Building structure modeling method and device based on BIM, equipment and medium

Abstract

The invention relates to a BIM (Building Information Modeling)-based building structure modeling method, device, equipment and medium, and the method comprises the steps: aiming at a curvature-mechanics semantic fault problem existing in a process of converting a special-shaped curved surface structure from a BIM geometric model to finite element analysis, generating a curvature tensor field with parameter coordinates by analyzing an NURBS curved surface; integrating along the maximum curvature change direction to construct an internal force flow function, and forming a guide field for controlling the grid density; shell / beam units are divided based on the guide field gradient, space coordinates are marked, and a curvature-stiffness matrix and an internal force flow driving variable cross-section are combined for calculation to generate a structural analysis model; the gradient distribution of the guide field is dynamically corrected through displacement error feedback, and lossless transmission of geometric topology and mechanical properties is achieved. According to the method, the distortion risk of special-shaped structure analysis is remarkably reduced, artificial experience correction is avoided, and high-precision automatic modeling support is provided for a complex building structure.

Description

Technical Field

[0001] This invention relates to the field of digital model building technology, specifically to a BIM-based building structure modeling method, device, equipment, and medium. Background Technology

[0002] In the design of complex building structures, the mechanical analysis of irregular curved surfaces often relies on the collaborative work of Building Information Modeling (BIM) and finite element software. The current industry standard workflow involves exporting the geometric model (usually represented as a NURBS surface) from the BIM system to structural analysis software, generating a finite element mesh through geometric transformation, assigning standardized mechanical properties, and then performing simulation calculations. This method is applicable to regular structures, but when dealing with irregular structures such as hypercurvature and freeform surfaces, the mapping process between geometric data and mechanical properties has inherent flaws.

[0003] The main problem with existing technologies is that the mechanical behavior of curved structures is highly dependent on local curvature distribution (such as moment transfer paths and stress concentration areas), while the pure geometric models exported by BIM software lose the curvature-mechanical semantic relationship during format conversion. This causes structural analysis software to be unable to accurately reconstruct the curvature-driven stiffness matrix and internal force transfer paths, especially in high-curvature transition areas such as surface junctions and cantilever edges, resulting in significant calculation distortion. Although some improvement schemes attempt to compensate for errors by refining the mesh or manually correcting parameters, they fail to fundamentally solve the semantic gap between geometric topology and mechanical properties. This leads to an over-reliance on empirical coefficients for the safety redundancy design of irregular structures, increasing construction costs and creating potential risks. Summary of the Invention

[0004] Based on this, the purpose of the present invention is to provide a BIM-based building structure modeling method, device, equipment and medium that can achieve lossless conversion between geometric data and mechanical properties.

[0005] The objective of this invention is achieved through the following solution:

[0006] In a first aspect, the present invention provides a BIM-based building structure modeling method, comprising the following steps:

[0007] S1: Process the NURBS surface exported from the building information modeling system, calculate the curvature properties of each point on the NURBS surface through second-order partial derivatives, and generate a curvature tensor field with parameter coordinates.

[0008] S2: Process the curvature tensor field, extract the principal curvature direction field and integrate along the direction of maximum curvature change to construct the internal force flow function, and generate the guiding field that controls the mesh density;

[0009] S3: Based on the gradient magnitude of the guide field, the shell element and beam element are divided according to the preset first gradient threshold, and a marked mesh with center coordinates and axis parameters is generated.

[0010] S4: Perform curvature-stiffness matrix calculations on shell elements in the marked mesh, perform variable cross-section calculations driven by internal force flow on beam elements, and generate a structural analysis model;

[0011] S5: Perform finite element analysis on the structural analysis model to obtain the displacement field. When the displacement error exceeds the preset second gradient threshold, perform weighted correction on the gradient distribution of the guide field and update the spatial distribution parameters of the guide field.

[0012] In one embodiment, S1 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0013] S11: Perform control point topology analysis on the NURBS surface data input from the building information modeling software, extract the control point coordinate matrix and parameter domain boundary, and generate a discretized parameter mesh;

[0014] S12: Calculate the first-order partial derivatives of the surface on the discretized parameter mesh, solve the unit normal vector based on the orthogonality of the tangent plane, and generate a global normal vector field;

[0015] S13: Perform surface second-order partial derivative fusion on the normal vector field, and generate a curvature tensor field with parameterized coordinates by combining the curvature component calculation formula.

[0016] In one embodiment, S2 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0017] S21: Perform eigenvalue decomposition on the curvature tensor field, separate the unit vectors of the maximum curvature direction and the minimum curvature direction, and generate an orthogonal principal curvature direction field;

[0018] S22: The orthogonal principal curvature direction field is integrated along the curvature gradient direction. The coupling effect between the curvature direction and the path tangent is accumulated by vector superposition to generate the internal force flow function field.

[0019] S23: Perform spatial gradient field calculation on the internal force flow function field, and generate principal direction weight coefficients by combining the eigenvalue ratios of the orthogonal principal curvature direction fields, thereby generating a guiding field that controls the grid density distribution.

[0020] In one embodiment, S3 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0021] S31: Extract the gradient modulus of the guiding field, convert the curvature change intensity through an exponential decay function, and generate an adaptive mesh size function;

[0022] S32: The parametric coordinate domain of the curvature tensor field is subjected to constrained Delaunay triangulation, and the element side length is dynamically adjusted according to the mesh size function to generate a finite element mesh with topological association.

[0023] S33: Perform gradient threshold judgment processing on the finite element mesh. Based on the preset first gradient threshold, mark the high curvature region elements as shell elements and record the centroid coordinates, and mark the low curvature region elements as beam elements and record the axis parameter equations to generate a marked mesh with spatial marking.

