Data processing method and device

Abstract

The invention discloses a data processing method and device. The data processing method comprises the steps that first attitude data of a one-dimensional beam corresponding to a flexible rod cylinder assembly, first grid data of a three-dimensional surface grid of the flexible rod cylinder assembly and fluid parameters associated with fluid acting on the flexible rod cylinder assembly are obtained; calculating a current hydrodynamic load based on the first attitude data, the first grid data and the fluid parameters; acquiring second attitude data of a one-dimensional beam corresponding to the flexible rod cylinder assembly deformed by applying the current hydrodynamic force load; and on the basis of the first attitude data, the first grid data and the second attitude data, a deformation vector of a three-dimensional surface grid of the flexible rod cylinder assembly deformed by applying the current hydrodynamic force load is calculated, and the deformation vector is used for representing the deformation degree of the flexible rod cylinder assembly.

Description

Technical Field

[0001] The present disclosure generally relates to the technical field of fluid mechanics and structural dynamics, and more specifically, to a data processing method and device. Background Art

[0002] In the existing design of flexible rod barrel components, it is usually necessary to calculate the influence of the fluid acting on the flexible rod barrel component on the flexible rod barrel component. In the case of a fluid acting on a flexible rod barrel component, for example, when calculating the series of influences of the flowing gas (for example, wind) on the blade assembly of a wind turbine (referred to as the fan blade), the mainstream aerodynamic algorithm used is an algorithm based on the blade element momentum theory (referred to as the BEM algorithm). The implementation process of the BEM algorithm is roughly as follows: first, the surface of the fan blade is discretized, and then the complex three-dimensional aerodynamic problem is converted into a process of solving the two-dimensional integral equation on the surface. The above-mentioned BEM algorithm has certain advantages in terms of computing time and resource consumption, and is suitable for large-scale load calculation of fan blades. However, the implementation of the BEM algorithm needs to be based on a series of assumptions (such as ideal flow, superposition of two-dimensional aerodynamic forces and inviscid flow, etc.), but these assumptions limit the accuracy and scope of application of the BEM algorithm. The reason is that in actual application scenarios, these assumptions ignore several important realities: such as turbulence, three-dimensional flow and viscosity effects.

[0003] In particular, for fan blades with relatively large component length / height, the aeroelastic constraints of the fan blades become increasingly apparent and their operating performance characteristics become more complex when calculating the effects of gas on such fan blades. In addition, with the trend towards lighter and more flexible fan blades, adverse issues have arisen in terms of vibration stability of the fan blades and their associated components (e.g., impellers) both during operation and in a non-moving state.

[0004] Furthermore, in the prior art, the computational efficiency of the algorithms related to the action of fluid on the flexible rod barrel assembly is relatively low and the computational resource consumption is large. Summary of the invention

[0005] The embodiments of the present disclosure provide a data processing method and device, which can effectively solve the problem in the prior art that the calculation efficiency of the algorithm related to the action of fluid on the flexible rod barrel assembly is relatively low and the calculation resource consumption is large.

[0006] In a general aspect, a data processing method is provided, which includes: acquiring first posture data of a one-dimensional beam corresponding to a flexible rod barrel assembly, first grid data of a three-dimensional surface grid of the flexible rod barrel assembly, and fluid parameters associated with a fluid acting on the flexible rod barrel assembly; calculating a current fluid dynamic load based on the first posture data, the first grid data, and the fluid parameters; acquiring second posture data of the one-dimensional beam corresponding to the flexible rod barrel assembly deformed by applying the current fluid dynamic load; and calculating a deformation vector of the three-dimensional surface grid of the flexible rod barrel assembly deformed by applying the current fluid dynamic load based on the first posture data, the first grid data, and the second posture data, wherein the deformation vector is used to characterize the degree of deformation of the flexible rod barrel assembly.

[0007] Optionally, the data processing method may further include: updating the current fluid dynamic load based on the deformation vector, and returning to the step of acquiring the second posture data.

[0008] Optionally, the first posture data and the second posture data may include spatial point coordinate data and quaternion data of a beam node of a one-dimensional beam, wherein the spatial point coordinate data indicates the spatial position of the beam node in a global coordinate system, and the quaternion data indicates the rotational posture of the beam node in the global coordinate system.

[0009] Optionally, the first mesh data may include spatial point coordinate data of mesh nodes of the three-dimensional surface mesh in a global coordinate system.

[0010] Optionally, the step of calculating the deformation vector may include: calculating the deformation vector by applying a preset interpolation algorithm to the first posture data, the first mesh data and the second posture data.

[0011] Optionally, the step of calculating the deformation vector may include: calculating the mapping posture data of the grid points of the three-dimensional surface grid mapped on the one-dimensional beam based on the first posture data and the first grid data; calculating the translational displacement change vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod barrel assembly based on the second posture data and the first grid data; calculating the rotational displacement change vector of the deformed grid points based on the second posture data and the mapping posture data; and calculating the deformation vector by adding the translational displacement change vector to the rotational displacement change vector.

[0012] Optionally, the step of calculating mapping posture data of the grid points of the three-dimensional surface mesh mapped on the one-dimensional beam may include: based on the first grid data, applying a first preset interpolation algorithm to the first posture data, and calculating the mapping space point coordinate data of the grid points mapped on the one-dimensional beam; based on the first posture data and the mapping space point coordinate data, applying a second preset interpolation algorithm different from the first preset interpolation algorithm to the grid points, and calculating the mapping quaternion data of the grid points mapped on the one-dimensional beam, so as to obtain the mapping posture data including the mapping space point coordinate data and the mapping quaternion data.

[0013] Optionally, the step of calculating the translational displacement change vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod-barrel assembly may include: calculating the translational displacement change vector of the one-dimensional beam corresponding to the deformed flexible rod-barrel assembly based on the first posture data and the second posture data; and applying a preset interpolation algorithm to the translational displacement change vector of the one-dimensional beam based on the first grid data to calculate the translational displacement change vector of the deformed grid points.

[0014] Optionally, the step of calculating the rotational displacement change vector of the deformed grid point may include: based on the second posture data, applying a preset interpolation algorithm to the deformed grid point, and calculating the deformation mapping quaternion data of the deformed grid point mapped on the one-dimensional beam; based on the first grid data and the deformation mapping quaternion data, calculating the rotational displacement change vector of the deformed grid point.

