coefficient, and k is the structural stiffness coefficient. The structural dynamics equation is an ordinary differential equation that can be solved using the fourth-order Runge-Kutta method. The process of using the fourth-order Runge-Kutta method to solve ordinary differential equations is as follows:

[0073]

[0074] x n+1 =x n +Δt*(x k1 +2x k2 +2x k3 +x k4 ) / 6

[0075] in:

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084] According to the above solution process, the principle is to divide the time period to be solved into n time steps, each time step corresponds to a duration of Δt, and advance the time step based on the overlapping grid technology; taking the elastically supported single-degree-of-freedom cylinder as an example, the grid is divided around the elastically supported single-degree-of-freedom cylinder, such as Figure 5 As shown in the figure, its grid overlaps with the fixed background grid. When the time step is advanced based on the overlapping grid technology, different grids exchange information between the overlapping areas. The accuracy and consistency of the calculation are guaranteed by the Penalty interpolation method, and the interaction force between the near-surface moving object structure and the fluid is guaranteed to be smoothly transferred at the grid points, so as to obtain the displacement x of the near-surface moving object corresponding to each grid at each time step. The speed can be further calculated based on the displacement x. and acceleration And other sports data.

[0085] In this embodiment, when executing steps S201-S204, a user-defined function (UDF) program of Fluent can be run, and the UDF program automatically calls the initial motion data and introduces it into the IBM calculation, thereby updating the position and motion information of the solid boundary in the fluid, for example, calculating the displacement x of the corresponding near-water surface moving object at each time step, and further calculating the velocity

[0086] In this embodiment, the UDF program can store the called data locally in CSV format to facilitate subsequent analysis and processing, thereby enhancing the compatibility and scalability of the system.

[0087] In this embodiment, due to the use of overlapping grid technology, Figure 5 Each grid in can calculate a corresponding velocity at each time step if Figure 5 There are m overlapping grids (spatial nodes) in total, and n time steps are set in total. The calculated velocity of the i-th grid at the j-th time step is expressed as Then for the first spatial node, we can get

[0088]

[0089] For n speed values, the second spatial node can be obtained in the same way.

[0090]

[0091] etc. for n speed values,

[0092] ...For the mth spatial node, we can obtain

[0093]

[0094] And so on for n speed values.

[0095] The above m vectors constitute the flow field snapshot data of the object moving near the water surface, which can be used to execute step S3.

[0096] In this embodiment, when executing step S3, that is, performing intrinsic orthogonal decomposition according to the flow field snapshot data to obtain modal data, the following steps are specifically performed:

[0097] S301. Obtaining a data matrix according to the flow field snapshot data;

[0098] S302. Performing intrinsic orthogonal decomposition on the data moments to obtain a left singular matrix, a diagonal matrix and a right singular matrix;

[0099] S303. Obtain modal data according to the diagonal matrix.

[0100] In step S301, the flow field snapshot data obtained in steps S201-S204 is executed

[0101]

[0102]

[0103] …

[0104]

[0105] It can be expressed in matrix form, for example, each vector is used as a row vector and arranged in the order of spatial nodes 1-m to obtain the data matrix

[0106]

[0107] The data matrix X satisfies X∈R m×n .

[0108] In step S302, the extracted data matrix X is imported into the POD program (which can be written using tools such as MATLAB), and the large amount of data obtained from IBM, i.e., the data matrix X, is reduced in dimension through intrinsic orthogonal decomposition based on singular value decomposition (SVD) to extract the main characteristic mode data.

[0109] Specifically, by executing step S302, the data matrix X can be decomposed into:

[0110] X=U∑V T

[0111] The data matrix X contains the state of the system consisting of the near-water moving object and water at different time steps;

[0112] U∈R m×m It is a left singular matrix. Each column in the left singular matrix U corresponds to a spatial mode (i.e., the eigenvector of the matrix X). These modes represent the flow patterns of the system in different spaces.

[0113] ∑∈R m×n is a diagonal matrix. The diagonal elements in the diagonal matrix ∑ are singular values, and each singular value represents the energy of each mode;

[0114] V∈R n×n is a right singular matrix, T represents matrix transpose, and each column in the right singular matrix V corresponds to a time mode, indicating the degree of contribution of the system to different modes in time.