[0024] In one embodiment, S4 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0025] S41: Perform principal curvature direction matching processing on the centroid coordinates of the marked mesh shell elements, reconstruct the material constitutive relation through the local coordinate system rotation matrix, and generate the curvature-driven stiffness matrix;

[0026] S42: Sample the internal force flow function of the beam element axis parametric equation of the marked mesh, calculate the nonlinear change of cross-sectional area based on the stress attenuation model, and generate the variable cross-sectional property distribution function;

[0027] S43: The stiffness matrix and variable cross-section property distribution function are processed by finite element assembly. The structural stiffness relationship is integrated by nodal degree of freedom association and boundary condition constraints to generate a structural analysis model to guide structural strength analysis.

[0028] Secondly, the present invention provides a BIM-based building structure modeling device, which is configured with the following modules:

[0029] The curvature tensor calculation module is used to process the NURBS surface exported from the building information modeling system. It calculates the curvature properties of each point on the NURBS surface through second-order partial derivatives and generates a curvature tensor field with parameterized coordinates.

[0030] The guide field generation module is used to process the curvature tensor field, extract the principal curvature direction field, integrate along the direction of maximum curvature change to construct the internal force flow function, and generate the guide field that controls the mesh density.

[0031] The element type partitioning module is used to process the gradient magnitude based on the guide field, and divides shell elements and beam elements according to the preset first gradient threshold to generate a marked mesh with center coordinates and axis parameters.

[0032] The structural model building module is used to calculate the curvature-stiffness matrix of shell elements in the marked mesh, calculate the variable cross section driven by internal force flow for beam elements, and generate a structural analysis model.

[0033] The guide field correction module is used to obtain the displacement field by performing finite element analysis on the structural analysis model. When the displacement error exceeds the preset second gradient threshold, the gradient distribution of the guide field is weighted and corrected to update the spatial distribution parameters of the guide field.

[0034] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the above-mentioned BIM-based building structure modeling methods.

[0035] Fourthly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the above-mentioned BIM-based building structure modeling methods.

[0036] In summary, the BIM-based building structure modeling method provided in this application generates a curvature tensor field with parametric coordinates based on the second-order partial derivative calculation of NURBS surfaces. This achieves precise binding between geometric topology and mechanical behavior, ensuring lossless transmission of curvature distribution characteristics in subsequent processes. Secondly, by integrating along the direction of maximum curvature change to construct an internal force flow function and generate a guiding field, a physically driven expression of the structural internal force transmission path can be realized, effectively capturing the stress concentration characteristics of high curvature regions. Furthermore, based on the gradient of the guiding field, shell / beam elements are adaptively partitioned and spatial coordinates are marked. Combined with curvature-stiffness matrix reconstruction and internal force flow-driven variable cross-section calculation, dynamic coupling of mechanical properties and geometric features is achieved, avoiding the distortion risk caused by standardized attribute assignment in traditional methods. Finally, the guide field gradient distribution is dynamically corrected through a displacement error feedback mechanism, forming a closed-loop optimization system that can continuously calibrate the geometric-mechanical mapping relationship until convergence.

[0037] To better understand and implement this invention, the following detailed description is provided in conjunction with the accompanying drawings. Attached Figure Description

[0038] Figure 1 A flowchart illustrating a BIM-based building structure modeling method provided in this application embodiment;

[0039] Figure 2 This is a structural schematic diagram of a BIM-based building structure modeling device provided for another embodiment of this application. Detailed Implementation

[0040] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0042] In one embodiment, such as Figure 1 As shown, a BIM-based building structure modeling method is provided. This embodiment illustrates the method's application to a terminal, but it is understood that the method can also be applied to a server, or to a device including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0043] S1: Process the NURBS surface exported from the Building Information Modeling System, calculate the curvature properties of each point on the NURBS surface through second-order partial derivatives, and generate a curvature tensor field with parameterized coordinates.

[0044] Specifically, the system reads NURBS surface data exported from the Building Information Modeling (BIM) system. This data is stored in a standard format. The system parses the standard format and identifies parameters such as the order of the B-spline basis functions, weight factors, and control vertices contained in the format. Through the mapping relationship between parameters and data storage addresses, a one-to-one correspondence is established to ensure that the storage location of the parameters can be accurately located during subsequent calls. Based on the mathematical expression of the NURBS surface, the system determines the coordinate functions corresponding to the two parameters u and v in the parameter domain. The system calculates the second-order partial derivatives in the u direction, the v direction, and the mixed second-order partial derivatives of uv for the coordinate functions. During the calculation process, the results of each partial derivative are recorded in the order of the parameter coordinates, forming an ordered partial derivative dataset. Each entry in the dataset contains the parameter coordinates and the corresponding partial derivative value.

[0045] For example, the system combines the calculated first-order partial derivatives with a vector cross product to obtain an initial normal vector. A normalization algorithm is then used to process this initial normal vector, yielding unit normal vectors at each parameter coordinate. Simultaneously, the direction of the normal vectors is verified through the directional relationship of the first-order partial derivatives, ensuring consistency with the surface orientation. The system substitutes the second-order partial derivatives and unit normal vectors into the calculation logic for the first and second fundamental form coefficients, obtaining the corresponding coefficients through vector dot product, modulus calculation, and other operations. Based on these coefficients, the system uses an eigenvalue decomposition algorithm to construct the curvature tensor corresponding to each parameter coordinate. This algorithm yields the eigenvalues ​​and eigenvectors of the curvature tensor, corresponding to the principal curvature and principal curvature directions, respectively. Using the parameter coordinates as indexes, the system binds the three-dimensional spatial coordinates with the principal curvature and principal curvature directions, arranging all data entries in parameter coordinate order and storing them as a readable and writable curvature tensor field file.

[0046] S2: Process the curvature tensor field, extract the principal curvature direction field, and integrate along the direction of maximum curvature change to construct the internal force flow function, generating the guiding field that controls the mesh density.

