Multidisciplinary Coupling Surface Grid Point Communication Data Encoding Method, Decoding Method, Device and Equipment

Abstract

The present application discloses a multi-disciplinary coupled surface grid point communication data encoding method, a decoding method, a device and equipment, which relate to the field of multi-disciplinary coupled numerical simulation, including: encoding various types of coupled data on grid nodes on multiple coupled interfaces into a one-dimensional real array, so as to complete all coupled data communication with only one message passing interface call, reducing the number of parallel communication calls and improving the efficiency of multi-disciplinary coupled simulation.

Description

Technical Field

[0001] The present invention relates to the field of multidisciplinary coupled numerical simulation, and particularly to a method and device for encoding and decoding communication data of multidisciplinary coupled surface grid points, as well as equipment. Background Art

[0002] Currently, multidisciplinary coupled simulation is mainly implemented through two approaches: one is to perform multidisciplinary coupled solution in a unified method framework, that is, different disciplines adopt the same grid discretization and the same calculation method; the other is to adopt a separated solution strategy, that is, different disciplines are solved independently, and physical information and data are transmitted between different disciplines through an interface. The first method has the advantages of high accuracy and good stability, but due to the limitations of the method itself, it is difficult to adapt to complex application scenarios, and the design and development difficulty is relatively large. It is rarely used in the industrial design field and is mainly used for academic theoretical research. Although the second method is slightly lower than the first method in terms of accuracy and robustness, it can use relatively mature single-discipline solvers, thereby greatly reducing the development difficulty of the solver and being applicable to extremely complex application scenarios. It is a widely adopted multidisciplinary coupled simulation method in the current industrial field.

[0003] In the separated coupling solution strategy, different discipline solvers run independently, and iterative update of different physical field data is achieved through the exchange of interface information. When the simulation problem is relatively complex, the discipline solution adopts a multi-process parallel operation mode, and parallel communication and transmission of coupling interface data need to be carried out between different processes. Currently, the message passing interface is still the main way for parallel data communication in multidisciplinary coupled analysis, but the message passing interface method can only send and receive single-type data each time. When there are many types of coupled data, the message passing interface needs to be called multiple times, resulting in the solver needing to carry out multiple communication interface preparation operations, leading to an increase in the overall communication time. In the case of a large number of computing processes, the communication time cost will account for a large proportion of the overall computing time, thereby reducing the efficiency of multidisciplinary coupled simulation analysis. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method and device for encoding and decoding communication data of multidisciplinary coupled surface grid points, as well as equipment, which can perform one communication for multiple types of coupled data, reduce the number of calls to the transfer interface, and improve the efficiency of multidisciplinary coupled analysis. The specific solutions are as follows:

[0005] In a first aspect, the present application discloses a method for encoding communication data of multidisciplinary coupled surface grid points, including:

[0006] Determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in the multidisciplinary coupled analysis problem;

[0007] Form corresponding disciplinary analysis and calculation grids according to the multidisciplinary coupling analysis problem, extract coupling interface grids from the disciplinary analysis and calculation grids, and calculate the number of coupling interfaces and the number of grid nodes of the coupling interfaces;

[0008] Perform numerical calculations on the physical quantities to be communicated among the grid nodes of the coupling interfaces to obtain the values of the physical quantities to be communicated for each grid node;

[0009] Convert the current integer data form of the number of coupling interfaces, the number of grid nodes of a single coupling interface, and the physical field dimension into the real data form of the target number of coupling interfaces, the target number of grid nodes, and the target physical field dimension, and determine the encoding order of the physical quantities;

[0010] Perform encoding processing on the target physical field dimension and the target number of coupling interfaces to obtain a first real array, perform encoding processing on the target number of grid nodes, and fill the encoded information into the first real array to obtain a second real array;

[0011] Perform cyclic encoding on the physical quantities to be communicated according to the encoding order of the physical quantities, and fill the encoding results into the second real array to obtain a target real array.

[0012] Optionally, before determining the physical quantity data type, physical field dimension, and physical quantities to be communicated of the coupling data to be communicated in the multidisciplinary coupling analysis problem, it further includes:

[0013] Generate an example folder for the multidisciplinary coupling analysis problem; wherein, the example folder is used to store the folders of each disciplinary solver and the corresponding coupling framework configuration files;

[0014] When obtaining the multidisciplinary coupling analysis problem, call the example folder to perform simulation processing on the multidisciplinary coupling analysis problem to obtain the coupling interfaces participating in the coupling analysis.

[0015] Optionally, determining the physical quantity data type, physical field dimension, and physical quantities to be communicated of the coupling data to be communicated in the multidisciplinary coupling analysis problem includes:

[0016] According to the multidisciplinary coupling analysis problem and the action mechanism of iterative exchange between different disciplines, determine the physical quantity data type, physical field dimension, and physical quantities to be communicated of the coupling data to be communicated participating in the coupling communication in the multidisciplinary coupling analysis problem.