[0015] Optionally, the step of updating the current fluid dynamic load may include: calculating the fluid dynamic vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid parameter corresponding to the deformation vector; calculating the fluid dynamic moment vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid dynamic vector; and updating the current fluid dynamic load of the three-dimensional surface mesh mapped on the one-dimensional beam based on the fluid dynamic vector and the fluid dynamic moment vector.

[0016] Optionally, the step of calculating the current fluid dynamic load may include: calculating the fluid dynamic vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data and the fluid parameters; calculating the fluid dynamic moment vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data and the fluid dynamic vector; and calculating the current fluid dynamic load of the three-dimensional surface mesh mapped on the one-dimensional beam based on the fluid dynamic vector and the fluid dynamic moment vector.

[0017] In another general aspect, a data processing device is provided, comprising: an acquisition unit configured to acquire first posture data of a one-dimensional beam corresponding to a flexible rod barrel assembly, first grid data of a three-dimensional surface grid of the flexible rod barrel assembly, and fluid parameters associated with a fluid acting on the flexible rod barrel assembly; the acquisition unit is also configured to acquire second posture data of the one-dimensional beam corresponding to the flexible rod barrel assembly deformed by applying the current fluid dynamic load; a load calculation unit configured to calculate a current fluid dynamic load based on the first posture data, the first grid data, and the fluid parameters; a deformation mapping unit configured to calculate a deformation vector of the three-dimensional surface grid of the flexible rod barrel assembly deformed by applying the current fluid dynamic load based on the first posture data, the first grid data, and the second posture data, wherein the deformation vector is used to characterize the degree of deformation of the flexible rod barrel assembly.

[0018] Optionally, the deformation mapping unit is configured to: calculate the mapping posture data of the grid points of the three-dimensional surface grid mapped on the one-dimensional beam based on the first posture data and the first grid data; calculate the translational displacement change vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod barrel assembly based on the second posture data and the first grid data; calculate the rotational displacement change vector of the deformed grid points based on the second posture data and the mapping posture data; and calculate the deformation vector by adding the translational displacement change vector to the rotational displacement change vector.

[0019] In another general aspect, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to perform the data processing method as described above.

[0020] In another general aspect, a computer device is provided, comprising: at least one processor; and at least one memory storing computer executable instructions, wherein the computer executable instructions, when executed by the at least one processor, cause the at least one processor to perform the data processing method as described above.

[0021] According to the data processing method and device of the embodiment of the present disclosure, through the data processing method based on fluid-solid coupling, it is possible to effectively improve the calculation accuracy of the fluid dynamic load acting on the flexible rod barrel assembly and the deformation prediction accuracy of the flexible rod barrel assembly, improve the data calculation efficiency in the relevant calculation process and reduce the data calculation resource consumption. Therefore, through the present disclosure, it is possible to effectively solve the problem of relatively low calculation efficiency and high calculation resource consumption of the relevant algorithms for the action of fluid on the flexible rod barrel assembly in the prior art. At the same time, according to the data processing method based on fluid-solid coupling of the present disclosure, the load and deformation of the blade can be calculated more accurately in the early design of the wind turbine, which is helpful to deeply understand the vibration behavior of the blade, guide the optimization design and performance evaluation of the blade, and improve the reliability of the prediction of blade strength, fatigue life, power curve, and tower clearance.

[0022] Additional aspects and / or advantages of the present general inventive concept will be set forth in part in the following description and in part will be apparent from the description or may be learned through practice of the present general inventive concept. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects and features of the embodiments of the present disclosure will become more apparent through the following description in conjunction with the accompanying drawings showing the embodiments, in which:

[0024] Figure 1 is a flow chart showing a data processing method according to an embodiment of the present disclosure;

[0025] Figure 2 is a schematic diagram showing a spatial representation of a one-dimensional beam node according to an embodiment of the present disclosure;

[0026] Figure 3 is a schematic diagram showing a three-dimensional surface mesh of a blade according to an embodiment of the present disclosure;

[0027] Figure 4A and Figure 4B is a schematic diagram showing a process of corresponding one-dimensional beam nodes to three-dimensional surface meshes according to an embodiment of the present disclosure;

[0028] Figure 5 is a flowchart showing steps of calculating a deformation vector according to an embodiment of the present disclosure;

[0029] Figure 6 is a flow chart showing steps for calculating mapping posture data according to an embodiment of the present disclosure;

[0030] Fig. 7A and Figure 7B is a schematic diagram showing a derivation process for quaternion spherical linear interpolation according to an embodiment of the present disclosure;

[0031] Figure 8 is a schematic diagram showing interpolation coefficients of quaternion spherical linear interpolation according to an embodiment of the present disclosure;

[0032] Fig. 9 is a flowchart showing steps of calculating a translation displacement variation vector according to an embodiment of the present disclosure;

[0033] Fig.10 is a flowchart showing the steps of calculating a rotation displacement variation vector according to an embodiment of the present disclosure;

[0034] Fig.11 is a schematic diagram showing a simulation application platform system according to an embodiment of the present disclosure;

[0035] Fig. 12A and Fig. 12B is a schematic diagram showing simulation results according to an embodiment of the present disclosure;

[0036] Fig.13 is a schematic diagram showing another simulation result according to an embodiment of the present disclosure;

[0037] Fig.14 is a block diagram illustrating a data processing apparatus according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] The following specific embodiments are provided to help the reader obtain a comprehensive understanding of the methods, devices and / or systems described herein. However, after understanding the disclosure of the present application, various changes, modifications and equivalents of the methods, devices and / or systems described herein will be clear. For example, the order of operations described herein is only an example and is not limited to those orders set forth herein, but can be changed as will be clear after understanding the disclosure of the present application, except for operations that must occur in a specific order. In addition, for greater clarity and simplicity, the description of features known in the art may be omitted.

[0039] The features described herein can be implemented in different forms and should not be construed as being limited to the examples described herein. Rather, the examples described herein have been provided to illustrate only some of the many possible ways to implement the methods, devices, and / or systems described herein, which will be clear after understanding the disclosure of the present application.

[0040] As used herein, the term "and / or" includes any one of the associated listed items and any combination of any two or more.