[0047] Specifically, the system uses the eigenvalue decomposition algorithm from linear algebra to process each extracted curvature tensor. This algorithm yields two eigenvalues ​​and two eigenvectors. The eigenvalues ​​correspond to the principal curvatures, and the eigenvectors correspond to the directions of action of the principal curvatures. The system employs a numerical difference calculation algorithm to obtain the absolute value of the difference between the two principal curvatures at each parameter coordinate. This absolute value of the difference is associated with the eigenvector, and a comparison algorithm is used to select the eigenvector with the largest absolute value of the difference, which is determined as the direction of the maximum curvature change. This direction vector is recorded according to the parameter coordinates, forming a direction vector dataset.

[0048] For example, the system uses the preset parameter coordinates of the curved surface boundary as the starting point and performs numerical integration along the direction of maximum curvature change using the fourth-order Runge-Kutta algorithm. Before integration, the gradient information of the principal curvature difference is calculated using the finite difference algorithm. This gradient information is used as a weighting factor in the integration process. The results are recorded after each integration step, gradually constructing the internal force flow function. The system uses a numerical gradient algorithm to calculate the gradients in the u and v directions of the internal force flow function, obtaining the gradient vectors at each parameter coordinate, which constitute the spatial distribution vector of the guide field. The system stores the x, y, and z components of the guide field and the gradient magnitude values ​​in different data segments. The two data segments are linked by the parameter coordinates to form a guide field file. The gradient magnitude values ​​are used for mesh density calculation, and the components are used for mesh generation direction guidance.

[0049] S3: Based on the gradient magnitude of the guide field, the shell element and beam element are divided according to the preset first gradient threshold, and a marked mesh with center coordinates and axis parameters is generated.

[0050] Specifically, the system calls the guide field file and extracts gradient magnitude data in parameter coordinate order through the data reading interface, while retrieving the first gradient threshold from the preset parameter library. The system employs a threshold verification algorithm to compare the first gradient threshold with the stress analysis accuracy standard corresponding to the structural type; if a mismatch is found, the appropriate threshold is reloaded. The system uses a point-by-point comparison algorithm to compare the gradient magnitude at each parameter coordinate with the first gradient threshold one by one, classifying the element type based on the results: when the gradient magnitude exceeds the threshold, it is determined to be a potential stress concentration region, and a beam element partitioning algorithm is used to record the axis start and end coordinates, determining the cross-sectional direction vector through the surface normal vector; when it does not exceed the threshold, it is determined to be a conventional stress region, and a shell element partitioning algorithm is used to record the center coordinates, determining the element surface normal vector through the surface normal vector. The system uses a numerical mapping algorithm, based on the inverse relationship between gradient magnitude and element size, to calculate the element size for each region, ensuring that the element size in stress concentration regions meets the analysis accuracy requirements. The system uses a parameter coordinate matching algorithm to associate element information (ID, type, geometric parameters) with the principal curvature parameters of the corresponding parameter coordinates in the curvature tensor field, forming marked mesh data entries.

[0051] S4: Perform curvature-stiffness matrix calculations on shell elements in the marked mesh, perform variable cross-section calculations driven by internal force flow on beam elements, and generate a structural analysis model.

[0052] Specifically, the system calls upon the marked mesh file and employs an element data extraction algorithm to extract the principal curvature parameters and geometric parameters of the shell elements by element ID. Among the geometric parameters, the side lengths are obtained from the mesh generation dimension data, and the thickness is read from the surface additional attributes exported from the BIM system. Based on thin plate bending theory, the system uses a matrix construction algorithm to substitute the principal curvature parameters into the calculation logic of the geometric stiffness matrix, forming the shell element's geometric stiffness matrix through matrix multiplication. The system retrieves the corresponding material properties from the material database and uses a constitutive matrix generation algorithm. Based on the constitutive relations of material mechanics and combined with parameters such as elastic modulus and Poisson's ratio, it calculates the shell element material constitutive matrix.

[0053] Preferably, the system employs a numerical integration algorithm, substituting the geometric stiffness matrix and material constitutive matrix into the integration logic, covering the shell element area to complete the integration, thus obtaining the shell element stiffness matrix. The system uses a linear mapping algorithm, establishing a linear relationship between the internal force flow function and the beam element section parameters (height, width) based on the numerical variation law of the internal force flow function, and calculating the section parameters. The system uses a data matching algorithm to extract load and boundary condition data from the BIM model and associate them with corresponding elements and nodes according to component ID. The system uses a finite element matrix assembly algorithm to integrate the shell element stiffness matrix, beam element section parameters, loads, and boundary conditions, assembling them into an overall stiffness matrix, forming a structural analysis model in standard finite element format.

[0054] S5: Perform finite element analysis on the structural analysis model to obtain the displacement field. When the displacement error exceeds the preset second gradient threshold, perform weighted correction on the gradient distribution of the guide field and update the spatial distribution parameters of the guide field.

[0055] Specifically, the system applies load data to the structural analysis model, derives and solves the finite element equilibrium equations based on the principle of virtual work using a matrix factorization algorithm, and obtains the displacement vectors of each node. Preferably, the system can use a coordinate mapping algorithm to organize the displacement vectors according to the spatial coordinates of the nodes, forming a displacement field. The system retrieves the allowable displacement data of the corresponding structure from the specification database, uses a component matching algorithm to match the allowable displacement value according to the component type to which the node belongs, and then uses a difference calculation algorithm to obtain the displacement error of each node and retain the positive and negative signs.

[0056] Furthermore, the system loads a second gradient threshold from a preset parameter library and uses a node-by-node comparison algorithm to compare the absolute value of the displacement error with the second gradient threshold. If all errors meet the threshold, the correction stops; if any errors exceed the threshold, the correction process is triggered. After correction is triggered, the system uses an extreme value search algorithm to determine the maximum error value, calculates the ratio of each node's displacement error to the maximum error value using a proportional coefficient algorithm, and obtains a weighting coefficient by combining it with the correction coefficient. Preferably, the system can use a linear correction algorithm to adjust the gradient magnitude of the guide field based on the weighting coefficient, keeping the direction vector unchanged, updating the guide field data and overwriting the original file. The system calls the new guide field file, re-executes steps S3 and S4, and repeats the error calculation and correction process until all displacement errors meet the threshold, outputting the final structural analysis model.