[0017] Optionally, calculating the number of grid nodes of the coupling interface includes:

[0018] If there are multiple grid surfaces in the coupling interface, count the number of grid points on each grid surface respectively, and accumulate and calculate the number of grid points on all the grid surfaces to obtain the number of grid nodes of the coupling interface.

[0019] Optionally, the numerical calculation of the physical quantities to be communicated in the grid nodes of the coupling interface to obtain the values of the physical quantities to be communicated at each grid node includes:

[0020] Calculating the multi-disciplinary coupling analysis problem according to each discipline solver to obtain physical field distribution data;

[0021] Calculating the values of the physical quantities to be communicated at the grid nodes of the coupling interface through a preset data processing technology for the physical field distribution data and the grid data of the coupling interface.

[0022] Optionally, the target real array is a one-dimensional coupling data array.

[0023] In a second aspect, the present application discloses a method for decoding multi-disciplinary coupling surface grid point communication data, including:

[0024] Obtaining a target real array encoded by the multi-disciplinary coupling surface grid point communication data encoding method;

[0025] Extracting the target physical field dimension, the target number of coupling interfaces, and the target number of grid nodes from the target real array, and performing data format conversion on the target physical field dimension, the target number of coupling interfaces, and the target number of grid nodes to obtain the physical field dimension, the number of coupling interfaces, and the number of grid nodes in integer data format;

[0026] Obtaining corresponding communication data from the encoded physical quantities according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces, and the number of grid nodes.

[0027] Optionally, after obtaining the corresponding communication data from the encoded physical quantities according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces, and the number of grid nodes, it further includes:

[0028] Taking the currently decoded communication data of any one discipline solver as control point information, and constructing a corresponding target interpolation function by using the control point information and the initial interpolation function;

[0029] Performing interpolation calculation on other communication data except the currently decoded communication data by using the target interpolation function to obtain interpolated communication data.

[0030] In a third aspect, the present application discloses a multi-disciplinary coupling surface grid point communication data encoding device, including:

[0031] An information determination module, configured to determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated in a multidisciplinary coupling analysis problem;

[0032] A data calculation module, configured to form a corresponding disciplinary analysis calculation grid according to the multidisciplinary coupling analysis problem, extract a coupling interface grid from the disciplinary analysis calculation grid, and calculate the number of coupling interfaces and the number of grid nodes of the coupling interface;

[0033] A numerical calculation module, configured to perform numerical calculations on the physical quantities to be communicated in the grid nodes of the coupling interface to obtain the values of the physical quantities to be communicated of each grid node;

[0034] A format conversion module, configured to convert the number of coupling interfaces in the current integer data format, the number of grid nodes of a single coupling interface, and the physical field dimension into a target number of coupling interfaces, a target number of grid nodes, and a target physical field dimension in the real data format respectively, and determine the encoding order of physical quantities;

[0035] A first encoding module, configured to perform encoding processing on the target physical field dimension and the target number of coupling interfaces to obtain a first real array, perform encoding processing on the target number of grid nodes, and fill the encoded information into the first real array to obtain a second real array;

[0036] A second encoding module, configured to perform cyclic encoding on the physical quantities to be communicated according to the encoding order of physical quantities, and fill the encoding result into the second real array to obtain a target real array.

[0037] In a fourth aspect, the present application discloses an electronic device, including:

[0038] A memory, configured to store a computer program;

[0039] A processor, configured to execute the computer program to implement the steps of the method disclosed above.

[0040] It can be seen that the present application discloses a multi-disciplinary coupled surface grid point communication data encoding method, including: determining the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in a multi-disciplinary coupled analysis problem; forming a corresponding disciplinary analysis calculation grid according to the multi-disciplinary coupled analysis problem, so as to extract a coupled interface grid from the disciplinary analysis calculation grid, and calculating the number of coupled interfaces and the number of grid nodes of the coupled interface; performing numerical calculation on the physical quantity to be communicated in the grid nodes of the coupled interface to obtain the values of the physical quantity to be communicated of each grid node; converting the number of coupled interfaces in the current integer data form, the number of grid nodes of a single coupled interface, and the physical field dimension into the target number of coupled interfaces, the target number of grid nodes, and the target physical field dimension in the real data form respectively, and determining the physical quantity encoding order; performing encoding processing on the target physical field dimension and the target number of coupled interfaces to obtain a first real array, performing encoding processing on the target number of grid nodes, and filling the encoded information into the first real array to obtain a second real array; performing cyclic encoding on the physical quantity to be communicated according to the physical quantity encoding order, and filling the encoding result into the second real array to obtain a target real array. Thus, by uniformly converting key information such as the number of coupled interfaces in the integer data form, the number of grid nodes of a single coupled interface, and the physical field dimension into the real data form, the data types are more consistent in the subsequent encoding process, avoiding additional processing steps and potential errors that may be caused by inconsistent data types, thereby improving the overall efficiency of data processing. Encoding according to the physical quantity encoding order reduces chaos and uncertainty in the encoding process, improves the accuracy and speed of encoding, and further enhances the data processing efficiency of the entire multi-disciplinary coupled analysis. After a series of encoding processes, a target real array is obtained. This way of integrating various types of physical quantities to be communicated into a unified format (target real array) is conducive to data communication between different disciplinary solvers in multi-disciplinary coupled analysis. It enables all relevant coupled data to be carried in a single data transfer, avoiding communication overhead and time delay that may be caused by multiple transfers of different types of data, thereby enhancing the effect of data communication and improving the overall operation efficiency of multi-disciplinary coupled analysis. Brief Description of the Drawings