[0041] Although terms such as "first", "second", and "third" may be used herein to describe various members, components, regions, layers, or portions, these members, components, regions, layers, or portions should not be limited by these terms. Instead, these terms are only used to distinguish one member, component, region, layer, or portion from another member, component, region, layer, or portion. Therefore, without departing from the teachings of the examples described herein, the first member, first component, first region, first layer, or first portion referred to in the examples may also be referred to as the second member, second component, second region, second layer, or second portion.

[0042] In the specification, when an element (such as a layer, a region, or a substrate) is described as being “on”, “connected to”, or “coupled to” another element, the element may be directly “on”, “connected to”, or “coupled to” another element, or one or more other elements may be present therebetween. Conversely, when an element is described as being “directly on”, “directly connected to”, or “directly coupled to” another element, there may be no other elements present therebetween.

[0043] The terms used herein are only used to describe various examples and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. The terms "comprise", "include" and "have" indicate the presence of the described features, quantities, operations, components, elements and / or combinations thereof, but do not exclude the presence or addition of one or more other features, quantities, operations, components, elements and / or combinations thereof.

[0044] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by a person of ordinary skill in the art to which the present disclosure belongs after understanding the present disclosure. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0045] Furthermore, in the description of examples, when it is considered that a detailed description of a well-known related structure or function would cause vague interpretation of the present disclosure, such a detailed description will be omitted.

[0046] In the present disclosure, the application object of the data processing method according to the embodiment of the present disclosure may include a flexible rod-barrel assembly. As a non-limiting example, the flexible rod-barrel assembly involved in the present disclosure may be a rod-barrel-shaped assembly with flexibility, and may be an airfoil assembly (e.g., a wind turbine blade of a wind turbine, a wing of an aircraft, a blade of an underwater generator, etc.), a rod-barrel-shaped assembly (e.g., a tower of a wind turbine, a chimney, etc.).

[0047] In the present disclosure, the application scenarios of the data processing method according to the embodiments of the present disclosure may include scenarios in which fluids (gas and liquid) act on the flexible rod barrel assembly to deform the flexible rod barrel assembly. As non-limiting examples, the above application scenarios may include: scenarios in which gas (e.g., air) acts on the fan blades of a wind turbine, scenarios in which liquid (e.g., water) acts on the blades of a hydroelectric generator, and scenarios in which gas (e.g., air) acts on a chimney and / or a tower of a wind turbine.

[0048] In the following, for the convenience of explanation, when describing the details of the data processing method, the scenario of air acting on the wind turbine blades of a wind turbine will be taken as an example to specifically describe the data processing method of the present disclosure.

[0049] In the application scenario where air acts on the fan blades of a wind turbine, as mentioned in the background technology of the present disclosure, in the existing wind turbine design (for example, the related design of fan blades and towers), the mainstream aerodynamic algorithm is the BEM algorithm. However, for long and flexible wind blades with an impeller diameter of more than 200m, the aeroelastic constraints of the long and flexible wind blades are becoming increasingly obvious, and the operating performance characteristics are more complex, and the applicability of the BEM algorithm is significantly reduced. In addition, with the development trend of wind turbine blade weight reduction and flexibility, wind turbine units have problems such as impeller vibration stability (for example, vortex excitation, flutter, speed oscillation, impeller modal abnormality) in both operation and shutdown scenarios, and the impeller mode has also expanded from low order to high order. Therefore, a data processing method that can solve the above problems is needed.

[0050] In the present disclosure, in the application scenario where air acts on the fan blades of a wind turbine, considering the bidirectional coupling between the wind field and the blades, the present disclosure adopts a fluid-solid coupling algorithm based on computational fluid dynamics (CFD) and computational structural dynamics (CSD) theory to simulate the unsteadiness, turbulence effect and non-uniform wind field of the wind field, and provide accurate blade response results (for example, the deformation effect caused by the wind acting on the blades). The fluid-solid coupling algorithm based on CFD and CSD according to the present disclosure has the following effects: in the early design of the wind turbine, the load and deformation of the blades can be calculated more accurately, which helps to deeply understand the vibration behavior of the blades, guide the optimization design and performance evaluation of the blades, and improve the reliability of the prediction of blade strength, fatigue life, power curve and tower clearance.

[0051] The present disclosure is described in detail below with reference to the accompanying drawings.

[0052] The present disclosure proposes a data processing method. Figure 1 is a flowchart illustrating a data processing method according to an embodiment of the present disclosure.

[0053] Reference Figure 1 According to an embodiment of the present disclosure, the data processing method comprises the following steps:

[0054] In step S100 , first posture data of a one-dimensional beam corresponding to the flexible rod barrel assembly, first mesh data of a three-dimensional surface mesh of the flexible rod barrel assembly, and fluid parameters associated with a fluid acting on the flexible rod barrel assembly are acquired.

[0055] According to an embodiment of the present disclosure, the first posture data and the second posture data may include spatial point coordinate data and quaternion data of a beam node of a one-dimensional beam, wherein the spatial point coordinate data indicates the spatial position of the beam node in a global coordinate system, and the quaternion data indicates the rotational posture of the beam node in a global coordinate system. Here, the first posture data represents the posture data before the fluid acts on the flexible rod barrel assembly, and the second posture data represents the posture data after the fluid acts on the flexible rod barrel assembly.

[0056] Here, the application scenario of air acting on the fan blades of a wind turbine (hereinafter referred to as blades) is taken as an example to explain the specific details.

[0057] According to an embodiment of the present disclosure, the one-dimensional beam corresponding to the blade in the present disclosure can represent the use of a one-dimensional beam (abbreviated as 1D beam) model to model the blade. The modeled 1D beam model is used to describe the shear, flexure, torsion and other behaviors of the blade under wind load. In the 1D beam model, it is assumed that the blade is a one-dimensional beam, and the blade is divided into a plurality of nodes, and the nodes are connected by beam units. Each node represents a position on the blade, and the beam unit describes the connection relationship between the nodes. The deformation of the blade is described by the translation and rotation of the beam unit. Here, when modeling, there is no special restriction on the state of the blade, that is, the blade can be in a stationary state, or the blade can be in a running (for example, rotating) state.