[0057] In summary, the BIM-based building structure modeling method provided in this application generates a curvature tensor field with parametric coordinates based on the second-order partial derivative calculation of NURBS surfaces. This achieves precise binding between geometric topology and mechanical behavior, ensuring lossless transmission of curvature distribution characteristics in subsequent processes. Secondly, by integrating along the direction of maximum curvature change to construct an internal force flow function and generate a guiding field, a physically driven expression of the structural internal force transmission path can be realized, effectively capturing the stress concentration characteristics of high curvature regions. Furthermore, based on the gradient of the guiding field, shell / beam elements are adaptively partitioned and spatial coordinates are marked. Combined with curvature-stiffness matrix reconstruction and internal force flow-driven variable cross-section calculation, dynamic coupling of mechanical properties and geometric features is achieved, avoiding the distortion risk caused by standardized attribute assignment in traditional methods. Finally, the guide field gradient distribution is dynamically corrected through a displacement error feedback mechanism, forming a closed-loop optimization system that can continuously calibrate the geometric-mechanical mapping relationship until convergence.

[0058] In one embodiment, S1 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0059] S11: Perform control point topology analysis on the NURBS surface data input from the Building Information Modeling (BIM) software, extract the control point coordinate matrix and parameter domain boundary, and generate a discretized parameter mesh.

[0060] Specifically, the system receives NURBS surface data input from Building Information Modeling (BIM) software. This data includes a set of control points, the order of the B-spline basis functions, weight factors, and node vectors. The system initiates control point topology analysis, employing an adjacency matrix construction algorithm to associate control points along the u and v parameter directions, forming a topology graph and excluding isolated control points. The system then uses a matrix extraction algorithm to construct a control point coordinate matrix based on the number of control points in the u direction (m+1) and the v direction (n+1), using the following formula:

[0061] P = [P] i,j ] (m+1)×(n+1)

[0062] Among them, P i,j Let (x, y, z) be the three-dimensional coordinates of the control point in the i-th row and j-th column, and m and n be the orders of the B-spline basis functions in the u and v directions, respectively. Based on the node vectors, the system uses a boundary recognition algorithm to extract node values ​​whose repetition count equals the order of the basis functions, thus determining the parameter domain boundary (u∈[u...]). start ,u end ], v∈[v start ,v end Preferably, the system can use a parametric discretization algorithm to divide parameter points, arranging them in the order of u and v directions to form a discretized parameter grid, where each grid node contains parameter coordinates (u...). i ,v j The coordinates and indexes of the control points are stored as a structured data file.

[0063] S12: Calculate the first-order partial derivatives of the surface on the discretized parameter mesh, solve for the unit normal vector based on the orthogonality of the tangent plane, and generate a global normal vector field.

[0064] Specifically, the system calls the discretized parameter mesh file and extracts the NURBS surface parameter information corresponding to the mesh nodes. Preferably, the system can use the de Boer-Cox algorithm to solve for the first-order bias in the u-direction of each node. First-order deflection in the v direction Boundary nodes are supplemented with calculations using forward / backward differencing algorithms. The system is based on the orthogonality of the tangent planes, and the initial normal vector is obtained through the cross product, as shown in the formula:

[0065]

[0066] in, Let u be the tangent vector of the surface in the u direction. Let v be the tangent vector to the surface in the direction v, and the cross product direction is determined by the right-hand rule. The system uses a normalization algorithm to... Dividing each component by its magnitude yields the unit normal vector. Abnormal vectors are excluded through modulus threshold verification. The system uses parameter coordinates (u) i ,v j Using the index ) as the associated unit normal vector, the data is organized to form a global normal vector field and stored as a file containing a column of parameter coordinates and a column of normal vector components.

[0067] S13: Perform surface second-order partial derivative fusion on the normal vector field, and generate a curvature tensor field with parameterized coordinates by combining the curvature component calculation formula.

[0068] Specifically, the system calls the global normal vector field file, loads the NURBS surface basis function information, and initiates second-order partial derivative fusion, employing a second-order difference algorithm to... Find the partial derivative in the u direction. right Find the partial derivative in the v direction. right Find the partial derivative in the v direction. Combine the three with the unit normal vector Correlation, combined with the curvature component calculation logic, uses the vector dot product algorithm to find the coefficients of the second fundamental form:

[0069]

[0070] in, The unit normal vector is used, and each second-order deflection vector is the surface curvature vector in the corresponding direction. After the system calculates the first fundamental form coefficients (E, F, G), it constructs the curvature tensor using an eigenvalue decomposition algorithm, with parametric coordinates (u... i ,v j Bind the curvature tensor to generate a curvature tensor field file with parameterized coordinates.

[0071] In one embodiment, S2 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0072] S21: Perform eigenvalue decomposition on the curvature tensor field, separate the unit vectors of the maximum curvature direction and the minimum curvature direction, and generate an orthogonal principal curvature direction field.

[0073] Specifically, the system invokes a curvature tensor field with parameterized coordinates, first extracting the curvature tensor components corresponding to each parameter point. These components contain multiple independent elements reflecting the bending characteristics of the surface. The system employs an eigenvalue decomposition algorithm from linear algebra to decompose the curvature tensor at each parameter point. The decomposition process follows the eigenvalue solving rules for tensor matrices, yielding the eigenvalues ​​and corresponding eigenvectors of the curvature tensor. The system then selects the largest and smallest eigenvalues ​​from the decomposition results, extracting the corresponding eigenvectors. These extracted eigenvectors are normalized, and the unit vectors in the direction of maximum curvature and minimum curvature are obtained by multiplying the reciprocal of the vector magnitude with the eigenvector.