[0115] In step S3, the left singular matrix U, the diagonal matrix ∑ and the right singular matrix V can be used as modal data. These modal data contain information such as the dominant vibration mode of the structure of the surface moving object, reflecting the main motion response of the surface moving object under specific excitation, and can be used for feedback and optimization of the hydrodynamic performance of the moving structure. They can also be visualized to explain and provide feedback on the dynamic behavior of the surface moving object structure.

[0116] In this embodiment, the diagonal matrix ∑ obtained in step S303 contains the energy components corresponding to each mode, where the energy component corresponding to the pth mode can be expressed as λ p ,λ p It represents the energy contribution of the pth mode, so the energy component can be used to measure the importance of each mode. In this embodiment, only the diagonal matrix ∑ can be used as the modal data obtained in step S3.

[0117] In step S303, for the set interception accuracy k, the energy proportion of the first k-order characteristic modes can be given by the following formula:

[0118]

[0119] Wherein, N is the total number of POD modes obtained by executing step S302. The principle of the calculation formula of the energy proportion is: select the number of modes according to the required accuracy, and linearly sum the first k-order modes to obtain The entire transient field can be reconstructed, and complex high-dimensional data can be simplified into a few modes. By comparing the first k-order modes generated by the flow field snapshots at each time step, the complex motion of the system can be explained on the time domain scale, which helps to understand the system's stability, periodicity and other motion properties. In addition, the obtained modes also reflect some of the motion characteristics of the system under the current external conditions. The energy proportion I(k) of the first k-order characteristic modes can be used to further predict the future dynamic behavior of similar systems, predict the response of the structure of near-water moving objects under different working conditions, and help analyze the long-term evolution characteristics of the system.

[0120] In this embodiment, the principle of executing steps S1-S3 is that the principle of IBM is to use a fixed background grid or an overlapping grid to embed the boundary of the solid into the fluid grid, so there is no need to continuously adjust the grid topology during the solution process, which can reduce the complexity of grid generation and reduce the amount of calculation; however, when IBM processes very complex fluid-structure interactions, especially under the demand for high-resolution fluid simulation, the amount of calculation is still very large; POD technology is an efficient dimensionality reduction technology, and POD is applied to process the flow field snapshot data obtained through IBM, which can extract the main features of the flow field or structural motion from the huge flow field snapshot data, thereby obtaining the main modes of the system composed of surface moving objects and water, which can reduce the degrees of freedom of the fluid or structural system, thereby reducing the computational complexity.

[0121] Moreover, S1-S3 in this embodiment can also use the Penalty interpolation method, and the boundary conditions of the moving structure and the fluid grid are automatically coupled through the written UDF program, without adjusting the grid topology, reducing the complexity of grid generation and adjustment; for the large amount of data generated by calculation, the modal extraction of the flow field and structural motion is performed through the POD method, which greatly reduces the degrees of freedom of the data set and realizes efficient dimensionality reduction solution; finally, the UDF program is used to automatically obtain the motion data of the structure boundary to update the flow field in real time, and extract the flow field snapshot at the specified time step for modal analysis, thereby improving the solution efficiency, stability and accuracy in complex fluid-solid interaction scenarios.

[0122] A computer program for executing the fluid-solid coupling analysis method for near-water-surface moving objects in this embodiment can be written and written into a computer device or storage medium. When the computer program is read out and executed, the fluid-solid coupling analysis method for near-water-surface moving objects in this embodiment is executed, thereby achieving the same technical effect as the fluid-solid coupling analysis method for near-water-surface moving objects in the embodiment.

[0123] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, etc. used in the present disclosure are only relative to the relative positional relationship of the components of the present disclosure in the accompanying drawings. The singular forms of "a", "" and "the" used in the present disclosure are also intended to include the plural forms, unless the context clearly indicates other meanings. In addition, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those generally understood by those skilled in the art. The terms used in the specification of this embodiment are only for describing specific embodiments and are not intended to limit the present invention. The term "and / or" used in this embodiment includes any combination of one or more related listed items.

[0124] It should be understood that, although the term first, second, third etc. may be adopted to describe various elements in the present disclosure, these elements should not be limited to these terms. These terms are only used to distinguish the same type of elements from each other. For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element. The use of any and all examples or exemplary language ("for example", "such as" etc.) provided by the present embodiment is only intended to better illustrate embodiments of the present invention, and unless otherwise required, the scope of the present invention will not be limited.

[0125] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed dedicated integrated circuit for this purpose.