[0058] Reference Figure 2 , Figure 2 is a schematic diagram showing a spatial representation of a one-dimensional beam node according to an embodiment of the present disclosure. Figure 2 In the figure, the red line represents the 1D beam, the red circles represent the 1D beam nodes, and the blue and green arrows describe the rotation of the 1D beam nodes.

[0059] Specifically, the posture data of a 1D beam may include 7 parameters, namely, the spatial point coordinates in the global coordinate system (which can be represented by x, y, and z) and the quaternion q in the global coordinate system (which can be represented by a, b, c, and d) (it should be understood that the letters in bold (such as q) in this disclosure can represent the meaning of vectors, which will not be repeated hereafter). In other words, the spatial point coordinates can be used to describe the spatial position of the 1D beam node, and the quaternion can be used to describe the rotation of the 1D beam node. The meaning of the quaternion is further explained below.

[0060] Regarding the quaternion q, the following formula (1) is satisfied:

[0061] q=a+bi+cj+dk (1)

[0062] Among them, a, b, c, d are real numbers, i 2 =j 2 =k 2 =ijk=-1.

[0063] The rotation angle θ represented by the quaternion q can satisfy the following equation (2):

[0064]

[0065] The rotation axis u represented by the quaternion q can satisfy the following equation (3):

[0066]

[0067] Where b = [b, c, d].

[0068] According to an embodiment of the present disclosure, the first mesh data may include spatial point coordinate data of mesh nodes of the three-dimensional surface mesh in a global coordinate system.

[0069] According to an embodiment of the present disclosure, the three-dimensional surface mesh (hereinafter referred to as 3D surface mesh) of the blade in the present disclosure may be as follows: Figure 3 As shown, Figure 3 is a schematic diagram showing a three-dimensional surface mesh of a blade according to an embodiment of the present disclosure. Figure 3 The shape of the three-dimensional surface mesh of the blade shown in FIG is a substantially triangular shape, but in the present disclosure, the three-dimensional surface mesh can also be described by a quadrilateral shape. In addition, during data processing, each three-dimensional surface mesh can be simplified to a mesh node (also referred to as a mesh point) for vector calculation, that is, each mesh node can be represented as a spatial point coordinate in a global coordinate system.

[0070] According to an embodiment of the present disclosure, the fluid parameters under the blade example in the present disclosure may include: wind speed, wind shear coefficient, blade pitch angle, blade azimuth angle, wind deviation and hub height at different times.

[0071] In step S200, the current fluid dynamic load is calculated based on the first posture data, the first grid data and the fluid parameters.

[0072] According to an embodiment of the present disclosure, step S200 may further include: calculating the fluid dynamic vector of the three-dimensional surface mesh mapping on the one-dimensional beam based on the first mesh data and the fluid parameters; calculating the fluid dynamic moment vector of the three-dimensional surface mesh mapping on the one-dimensional beam based on the first mesh data and the fluid dynamic vector; and calculating the current fluid dynamic load of the three-dimensional surface mesh mapping on the one-dimensional beam based on the fluid dynamic vector and the fluid dynamic moment vector.

[0073] In step S200, firstly, the 1D beam nodes corresponding to the blades need to be bound to the 3D surface mesh (ie, the two are in correspondence with each other). Figure 4A and Figure 4B , Figure 4A and Figure 4B The correspondence process between one-dimensional beam nodes and three-dimensional surface meshes according to an embodiment of the present disclosure is shown.

[0074] exist Figure 4A In the figure, node 1 and node 2 are two nodes on the 1D beam node. According to the spatial point coordinates of node 1 and node 2, the boundary line between the two nodes can be calculated (such as Figure 4A ). For example, the dividing line can be the midline of the line connecting the two nodes, but the present disclosure is not limited thereto. In this way, a dividing line can be obtained between each two adjacent beam nodes, and the 3D surface mesh corresponding to the 1D beam node is divided into multiple regions according to the dividing line between each two beam nodes, and the mesh in each region corresponds to a 1D beam node, that is, the binding between the 1D beam node and the 3D surface mesh is achieved (after binding, the binding relationship will not change in the subsequent calculation process). As an example, Figure 4B As shown, the blades shown correspond to 68 1D beam nodes (numbered 0.000000-67.000) (hereinafter referred to as numbered 0-67), and different colors are used to indicate the area where the bound 3D surface mesh is located.

[0075] According to an embodiment of the present disclosure, the specific process of calculating the current fluid dynamic load is as follows: First, based on the gas parameters (e.g., parameters related to wind) at different times, the pressure p and shear stress of the 3D surface grid are calculated by, for example, a predetermined CFD solver (but not limited thereto). Then the forces and moments required to load the 1D beam nodes are obtained by integration; the aerodynamic forces on the 3D surface mesh in the global coordinate system are then calculated. The details are as shown in equation (4). Finally, the aerodynamic force and aerodynamic moment on the 3D blade in the global coordinate system are integrated, as shown in equations (5) and (6).

[0076]

[0077]

[0078]

[0079] in, represents the area vector of the surface mesh, F Node1 and M Node1denote the force and moment acting on the 1D beam node 1, respectively, n is the number of 3D surface meshes bound to the 1D beam node 1 (i.e., node 1), Represents the distance vector from node 1 to the i-th grid point.

[0080] In this way, according to the above equations (4) to (6), the aerodynamic loads (including three-directional forces and three-directional moments) corresponding to all 1D beam nodes can be extracted from the 3D surface of the blade as the current fluid dynamic load.

[0081] According to an embodiment of the present disclosure, by utilizing a high-precision CFD-based method instead of the conventional BEM method for fluid-solid coupling calculations, the aerodynamic loads on the three-dimensional surface of the blade are calculated by the CFD-based method, which can improve the calculation accuracy and efficiency of the aerodynamic loads on the blade and the accuracy of deformation prediction.

[0082] In step S300, second posture data of the one-dimensional beam corresponding to the flexible rod-barrel assembly deformed by applying the current fluid dynamic load is acquired.

[0083] According to an embodiment of the present disclosure, step S300 may further include: acquiring second posture data by loading the current fluid dynamic load onto a one-dimensional beam corresponding to the blade via, for example, a predetermined structural solver (but not limited thereto).

[0084] In step S400, based on the first posture data, the first mesh data and the second posture data, the deformation vector of the three-dimensional surface mesh of the flexible barrel assembly deformed by applying the current fluid dynamic load is calculated. Here, the deformation vector is used to characterize the deformation degree (posture after deformation) of the flexible barrel assembly.