[0074] For example, the system calculates the dot product of two unit vectors to verify their orthogonality. If the dot product result exceeds the allowable deviation range for orthogonality, the system adjusts the solution accuracy of the eigenvectors and performs eigenvalue decomposition and normalization again until the two unit vectors meet the orthogonality requirement. The system associates the unit vectors of the maximum curvature direction and the minimum curvature direction of each parameter point with the parameter coordinates of that point, and combines the orthogonal direction vectors of all parameter points according to the arrangement order of the parameter grid to form an orthogonal principal curvature direction field. Finally, the system checks the directional continuity of the orthogonal principal curvature direction field by comparing the angle between the unit vectors of the same curvature direction of adjacent parameter points to determine whether there is a sudden change in direction. If so, an interpolation algorithm is used to correct the unit vectors in the abrupt change region to ensure the overall continuity of the direction field. The corrected orthogonal principal curvature direction field data is then stored.

[0075] S22: The orthogonal principal curvature direction field is integrated along the curvature gradient direction. The coupling effect between the curvature direction and the path tangent is accumulated by vector superposition to generate the internal force flow function field.

[0076] Specifically, the system invokes the orthogonal principal curvature direction field and simultaneously reads the boundary constraint information of the building structure. It then filters out parameter points corresponding to the structural supports or fixed connections from the boundary constraint information, designating these parameter points as the starting points for geodesic integration, with each starting point corresponding to an initial integration value. Based on the changing trend of curvature values ​​in the orthogonal principal curvature direction field, the system determines the curvature gradient direction, which is determined by the direction of the difference in curvature values ​​between adjacent parameter points. The system employs a geodesic integration algorithm to integrate the orthogonal principal curvature direction field along the curvature gradient direction. During integration, the system calculates the path tangent vector at each point on the integration path in real time; this vector is determined by the rate of change of the path's parameter coordinates. The system performs vector superposition operations on the principal curvature direction unit vector at each point and the corresponding path tangent vector. By accumulating the coupling effect between the curvature direction and the path tangent, the accumulated result of the coupling effect is used as the internal force flow function value at that point. The accumulation process follows the superposition rules of vector operations to ensure that the result reflects the mutual influence between the curvature direction and the path direction.

[0077] The system iterates through all parameter points in the orthogonal principal curvature direction field according to the above process, assigns a corresponding internal force flow function value to each parameter point, and combines these function values ​​according to the arrangement order of the parameter grid to form the internal force flow function field. The system verifies the numerical continuity of the internal force flow function field by calculating the difference between the function values ​​of adjacent parameter points to determine whether there is a numerical abrupt change. If so, the integration step size is adjusted and integration is repeated until the function field is numerically continuous. After successful verification, the internal force flow function field data is stored.

[0078] S23: Perform spatial gradient field calculation on the internal force flow function field, and generate principal direction weight coefficients by combining the eigenvalue ratios of the orthogonal principal curvature direction fields, thereby generating a guiding field that controls the grid density distribution.

[0079] Specifically, the system calls the generated internal force flow function field and the generated orthogonal principal curvature direction field. First, it performs spatial gradient field calculation on the internal force flow function field, using a numerical differentiation algorithm to calculate the partial derivatives of the internal force flow function in the two orthogonal directions in the parameter domain at each parameter point. The calculation of the partial derivatives is based on the ratio of the change in function value at adjacent parameter points to the parameter interval. Boundary parameter points are corrected using a one-sided differential formula to ensure the accuracy of the partial derivative calculation. The system combines the partial derivatives in the two directions to form the gradient vector of each parameter point. The gradient vectors of all parameter points are arranged according to the parameter grid to form the spatial gradient field. Subsequently, the system extracts the maximum and minimum eigenvalues ​​of each parameter point in the orthogonal principal curvature direction field and calculates the proportional relationship between the two eigenvalues. This proportional relationship reflects the degree of curvature difference in the principal curvature direction. The system substitutes this proportional relationship into the preset weight coefficient calculation formula to generate the principal direction weight coefficient for each parameter point. The weight coefficient is positively correlated with the eigenvalue ratio to reflect the difference in the influence of different principal curvature directions on the grid density.

[0080] Furthermore, the system multiplies the gradient vector of the spatial gradient field with the principal direction weight coefficient of the corresponding parameter point. The result serves as the grid density control parameter for that point, containing information on density magnitude and direction. The system associates the grid density control parameters of all parameter points with their coordinates, arranging them according to the parameter grid to form a guiding field controlling the grid density distribution. Finally, the system checks the rationality of the grid density control parameters in the guiding field, ensuring that the parameter values ​​are within a preset valid range. If they exceed the range, the parameters in the weight coefficient calculation formula are adjusted and recalculated until all parameters are reasonable. Finally, the guiding field data is stored, providing a control basis for subsequent grid generation.

[0081] In one embodiment, S3 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0082] S31: Extract the gradient modulus of the guiding field, convert the curvature change intensity through an exponential decay function, and generate an adaptive mesh size function.

[0083] Specifically, the system invokes the guiding field that controls the grid density distribution, first extracting the grid density control parameters corresponding to each parameter point. These parameters contain information on density magnitude and direction. The system employs a numerical calculation method to calculate the gradient modulus of the grid density control parameters at each parameter point. The calculation process uses the ratio of the change in parameter at adjacent points to the parameter interval, obtaining the gradient modulus through the vector modulus formula. This modulus reflects the spatial variation intensity of the grid density control parameters. The system introduces an exponential decay function, substituting the calculated gradient modulus into the function to convert it into curvature change intensity. The conversion process follows the operational rules of the exponential function, ensuring a correspondence between the curvature change intensity and the gradient modulus, and that the change trend conforms to the grid size adjustment requirements.

[0084] The system correlates the converted curvature change intensity with a preset baseline grid size, generating a grid size value for each parameter point through function mapping. All parameter point grid size values ​​are arranged according to the parameter grid, forming an adaptive grid size function. The system verifies the rationality of the adaptive grid size function by checking the rate of change of grid size values ​​at adjacent parameter points to determine if there are any abnormal fluctuations. If so, the parameters of the exponential decay function are adjusted and the calculation is recalculated until the grid size value changes continuously. After successful verification, the adaptive grid size function data is stored.