[0126] In addition, the operations of the process described in this embodiment may be performed in any suitable order, unless otherwise indicated in this embodiment or otherwise clearly contradicted by the context. The process described in this embodiment (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as a code (e.g., executable instructions, one or more computer programs, or one or more applications) executed on one or more processors in common, by hardware or a combination thereof. A computer program includes a plurality of instructions that may be executed by one or more processors.

[0127] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself.

[0128] The computer program can be applied to input data to perform the functions of the present embodiment, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on the display.

[0129] The above are only preferred embodiments of the present invention. The present invention is not limited to the above embodiments. As long as the technical effects of the present invention are achieved by the same means, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention. Within the scope of protection of the present invention, its technical solutions and / or implementation methods may have various modifications and changes.

Claims

1. A fluid-solid coupling analysis method for a moving object near a water surface, characterized in that: The fluid-solid coupling analysis method for a moving object near a water surface comprises: Acquire initial motion data of objects moving near the water surface; Using the immersed boundary method to process the initial motion data, to obtain flow field snapshot data; The intrinsic orthogonal decomposition is performed on the flow field snapshot data to obtain modal data.

2. The fluid-solid coupling analysis method for a moving object near a water surface according to claim 1, characterized in that: The method of using the immersed boundary method to process the initial motion data to obtain flow field snapshot data includes: Generate a fixed background fluid grid; Setting the fixed background fluid grid using the initial motion data; Applying a virtual force in the fixed background fluid grid using a feedback force method, thereby converting the initial motion data to obtain a virtual boundary condition; The structural dynamics equation is solved according to the virtual boundary condition and the initial motion data to obtain the flow field snapshot data.

3. The fluid-structure coupling analysis method for a moving object near a water surface according to claim 2, characterized in that: The step of solving the structural dynamics equation according to the virtual boundary condition and the initial motion data to obtain the flow field snapshot data includes: Establishing the structural dynamics equation according to the virtual boundary condition and the initial motion data; Solving the structural dynamics equation to obtain motion data of the near-water surface moving object corresponding to a corresponding time step; Advancing the time step based on the overlapping grid technology to update the motion data of the near-water surface moving object; The flow field snapshot data are composed of the motion data of the near-water surface moving object corresponding to each time step.

4. The fluid-solid coupling analysis method for a moving object near a water surface according to claim 3 is characterized in that: The solving of the structural dynamics equation comprises: obtaining the structural dynamics equation in the form of an ordinary differential equation; The structural dynamics equations are solved using the fourth-order Runge-Kutta method.

5. The fluid-solid coupling analysis method for a moving object near a water surface according to claim 3 or 4, characterized in that: The step of performing intrinsic orthogonal decomposition according to the flow field snapshot data to obtain modal data includes: Acquire a data matrix according to the flow field snapshot data; Performing intrinsic orthogonal decomposition on the data moments to obtain a left singular matrix, a diagonal matrix and a right singular matrix; The modal data is obtained according to the diagonal matrix.

6. The fluid-structure coupling analysis method for a moving object near a water surface according to claim 5, characterized in that: The step of obtaining a data matrix according to the flow field snapshot data includes: Obtaining a grid sequence corresponding to each motion data in the flow field snapshot data; Arrange the motion data in the flow field snapshot data according to the corresponding time step sequence and grid sequence to obtain the data matrix; in the data matrix, the motion data corresponding to the same time step form the same column vector or row vector, and the motion data in the same column vector or row vector are sorted according to the corresponding grid sequence.

7. The fluid-structure coupling analysis method for a moving object near a water surface according to claim 5, characterized in that: The acquiring the modal data according to the diagonal matrix includes: Extracting energy components corresponding to each mode of the near-water-surface moving object from the diagonal matrix; According to each of the energy components, determining energy proportions corresponding to multiple modes; The energy proportion is used as the modal data.

8. The fluid-structure coupling analysis method for a moving object near a water surface according to claim 7, characterized in that: Determining energy proportions corresponding to multiple modes according to each of the energy components includes: Determine the interception accuracy; Determining, from all modes of the near-water-surface moving object, a plurality of front modes whose number corresponds to the interception accuracy; Obtain energy proportions corresponding to the front multiple modes.

9. A computer device, characterized in that: It comprises a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the fluid-solid coupling analysis method for a near-water surface moving object as described in any one of claims 1-8.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to execute the fluid-solid coupling analysis method for a near-water surface moving object as described in any one of claims 1 to 8 when executed by the processor.

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