[0085] Specifically, the step of calculating the deformation vector may include calculating the deformation vector by applying a preset interpolation algorithm to the first posture data, the first mesh data, and the second posture data.

[0086] Further, refer to Figure 5 , Figure 5 : is a flowchart showing the steps of calculating the deformation vector according to an embodiment of the present disclosure. Specifically, the steps of calculating the deformation vector may include the following steps: in step S410, based on the first posture data and the first grid data, the mapping posture data of the grid points of the three-dimensional surface grid mapped on the one-dimensional beam is calculated; in step S420, based on the second posture data and the first grid data, the translational displacement variation vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod barrel assembly is calculated; in step S430, based on the second posture data and the mapping posture data, the rotational displacement variation vector of the deformed grid points is calculated; in step S440, the deformation vector is calculated by adding the translational displacement variation vector to the rotational displacement variation vector.

[0087] According to the embodiments of the present disclosure, referring to Figure 6 , Figure 6 : is a flowchart showing step S410 of calculating mapping posture data according to an embodiment of the present disclosure. Specifically, step S410 may further include the following steps: in step S411, based on the first grid data, a first preset interpolation algorithm is applied to the first posture data to calculate the mapping space point coordinate data of the grid point mapped on the one-dimensional beam; in step S412, based on the first posture data and the mapping space point coordinate data, a second preset interpolation algorithm different from the first preset interpolation algorithm is applied to the grid point to calculate the mapping quaternion data of the grid point mapped on the one-dimensional beam, so as to obtain the mapping posture data including the mapping space point coordinate data and the mapping quaternion data.

[0088] According to an embodiment of the present disclosure, in step S410, two reference points of the preset interpolation algorithm (i.e., the interpolation reference points of the 3D grid points) may be first determined. For example, the reference point of the point to be interpolated between two points is the two points themselves. Since the interpolation coefficients are different when every two points are used as reference points, the reference points may be the two points most adjacent to the point to be interpolated, but the present disclosure is not limited thereto, and three or more reference points may also be used. In addition, the interpolation algorithm used in the present disclosure may be a first interpolation, a second interpolation, a third interpolation, or more interpolations, which are not limited by the present disclosure.

[0089] As an example, the first preset interpolation algorithm may be a Lagrange interpolation algorithm, but the present disclosure is not limited thereto. The Lagrange interpolation formula and interpolation coefficients are briefly described below.

[0090] Assume that n (n is a positive integer) data points (x1, y1), ..., (x n ,y n ), the purpose of the Lagrange interpolation algorithm is to calculate the interpolation polynomial. If the explicit interpolation polynomial form is calculated, it is called the Lagrange formula, which is used to obtain a polynomial interpolation point of degree n-1. For n data points (x1, y1), ..., (x n ,y n ), for each k between 1 and n, the interpolation coefficient is defined as the following formula (7):

[0091]

[0092] According to formula (7), for the interpolation independent variable x of degree n-1, the interpolation dependent variable y can be obtained by the following formula (8):

[0093] P n-1 (x k )=y1L1(xk)+...+yn L n (xk)=0+…+y k L k (xk)+0+…+0=y k (8)

[0094] According to an embodiment of the present disclosure, by applying the above equations (7) and (8) to the interpolation calculation in step S411, the mapping space point coordinate data of the 3D grid point mapped on the 1D beam is obtained.

[0095] As an example, the second preset interpolation algorithm may be a quaternion spherical linear interpolation (ie, quaternion Slerp interpolation) algorithm, but the present disclosure is not limited thereto. The quaternion spherical linear interpolation formula and interpolation coefficients are briefly described below.

[0096] Assuming that two rotation transformations q0 and q1 are known, the purpose of quaternion spherical linear interpolation is to calculate the intermediate transformation q t , so that the initial rotation transformation q0 can smoothly transition to the final rotation transformation q1. t It is expressed as a linear combination of v0 as a unit vector and v1 as a unit vector, as shown in the following equation (9):

[0097] v t =αv0+βv1 (9)

[0098] In order to find α and β in formula (9), we can refer to Fig. 7A and Figure 7B The following equations (10) and (11) are derived.

[0099] cos((1-t)θ)=(cos(tθ)-βcos(θ))cos(θ)+β

[0100] cos((1-t)θ)=cos(tθ)cos(θ)-βcos 2 (θ)+β

[0101] β(1-cos 2 (θ))=cos((1-t)θ)-cos(tθ)cos(θ)

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] Through the above equations (9) to (11), we can get the quaternion q t The Slerp formula is as follows:

[0108]

[0109] Where t is the Slerp interpolation coefficient, and its value range is [0, 1].

[0110] Reference Figure 8 , Figure 8 The distribution cloud diagram of the interpolation coefficient t of the 3D surface mesh nodes is shown. For the 3D surface mesh nodes distributed between node 1 and node 2 of the 1D beam, the t value of the mesh node with a flat cross section at node 1 is 0 (e.g. Figure 8 The darkest blue value shown in the figure), and the t of the mesh node with flush cross section at node 2 is taken as 1 (as shown in the figure). Figure 8 The darkest red shown).

[0111] According to an embodiment of the present disclosure, by applying the above equations (9) to (12) to the interpolation calculation in step S412, the mapping quaternion data of the 3D grid point mapped on the 1D beam is obtained. The mapping spatial point coordinate data obtained in step S411 and the mapping quaternion data obtained in step S412 are combined to obtain the mapping posture data.

[0112] According to the embodiments of the present disclosure, referring to Fig. 9 , Fig. 9 1 is a flow chart showing step S420 of calculating the translational displacement variation vector according to an embodiment of the present disclosure. Specifically, step S420 may further include the following steps: in step S421, based on the first posture data and the second posture data, the translational displacement variation vector of the one-dimensional beam corresponding to the deformed flexible rod barrel assembly is calculated; in step S422, based on the first grid data, a preset interpolation algorithm is applied to the translational displacement variation vector of the one-dimensional beam to calculate the translational displacement variation vector of the deformed grid point.