[0085] S32: The parametric coordinate domain of the curvature tensor field is subjected to constrained Delaunay triangulation, and the element side length is dynamically adjusted according to the mesh size function to generate a finite element mesh with topological association.

[0086] Specifically, the system invokes a curvature tensor field with parameterized coordinates to extract the parameterized coordinate domain information. Simultaneously, it calls an adaptive mesh size function to perform constrained Delaunay triangulation on the parameterized coordinate domain. Boundary constraints are introduced during this process to ensure that the triangulation result does not exceed the parameter domain range and that the boundary contour is consistent with the parameter domain boundary. During triangulation, the system reads the mesh size value corresponding to each parameter point in the adaptive mesh size function in real time. Based on this value, it dynamically adjusts the side length of the generated triangular elements. Regions with smaller mesh size values ​​correspond to smaller element side lengths, while regions with larger mesh size values ​​correspond to taller element side lengths. The adjustment process follows the element generation rules of the triangulation algorithm to ensure that the element shape meets the requirements of finite element calculation.

[0087] Furthermore, the system establishes topological relationships for the generated triangular elements, recording the adjacent element numbers, shared edge information, and vertex coordinates of each element to form a topological relationship network between elements, ensuring the accuracy of data transfer in subsequent mechanical calculations. The system checks the quality of the finite element mesh by calculating indicators such as the interior angles and side length ratios of the elements to determine if there are any substandard elements. If so, the parameters of the triangulation algorithm are adjusted and reprocessed until the quality of all elements meets the requirements. Finally, the finite element mesh data with topological relationships is stored.

[0088] S33: Perform gradient threshold judgment processing on the finite element mesh. Based on the preset first gradient threshold, mark the high curvature region elements as shell elements and record the centroid coordinates, and mark the low curvature region elements as beam elements and record the axis parameter equations to generate a marked mesh with spatial marking.

[0089] Specifically, the system calls a finite element mesh with topological association, and simultaneously calls the curvature tensor field and the guiding field to extract the curvature value and gradient modulus value corresponding to each element vertex in the finite element mesh. Based on the mechanical analysis requirements of the building structure, the system sets a first gradient threshold, which is used to distinguish between high-curvature and low-curvature regions. The system performs gradient threshold judgment processing on each element, calculates the average value of the gradient modulus value at the element vertex, and compares this average value with the first gradient threshold. If the average value is greater than or equal to the first gradient threshold, the region where the element is located is determined to be a high-curvature region, and the element is marked as a shell element. Simultaneously, the centroid coordinates of the element are calculated from the element vertex coordinates and recorded. If the average value is less than the first gradient threshold, the region where the element is located is determined to be a low-curvature region, and the element is marked as a beam element. Furthermore, based on the element's orientation and parameter coordinates, the axis parameter equation of the element is derived and recorded. The axis parameter equation includes the direction vector and position parameters of the axis.

[0090] The system associates the type label of each element, the centroid coordinates of shell elements in high-curvature regions, and the axial parametric equations of beam elements in low-curvature regions with the element number, and combines them according to the element arrangement order of the finite element mesh to form a labeled mesh with spatial labels. The system checks the label consistency of the labeled mesh by comparing the type labels of adjacent elements to determine whether there are any label abrupt changes. If so, the gradient threshold judgment process is re-verified, the abnormal labels are corrected, the rationality of the labeled mesh is ensured, and the labeled mesh data is stored after correction.

[0091] In one embodiment, S4 of the BIM-based building structure modeling method provided by the present invention specifically includes the following steps:

[0092] S41: Perform principal curvature direction matching processing on the centroid coordinates of the marked mesh shell elements, reconstruct the material constitutive relation through the local coordinate system rotation matrix, and generate the curvature-driven stiffness matrix.

[0093] Specifically, the system calls the marked mesh data, extracts the coordinates of all centroids marked as shell elements, and simultaneously calls the orthogonal principal curvature direction field. Through parameter coordinate matching, it obtains the unit vectors of the maximum and minimum principal curvature directions at the centroid of each shell element. Based on these two orthogonal direction vectors and combined with the coordinate axis directions of the global coordinate system, the system constructs a local coordinate system rotation matrix. The elements of the rotation matrix are determined by the cosine of the angle between the direction vector and the global coordinate axis, used to realize the transformation between the global coordinate system and the local coordinate system of the shell element. The system reads the material property parameters of the building structure, including basic parameters such as elastic modulus and Poisson's ratio. Based on the material constitutive relation formula in the local coordinate system, the system reconstructs the constitutive parameters in the global coordinate system through the rotation matrix. The reconstructed constitutive relation reflects the influence of the principal curvature directions on the mechanical properties of the material. The system uses the mechanical theory formulas of the shell element, combined with the reconstructed material constitutive relation and the thickness parameters of the shell element, to calculate the in-plane stiffness, bending stiffness, and coupling stiffness components of the shell element. These components are then integrated according to the stiffness matrix assembly rules to generate a curvature-driven stiffness matrix. After generation, the system checks the symmetry and positive definiteness of the stiffness matrix. If the mechanical matrix characteristics are not met, the local coordinate system rotation matrix or constitutive relation parameters are readjusted until the stiffness matrix meets the requirements.

[0094] S42: The internal force flow function is sampled for the beam element axis parameter equation of the marked mesh, and the nonlinear change of cross-sectional area is calculated based on the stress attenuation model to generate the variable cross-sectional property distribution function.

[0095] Specifically, the system calls the marked mesh data and extracts the axis parametric equations of the beam elements. These equations contain the spatial trajectory and parameterized variables of the beam elements. Based on these equations, the system determines the sampling interval and uniformly selects multiple sampling points along the axis trajectory. The system then calls the internal force flow function field and obtains the internal force flow function value for each sampling point by matching the parameter coordinates of the sampling points with the parameter coordinates of the internal force flow function field. Finally, the system imports a preset stress attenuation model, which correlates the internal force flow intensity with the cross-sectional area. The internal force flow function values ​​of the sampling points are substituted into the model to calculate the cross-sectional area value at each sampling point.