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0042] Figure 1Flowchart of a multi-disciplinary coupled surface grid point communication data encoding method disclosed in this application;

[0043] Figure 2 Format diagram of a fluid solver encoding disclosed in this application;

[0044] Figure 3 Format diagram of a structural solver encoding disclosed in this application;

[0045] Figure 4 Flowchart of a multi-disciplinary coupled surface grid point communication data decoding method disclosed in this application;

[0046] Figure 5 Flowchart of wing flutter analysis based on encoding and decoding methods disclosed in this application;

[0047] Figure 6 Schematic diagram of the structure of a multi-disciplinary coupled surface grid point communication data encoding device disclosed in this application;

[0048] Figure 7 Structure diagram of an electronic device disclosed in this application. Detailed implementation manners

[0049] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0050] With the rapid improvement of computer hardware capabilities and the continuous development of numerical calculation methods, CAE (Computer - Aided Engineering) industrial software based on numerical calculation has gradually become an important driving force for the design mode transformation in the equipment manufacturing fields represented by aviation and aerospace, playing an important role in product design, performance evaluation, and use and maintenance. Among them, the development and maturity of single-disciplinary simulation software can replace physical simulation or physical experiments in many fields, providing high-precision prediction data for product design. However, with the continuous improvement of the precision and requirements of modern product design, many cross-disciplinary coupling problems have emerged, which have become the key problems restricting product performance. The improvement of the quality and performance of modern products urgently requires the support of high-fidelity multi-disciplinary coupled simulation analysis tools.

[0051] At present, multi-disciplinary coupled simulation is mainly implemented through two approaches: one is to perform multi-disciplinary coupled solution within a unified method framework, that is, the same mesh discretization and the same calculation method are used for different disciplines; the other is to adopt a separated solution strategy, that is, different disciplines are solved independently, and physical information and data are transmitted between different disciplines through interfaces. The first method has the advantages of high accuracy and good stability. However, due to the limitations of the method itself, it is difficult to adapt to complex application scenarios, and the design and development are difficult. It is rarely used in the industrial design field and is mainly used for academic theoretical research. Although the second method is slightly lower than the first method in terms of accuracy and robustness, it can use relatively mature single-discipline solvers, thus greatly reducing the development difficulty of the solver and being applicable to extremely complex application scenarios. It is the widely adopted multi-disciplinary coupled simulation method in the current industrial field.

[0052] In the separated coupling solution strategy, different discipline solvers run independently, and the iterative update of data in different physical fields is realized through the exchange of interface information. When the simulation problem is relatively complex, the discipline solution adopts a multi-process parallel operation mode, and parallel communication and transmission of coupling interface data are required between different processes. Currently, the message passing interface is still the main way of parallel data communication in multi-disciplinary coupled analysis. However, the message passing interface method can only send and receive single-type data each time. When there are many types of coupled data, the message passing interface needs to be called multiple times, which requires the solver to carry out multiple communication interface preparation operations, resulting in an increase in the overall communication time. In the case of a large number of computing processes, the communication time cost will account for a large proportion of the overall computing time, thus reducing the efficiency of multi-disciplinary coupled simulation analysis.

[0053] Therefore, the present invention provides a multi-disciplinary coupled surface grid point communication data encoding and decoding scheme, which can perform one communication for multi-type coupled data, reduce the number of calls to the transfer interface, and improve the efficiency of multi-disciplinary coupled analysis.

[0054] Refer to Figure 1 As shown, an embodiment of the present invention discloses a multi-disciplinary coupled surface grid point communication data encoding method, including:

[0055] Step S11: Determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in the multi-disciplinary coupled analysis problem.