[0113] As an example, in step S421, the spatial point coordinate data of the 1D beam node in the second posture data after the blade is deformed is subtracted from the spatial point coordinate data of the 1D beam node in the first posture data before the blade is deformed, and the translation displacement change vector (which can be expressed as dx, dy, dz) of the one-dimensional beam corresponding to the deformed blade is calculated. In step S422, by using the spatial coordinate point data in the first grid data before the blade is deformed, dx, dy, dz are preset interpolated (for example, but not limited to, Lagrange interpolation), and the translation displacement change vector (which can be expressed as dxi, dyi, dzi) of the deformed grid point is calculated. Here, when dxi, dyi, dzi are calculated in each cycle, the reference data used are the data before deformation (for example, the spatial coordinate point data in the first grid data before the blade is deformed) instead of the last deformation result data to perform the interpolation calculation. The purpose of this is to reduce the cumulative calculation error, which can effectively avoid the error accumulation caused by multiple interpolations.

[0114] According to the embodiments of the present disclosure, referring to Fig.10 , Fig.10 1 is a flowchart showing step S430 of calculating the rotation displacement variation vector according to an embodiment of the present disclosure. Specifically, step S430 may further include the following steps: in step S431, based on the second posture data, a preset interpolation algorithm is applied to the deformed grid points to calculate the deformation mapping quaternion data of the deformed grid points mapped on the one-dimensional beam; in step S432, based on the first grid data and the deformation mapping quaternion data, the rotation displacement variation vector of the deformed grid points is calculated.

[0115] As an example, in step S431, based on the second posture data after the blade deformation (including the spatial point coordinate data and quaternion data of the 1D beam node), the deformed grid points are pre-set interpolated (for example, but not limited to, quaternion Slerp interpolation), and the deformation mapping quaternion data of the deformed grid points mapped on the 1D beam is calculated. The specific solution process is described below using a formula.

[0116] For the predetermined 3D surface mesh nodes of the blade, from q t0 (which can represent the quaternion corresponding to the leaf before deformation) to q t The rotation transformation quaternion q (which can represent the quaternion corresponding to the deformed blade) can be expressed as the following formula (13):

[0117] q=q t ·q t0 -1 (13)

[0118] In addition, it is known that any vector along the rotation axis u defined by the unit vector (containing three components u x 、uy 、u z ) The rotation vector obtained after the angle θ is rotated can be obtained by matrix multiplication, that is, the rotation vector is equal to the rotation matrix multiplied by the arbitrary vector before rotation. Combining equations (1) to (3), we can get a, b, c, d and u in the quaternion x 、u y 、u z The relationship between , is shown in equation (14):

[0119]

[0120] Therefore, according to the above conversion relationship between quaternion and rotation matrix, the rotation matrix R shown in the following formula (15) can be calculated:

[0121]

[0122] For any 3D surface mesh node of the blade before deformation, its spatial coordinates can be expressed as a vector P, and the rotational displacement change vector [dxi′, dyi′, dzi′] of any 3D surface mesh node of the blade after deformation in the global coordinate system can be expressed as the following formula (16):

[0123] [dxi′, dyi′, dzi′]=RP-P (16)

[0124] Finally, the deformation vector of each 3D surface mesh node of the blade from before deformation to after deformation can be expressed as the superposition of three-directional translation components and three-directional rotation components, that is, [dxi′, dyi′, dzi′] + [dxi, dyi, dzi].

[0125] According to the embodiments of the present disclosure, through the above-mentioned deformation mapping method, the present disclosure can achieve high-precision interpolation mapping of the deformation displacement of the one-dimensional beam node to the three-dimensional blade during the CFD and CSD interactive coupling process.

[0126] According to an embodiment of the present disclosure, the data processing method may further include: updating the current fluid dynamic load based on the deformation vector, and returning to step S300.

[0127] Optionally, the step of updating the current fluid dynamic load may include: calculating the fluid dynamic vector of the three-dimensional surface mesh mapping on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid parameters corresponding to the deformation vector; calculating the fluid dynamic moment vector of the three-dimensional surface mesh mapping on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid dynamic vector; and updating the current fluid dynamic load of the three-dimensional surface mesh mapping on the one-dimensional beam based on the fluid dynamic vector and the fluid dynamic moment vector.

[0128] As an example, a predetermined threshold time length may be defined for the process of updating the current fluid dynamic load. That is, when the preset time required to update the fluid dynamic load a predetermined number of times is reached, the cyclic update operation may be terminated.

[0129] According to the embodiments of the present disclosure, through the updating process of the fluid dynamic load, the present disclosure can realize the efficient extraction of the aerodynamic load in the interactive coupling process of CFD and CSD.

[0130] Optionally, in actual application, the deformation of the blades may be coupled to the entire wind turbine, and there is no particular limit on the number of deformed blades.

[0131] According to the embodiments of the present disclosure, the deformation mapping algorithm based on fluid-solid coupling provided by the present disclosure can improve the reliability of blade strength, fatigue life, power curve, and tower clearance prediction, and can provide a reference for guiding the aerodynamic shape and blade structure finalization in the subsequent development process of new wind turbine generator sets.

[0132] The simulation application platform system and simulation results disclosed in the present invention are described in detail below.

[0133] Fig.11 is a schematic diagram showing a simulation application platform system according to an embodiment of the present disclosure. Fig. 12A and Fig. 12B is a schematic diagram showing simulation results according to an embodiment of the present disclosure. Fig.13 is a schematic diagram showing another simulation result according to an embodiment of the present disclosure.

[0134] Reference Fig.11 , the steps for implementing the above data processing method in the simulation application platform system are as follows: the first step is to configure the CFD solver according to the simulation working condition parameters, read the parameters of the wind field acting on the blade and the initial data of the 1D beam posture corresponding to the blade (pre-deformation data); the second step is to perform CFD calculations based on, for example, a predetermined computing platform (for example, but not limited to, a supercomputing platform), calculate the aerodynamic load on the 3D surface grid, and execute the above load mapping method from the 3D surface grid of the blade to the 1D beam node; the third step is to input the aerodynamic load into the 1D beam structure solver of the blade to solve the structural deformation response; the fourth step is to obtain the deformation vector of the 3D surface grid node based on the above deformation mapping method from the 1D beam to the 3D surface grid, and then update the grid parameters of the CFD solver, thereby updating the aerodynamic load in the second step, and repeat the second, third, and fourth steps until the simulation calculation requirements are met (for example, but not limited to, reaching a preset duration).