[0096] Preferably, the system can use a curve fitting algorithm to fit the cross-sectional area value of each sampling point with the corresponding axis parameter variable, generating a nonlinear distribution function of the cross-sectional area varying with the axis parameter. The fitting process must ensure that the function curve passes through all sampling points and that the first derivative is continuous to avoid abrupt changes in the cross-section. The system verifies the rationality of the distribution function by calculating the cross-sectional area at the axis endpoints to determine if it meets the minimum cross-sectional requirements of the structural design. If not, the parameters of the stress attenuation model are adjusted and recalculated. After successful verification, the variable cross-sectional property distribution function and the corresponding beam element number are stored.

[0097] S43: The stiffness matrix and variable cross-section property distribution function are processed by finite element assembly. The structural stiffness relationship is integrated by nodal degree of freedom association and boundary condition constraints to generate a structural analysis model to guide structural strength analysis.

[0098] Specifically, the system calls the stiffness matrix of the shell element and the variable cross-section property distribution function of the beam element, while extracting the node coordinates and element-node relationships in the marked mesh. The system first assembles finite element units, embedding the stiffness matrix of each shell element into the corresponding position of the overall stiffness matrix according to the element-node relationship. For beam elements, it calculates the stiffness matrix of each segment based on the variable cross-section property distribution function, and then completes the embedding and assembly. The system handles the junction region between shell and beam elements, using node degree-of-freedom association constraints to maintain coordination of the displacement degrees of freedom at the junction nodes, ensuring continuous transfer of mechanical loads between different elements.

[0099] Preferably, the system imports boundary condition data of the building structure, including support type, constraint degrees of freedom, etc., and converts the boundary conditions into corresponding stiffness matrix correction terms to constrain the overall stiffness matrix. The system integrates element information, node information, material properties, stiffness matrix, and boundary conditions to form a complete structural stiffness relationship. During the integration process, the consistency of the correlation between various data needs to be verified, such as the correspondence between element numbers and stiffness matrices, and the matching of node coordinates and constraint conditions. Finally, the system formats and outputs all the integrated data according to the common data format of finite element analysis software, generating a structural analysis model file. The file contains element, node, material, and constraint information that the software can recognize, for subsequent structural strength analysis.

[0100] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0101] Based on the same inventive concept, this application also provides a BIM-based building structure modeling device for implementing the BIM-based building structure modeling method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more BIM-based building structure modeling device embodiments provided below can be found in the limitations of the BIM-based building structure modeling method described above, and will not be repeated here.

[0102] Preferably, such as Figure 2 As shown, the present invention provides a BIM-based building structure modeling device 600, which is configured with the following modules:

[0103] The curvature tensor calculation module 610 is used to process the NURBS surface exported by the building information modeling system, calculate the curvature properties of each point on the NURBS surface through second-order partial derivatives, and generate a curvature tensor field with parameter coordinates.

[0104] The guide field generation module 620 is used to process the curvature tensor field, extract the principal curvature direction field and integrate along the direction of maximum curvature change to construct the internal force flow function, and generate the guide field that controls the mesh density.

[0105] The element type division module 630 is used to process the gradient magnitude based on the guide field, divide shell elements and beam elements according to the preset first gradient threshold, and generate a marked mesh with center coordinates and axis parameters.

[0106] The structural model building module 640 is used to calculate the curvature-stiffness matrix of shell elements in the marked mesh, calculate the variable cross section driven by internal force flow of beam elements, and generate a structural analysis model.

[0107] The guide field correction module 650 is used to perform finite element analysis on the structural analysis model to obtain the displacement field. When the displacement error exceeds the preset second gradient threshold, the gradient distribution of the guide field is weighted and corrected to update the spatial distribution parameters of the guide field.

[0108] Preferably, the curvature tensor calculation module 610 provided in this application is configured with the following units:

[0109] The control point topology analysis unit is used to perform control point topology analysis on the NURBS surface data input by the building information modeling software, extract the control point coordinate matrix and parameter domain boundary, and generate a discretized parameter mesh.

[0110] The normal vector field generation unit is used to calculate the first-order partial derivative of the surface on the discretized parametric mesh, solve the unit normal vector based on the orthogonality of the tangent plane, and generate the global normal vector field.

[0111] The curvature tensor fusion unit is used to fuse the second-order partial derivatives of the normal vector field on the surface, and generate a curvature tensor field with parameterized coordinates by combining the curvature component calculation formula.

[0112] Preferably, the guide field generation module 620 provided in this application is configured with the following units:

[0113] The principal curvature direction extraction unit is used to perform eigenvalue decomposition on the curvature tensor field, separate the unit vectors of the maximum curvature direction and the minimum curvature direction, and generate an orthogonal principal curvature direction field.

[0114] The internal force flow function generation unit is used to perform geodesic integration on the orthogonal principal curvature direction field along the curvature gradient direction. It generates the internal force flow function field by accumulating the coupling effect between the curvature direction and the path tangent through vector superposition.

[0115] The guide field parameter generation unit is used to perform spatial gradient field calculation on the internal force flow function field. It generates principal direction weight coefficients by combining the eigenvalue ratios of the orthogonal principal curvature direction field, and generates a guide field that controls the grid density distribution.

[0116] Preferably, the unit type division module 630 provided in this application is configured with the following units:

[0117] The gradient modulus conversion unit is used to extract the gradient modulus of the guiding field, convert the curvature change intensity through an exponential decay function, and generate an adaptive mesh size function.

[0118] Constrained triangulation mesh generation elements are used to perform constrained Delaunay triangulation on the parametric coordinate domain of the curvature tensor field. The element side length is dynamically adjusted according to the mesh size function to generate a finite element mesh with topological association.