[0135] The effect of the deformation mapping method according to the present disclosure will be illustrated below using a simulation example of air acting on a blade.

[0136] As a simulation example, the initial calculation conditions are as follows: wind speed is 30m / s, wind shear coefficient is 0.2, blade pitch angle is 90deg, blade azimuth angle is 0deg, wind deviation is 0deg, attitude data of 1D beam nodes corresponding to the blade (the number is 68, numbered 0-67 respectively) and mesh data of the 3D surface mesh of the blade. The attitude of the 1D beam node at the initial moment (i.e., before deformation) is shown in Table 1 below:

[0137]

[0138]

[0139] Here, as an example, the initial calculation conditions may come from SCADA data commonly used in the wind power field, but the present disclosure is not limited thereto.

[0140] During the execution of the method, the mapping of the aerodynamic load to the 1D beam node corresponding to the blade (i.e., the three-directional component forces and three-directional moments loaded to the 1D beam node) is shown in Table 2 below:

[0141]

[0142]

[0143] During the execution of the method, the structural deformation response of the 1D beam node is shown in Table 3:

[0144]

[0145]

[0146] Since the number of 3D mesh nodes of a blade is generally in the millions, it is not convenient to display it in the form of a data table. In this disclosure, cloud coloring is used for display. During the execution of the method, the deformation mapping result of the blade from the 1D beam to the 3D mesh is as follows: Fig. 12A and Fig. 12B See Fig. 12A and Fig. 12B The pink colored blades represent the undeformed blade posture at the initial moment, the red and blue colored blades represent the deformation mapping results of the blades at the predetermined moment after deformation, and the red dots represent the 1D beam nodes. From the above simulation results, it can be seen that as the position of the 1D beam node changes, the 3D grid points on the blades follow the 1D beam nodes to perform three-dimensional six-degree-of-freedom deformation (including three-degree-of-freedom translation + three-degree-of-freedom rotation), and the blades remain smooth before and after deformation.

[0147] In addition, refer to Fig.13 , Fig.13 The CFD flow field calculation cloud diagram related to wind speed is shown. Fig.13It can be seen that the CFD flow field calculation is numerically stable, which further proves the effectiveness of the algorithm.

[0148] In addition, in terms of the prediction of wind turbine power generation, since a slight blade twist may cause local stall of the blade, resulting in a loss of power generation, the deformation mapping algorithm based on fluid-solid coupling provided in the present disclosure can greatly improve the prediction accuracy of the wind turbine power generation and help draw the power curve of the wind turbine.

[0149] Fig.14 is a block diagram showing a data processing device according to an embodiment of the present disclosure. Fig.14 As shown, the data processing device includes an acquisition unit 100 , a load calculation unit 200 and a deformation mapping unit 300 .

[0150] According to an embodiment of the present disclosure, the acquisition unit 100 is configured to: acquire first posture data of a one-dimensional beam corresponding to the flexible rod-barrel assembly, first mesh data of a three-dimensional surface mesh of the flexible rod-barrel assembly, and fluid parameters associated with the fluid acting on the flexible rod-barrel assembly.

[0151] According to an embodiment of the present disclosure, the acquisition unit 100 is further configured to acquire second posture data of the one-dimensional beam corresponding to the flexible rod-barrel assembly deformed by applying the current fluid dynamic load.

[0152] According to an embodiment of the present disclosure, the load calculation unit 200 is configured to calculate the current fluid dynamic load based on the first posture data, the first grid data and the fluid parameters.

[0153] According to an embodiment of the present disclosure, the deformation mapping unit 300 is configured to calculate a deformation vector of a three-dimensional surface mesh of the flexible shaft barrel assembly deformed by applying a current fluid dynamic load based on the first posture data, the first mesh data, and the second posture data. Here, the deformation vector is used to characterize the degree of deformation of the flexible shaft barrel assembly.

[0154] Optionally, the deformation mapping unit 300 is configured to: calculate the mapping posture data of the grid points of the three-dimensional surface grid mapped on the one-dimensional beam based on the first posture data and the first grid data; calculate the translational displacement change vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod barrel assembly based on the second posture data and the first grid data; calculate the rotational displacement change vector of the deformed grid points based on the second posture data and the mapping posture data; and calculate the deformation vector by adding the translational displacement change vector to the rotational displacement change vector.

[0155] The data processing device according to the present disclosure can be used to execute the above-mentioned data processing method. In order to avoid repetition, descriptions similar to those in the above-mentioned data processing method will not be repeated.

[0156] In summary, according to the data processing method and device of the embodiment of the present disclosure, through the data processing method based on fluid-solid coupling, it is possible to effectively improve the calculation accuracy of the fluid dynamic load acting on the flexible rod barrel assembly and the deformation prediction accuracy of the flexible rod barrel assembly, improve the data calculation efficiency in the relevant calculation process and reduce the data calculation resource consumption. Therefore, through the present disclosure, it is possible to effectively solve the problem of relatively low calculation efficiency and high calculation resource consumption of the relevant algorithms for the action of fluid on the flexible rod barrel assembly in the prior art. At the same time, according to the data processing method based on fluid-solid coupling of the present disclosure, the load and deformation of the blade can be calculated more accurately in the early design of the wind turbine, which is helpful to deeply understand the vibration behavior of the blade, guide the optimization design and performance evaluation of the blade, and improve the reliability of the prediction of blade strength, fatigue life, power curve, and tower clearance.

[0157] According to an embodiment of the present disclosure, a computer-readable storage medium storing instructions is provided, wherein when the instructions are executed by at least one computing device, the at least one computing device is prompted to execute a data processing method as described in any of the above embodiments.

[0158] According to an embodiment of the present disclosure, a system is provided that includes at least one computing device and at least one storage device storing instructions, wherein the instructions, when executed by the at least one computing device, prompt the at least one computing device to execute a data processing method as described in any of the above embodiments.

[0159] Although some embodiments of the present disclosure have been shown and described, it will be appreciated by those skilled in the art that modifications may be made to the embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents.

Claims

1. A data processing method, characterized in that: The data processing method comprises: Acquire first posture data of a one-dimensional beam corresponding to a flexible rod-barrel assembly, first mesh data of a three-dimensional surface mesh of the flexible rod-barrel assembly, and fluid parameters associated with a fluid acting on the flexible rod-barrel assembly; Calculate a current fluid dynamic load based on the first posture data, the first grid data and the fluid parameters; acquiring second posture data of the one-dimensional beam corresponding to the flexible rod-barrel assembly deformed by applying the current fluid dynamic load; Based on the first posture data, the first mesh data and the second posture data, a deformation vector of the three-dimensional surface mesh of the flexible barrel assembly deformed by applying the current fluid dynamic load is calculated, and the deformation vector is used to represent the deformation degree of the flexible barrel assembly.

2. The data processing method according to claim 1, characterized in that: The data processing method further includes: updating the current fluid dynamic load based on the deformation vector, and returning to the step of acquiring the second posture data.

3. The data processing method according to claim 1, characterized in that: The first posture data and the second posture data include spatial point coordinate data and quaternion data of a beam node of a one-dimensional beam, wherein the spatial point coordinate data indicates the spatial position of the beam node in a global coordinate system, and the quaternion data indicates the rotational posture of the beam node in the global coordinate system.

4. The data processing method according to claim 1, characterized in that: The first mesh data includes spatial point coordinate data of mesh nodes of the three-dimensional surface mesh in a global coordinate system.

5. The data processing method according to claim 1, characterized in that: The step of calculating the deformation vector includes: calculating the deformation vector by applying a preset interpolation algorithm to the first posture data, the first mesh data and the second posture data.

6. The data processing method according to claim 1, characterized in that: The step of calculating the deformation vector comprises: Based on the first posture data and the first grid data, calculating mapping posture data of grid points of the three-dimensional surface grid mapped onto the one-dimensional beam; Calculating a translational displacement variation vector of a deformed grid point of a three-dimensional surface grid of the deformed flexible rod barrel assembly based on the second posture data and the first grid data; Calculating a rotation displacement variation vector of the deformed grid point based on the second posture data and the mapped posture data; The deformation vector is calculated by adding the translation displacement variation vector and the rotation displacement variation vector.

7. The data processing method according to claim 6, characterized in that: The step of calculating the mapping posture data of the grid points of the three-dimensional surface grid mapped on the one-dimensional beam comprises: Based on the first grid data, applying a first preset interpolation algorithm to the first posture data to calculate the mapping space point coordinate data of the grid points mapped on the one-dimensional beam; Based on the first posture data and the mapping space point coordinate data, a second preset interpolation algorithm different from the first preset interpolation algorithm is applied to the grid points to calculate the mapping quaternion data of the grid points mapped on the one-dimensional beam to obtain the mapping posture data including the mapping space point coordinate data and the mapping quaternion data.

8. The data processing method according to claim 6, characterized in that: The step of calculating the translational displacement variation vector of the deformed grid points of the three-dimensional surface grid of the deformed flexible rod barrel assembly comprises: Calculating a translation displacement change vector of the one-dimensional beam corresponding to the deformed flexible rod-barrel assembly based on the first posture data and the second posture data; Based on the first grid data, a preset interpolation algorithm is applied to the translational displacement variation vector of the one-dimensional beam to calculate the translational displacement variation vector of the deformed grid point.

9. The data processing method according to claim 6, characterized in that: The step of calculating the rotation displacement variation vector of the deformed grid point comprises: Based on the second posture data, a preset interpolation algorithm is applied to the deformed grid points to calculate deformation mapping quaternion data of the deformed grid points mapped on the one-dimensional beam; Based on the first mesh data and the deformation mapping quaternion data, a rotation displacement change vector of the deformation mesh point is calculated.

10. The data processing method according to claim 2, characterized in that: The step of updating the current fluid dynamic load comprises: Calculate the fluid dynamic vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid parameter corresponding to the deformation vector; Calculate the fluid dynamic moment vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data, the deformation vector and the fluid dynamic vector; The three-dimensional surface mesh is updated to map the current hydrodynamic load on the one-dimensional beam based on the hydrodynamic vector and the hydrodynamic moment vector.

11. The data processing method according to claim 1, characterized in that: The steps to calculate the current fluid dynamic loads include: Calculate the fluid dynamic vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data and the fluid parameters; Calculate the fluid dynamic moment vector of the three-dimensional surface mesh mapped on the one-dimensional beam based on the first mesh data and the fluid dynamic vector; The current fluid dynamic load mapped by the three-dimensional surface mesh on the one-dimensional beam is calculated based on the fluid dynamic vector and the fluid dynamic moment vector.

12. A data processing device, characterized in that: The data processing device comprises: An acquisition unit is configured to: acquire first posture data of a one-dimensional beam corresponding to a flexible rod-barrel assembly, first mesh data of a three-dimensional surface mesh of the flexible rod-barrel assembly, and fluid parameters associated with a fluid acting on the flexible rod-barrel assembly; The acquisition unit is further configured to: acquire second posture data of the one-dimensional beam corresponding to the flexible rod-barrel assembly deformed by applying the current fluid dynamic load; A load calculation unit, configured to: calculate a current fluid dynamic load based on the first posture data, the first grid data and the fluid parameter; A deformation mapping unit is configured to calculate a deformation vector of the three-dimensional surface mesh of the flexible rod barrel assembly deformed by applying the current fluid dynamic load based on the first posture data, the first mesh data and the second posture data, wherein the deformation vector is used to characterize the degree of deformation of the flexible rod barrel assembly.

13. The data processing device according to claim 12, characterized in that: The deformation mapping unit is configured to: Based on the first posture data and the first grid data, calculating mapping posture data of grid points of the three-dimensional surface grid mapped onto the one-dimensional beam; Calculating a translational displacement variation vector of a deformed grid point of a three-dimensional surface grid of the deformed flexible rod barrel assembly based on the second posture data and the first grid data; Calculating a rotation displacement variation vector of the deformed grid point based on the second posture data and the mapped posture data; The deformation vector is calculated by adding the translation displacement variation vector and the rotation displacement variation vector.

14. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to perform the data processing method according to any one of claims 1 to 11.

15. A computer device, characterized in that: include: at least one processor; at least one memory storing computer executable instructions, Wherein, when the computer executable instructions are executed by the at least one processor, the at least one processor is prompted to execute the data processing method according to any one of claims 1 to 11.

Images