[0119] The element type labeling element is used to perform gradient threshold judgment processing on the finite element mesh. Based on the preset first gradient threshold, the high curvature region element is labeled as a shell element and the centroid coordinate is recorded, and the low curvature region element is labeled as a beam element and the axis parameter equation is recorded, generating a labeled mesh with spatial labels.

[0120] Preferably, the structural model building module 640 provided in this application is configured with the following units:

[0121] The shell element stiffness calculation unit is used to perform principal curvature direction matching processing on the centroid coordinates of the marked mesh shell elements, and reconstruct the material constitutive relation through the local coordinate system rotation matrix to generate the curvature-driven stiffness matrix.

[0122] The beam element variable cross section calculation unit is used to sample the internal force flow function of the beam element axis parameter equation of the marked mesh, calculate the nonlinear change of cross section area based on the stress attenuation model, and generate the variable cross section property distribution function.

[0123] Finite element model assembly unit is used to assemble stiffness matrix and variable cross section property distribution function into finite element units. By associating nodal degrees of freedom and boundary condition constraints, it integrates structural stiffness relationships to generate a structural analysis model to guide structural strength analysis.

[0124] In one embodiment, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described BIM-based building structure modeling method.

[0125] In one embodiment, this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described BIM-based building structure modeling method.

[0126] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0127] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The components described as separate parts may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0128] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in this application, and these should all be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A BIM-based building structure modeling method, characterized in that, Includes the following steps: S1: Process the NURBS surface exported from the building information modeling system, calculate the curvature properties of each point on the NURBS surface through second-order partial derivatives, and generate a curvature tensor field with parameter coordinates. S2: Process the curvature tensor field, extract the principal curvature direction field and integrate along the direction of maximum curvature change to construct the internal force flow function, and generate the guiding field that controls the mesh density; S3: Based on the gradient magnitude of the guide field, the shell element and beam element are divided according to the preset first gradient threshold, and a marked mesh with center coordinates and axis parameters is generated. S4: Perform curvature-stiffness matrix calculation on the shell elements in the marked mesh, perform variable cross-section calculation driven by internal force flow on the beam elements, and generate a structural analysis model; S5: Perform finite element analysis on the structural analysis model to obtain the displacement field. When the displacement error exceeds the preset second gradient threshold, perform weighted correction processing on the gradient distribution of the guide field and update the spatial distribution parameters of the guide field.

2. The method according to claim 1, characterized in that, S1 includes: S11: Perform control point topology analysis on the NURBS surface data input from the building information modeling software, extract the control point coordinate matrix and parameter domain boundary, and generate a discretized parameter mesh; S12: Calculate the first-order partial derivative of the surface on the discretized parameter mesh, solve the unit normal vector based on the orthogonality of the tangent plane, and generate a global normal vector field; S13: Perform surface second-order partial derivative fusion on the normal vector field, and generate a curvature tensor field with parameter coordinates by combining the curvature component calculation formula.

3. The method according to claim 1, characterized in that, S2 includes: S21: Perform eigenvalue decomposition on the curvature tensor field, separate the unit vectors of the maximum curvature direction and the minimum curvature direction, and generate an orthogonal principal curvature direction field; S22: The orthogonal principal curvature direction field is integrated along the curvature change gradient direction using geodesic integration. The coupling effect between the curvature direction and the path tangent is accumulated by vector superposition to generate an internal force flow function field. S23: Perform spatial gradient field calculation on the internal force flow function field, and generate principal direction weight coefficients by combining the eigenvalue ratios of the orthogonal principal curvature direction field, thereby generating a guiding field that controls the grid density distribution.

4. The method according to claim 1, characterized in that, S3 includes: S31: Extract the gradient modulus of the guiding field, convert the curvature change intensity through an exponential decay function, and generate an adaptive mesh size function; S32: Perform constrained Delaunay triangulation on the parametric coordinate domain of the curvature tensor field, dynamically adjust the element side length according to the mesh size function, and generate a finite element mesh with topological association. S33: Perform gradient threshold judgment processing on the finite element mesh, mark the high curvature region elements as shell elements and record the centroid coordinates based on the preset first gradient threshold, mark the low curvature region elements as beam elements and record the axis parameter equations, and generate a marked mesh with spatial marking.

5. The method according to claim 1, characterized in that, S4 includes: S41: Perform principal curvature direction matching processing on the centroid coordinates of the shell elements of the marked mesh, reconstruct the material constitutive relationship through the local coordinate system rotation matrix, and generate a curvature-driven stiffness matrix. S42: Perform internal force flow function sampling processing on the beam element axis parameter equation of the marked mesh, calculate the nonlinear change of cross-sectional area based on the stress attenuation model, and generate a variable cross-sectional property distribution function; S43: Perform finite element assembly processing on the stiffness matrix and the variable cross-section property distribution function, integrate the structural stiffness relationship through nodal degree of freedom association and boundary condition constraints, and generate a structural analysis model to guide structural strength analysis.

6. A BIM-based building structure modeling device, characterized in that, The device includes: The curvature tensor calculation module is used to process the NURBS surface exported from the building information modeling system. It calculates the curvature properties of each point on the NURBS surface through second-order partial derivatives and generates a curvature tensor field with parameterized coordinates. The guide field generation module is used to process the curvature tensor field, extract the principal curvature direction field and integrate along the direction of maximum curvature change to construct the internal force flow function, and generate a guide field that controls the mesh density. The unit type division module is used to process the gradient magnitude of the guide field, divide shell units and beam units according to a preset first gradient threshold, and generate a marked mesh with center coordinates and axis parameters. The structural model building module is used to calculate the curvature-stiffness matrix of shell elements in the marked mesh, calculate the variable cross section driven by internal force flow for beam elements, and generate a structural analysis model. The guide field correction module is used to perform finite element analysis on the structural analysis model to obtain the displacement field. When the displacement error exceeds the preset second gradient threshold, the gradient distribution of the guide field is weighted and corrected to update the spatial distribution parameters of the guide field.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

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