[0056] In this embodiment, before determining the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated in the multi-disciplinary coupling analysis problem, it further includes: generating an example folder for the multi-disciplinary coupling analysis problem; wherein, the example folder is used to store the folders of each disciplinary solver and the corresponding coupling framework configuration files; when obtaining the multi-disciplinary coupling analysis problem, the example folder is called to perform simulation processing on the multi-disciplinary coupling analysis problem to obtain the coupling interface participating in the coupling analysis. It can be understood that a multi-disciplinary coupling analysis environment is pre-built. The present invention adopts a TRIP fluid solver, a modal structure solver, and a coupling interpolation algorithm. First, for the wing aerodynamic coupling analysis problem, an example folder for wing aerodynamic / structural coupling analysis is generated. The example folder stores folders such as the fluid solver, the structure solver, and the coupling data interpolation module, and the configuration files of the coupling framework. The solver folder stores the grid file and the configuration file of the wing respectively, and the coupling interpolation folder saves the interpolation parameter setting file. For the fluid solver setting, first use grid generation software to generate the grid of the external flow field of the wing, set the wing surface as the interface participating in the coupling analysis, and output the flow field grid in Plot3D format. In the fluid solver configuration file, set the flow field parameters (angle of attack, Mach number, Reynolds number, etc.), boundary conditions (far field, solid wall, coupling boundary, etc.), grid deformation method, and solution method (time / space discretization format, turbulence model, number of unsteady iteration steps, time step, etc.). For the structure solver setting, use structural pre-processing software, input the wing model and structural physical property parameters, use the modal analysis function, set the wing surface as the coupling interface, and export the first four natural frequencies and modal vibration mode coordinates of the wing after the calculation. In the coupling interpolation algorithm configuration file, set parameters such as the interpolation method as IPS and the interpolation radius. In the coupling framework configuration file, design parameters such as the coupling analysis type, time step, maximum number of iterations, total number of parallel cores, names of all solvers participating in the coupling analysis, number of cores, and configuration file address.

[0057] In this embodiment, according to the multi-disciplinary coupling analysis problem and the interaction mechanism of iterative exchange between different disciplines, determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated in the multi-disciplinary coupling analysis problem. It can be understood that according to the multi-disciplinary coupling analysis problem and the interaction mechanism of iterative exchange between different disciplines, determine all data types participating in the coupling communication in the multi-disciplinary coupling analysis. For example, in the fluid-structure coupling analysis, the fluid needs to transfer the force on the calculated coupling interface to the solid to facilitate the solid to carry out static or dynamic analysis, and the solid needs to transfer the displacement after deformation to the fluid to facilitate the fluid to update the shape and calculate the force in the new state. Therefore, in the fluid-structure coupling analysis, the physical field dimension , the physical quantity data type includes: grid node coordinates , nodal aerodynamic force , node displacement , and based on the number of coupled interface mesh surfaces , the number of coupling interface mesh nodes The physical quantity to be communicated is determined.

[0058] Specifically, in the wing aerodynamic coupling analysis problem, after the fluid solver completes the unsteady solution within a single coupling time step, the node aerodynamic interpolation on the coupling interface is passed to the structural solver for dynamic analysis; after the structural solver completes the solution of a single coupling time step, the displacement interpolation on the coupling interface is passed to the fluid solver for fluid mesh deformation. In the data transmission process, it is necessary to predetermine the physical quantity data types of the coupling data to be communicated between the fluid solver and the structural solver. Among them, the physical quantity types of the fluid solver participating in the coupling communication include: node coordinates and node aerodynamic forces; the physical quantity types of the structural solver participating in the coupling communication include: node coordinates and node displacements. Furthermore, since the dimensions of different physical fields determine the number of components of physical quantities, for example, in a three-dimensional physical field ( ), physical quantities such as node coordinates, node aerodynamic forces, and node displacements have three components (e.g. direction), that is, then the corresponding grid node coordinates of the physical quantity to be communicated are , node aerodynamic force , node displacement . In the two-dimensional physical field ( ), such as the plate coupling problem, since the thickness direction is much smaller than the other two directions, only the coordinates of the length and width directions are used to construct the transfer matrix, and the physical quantities only use the thickness direction, i.e., the plane normal, for coupling calculations. These physical quantities have only two components, i.e. Determining the physical field dimension ensures that these physical quantities can be correctly operated during data processing. Taking the value of the physical quantity to be communicated on the coupling interface mesh node as an example, the physical field dimension determines how to calculate the communicated physical quantity based on the physical field distribution data calculated by the subject solver. If In the pressure data processing obtained by fluid calculation, it is necessary to consider the distribution of pressure in three-dimensional space. By calculating the normal vector and area of ​​the grid unit, combined with the pressure data, the size and direction of the pressure load in three-dimensional space are obtained, and then it is reasonably distributed to the nodes. Therefore, the physical field dimensions of the computer involved in the coupled communication are further determined. In the fluid solver, the wing fluid grid belongs to the three-dimensional structured grid, so the physical field dimension data in the fluid solver is set. is 3. In the structural solver, although the finite element model of the wing structure is discretized by two-dimensional quadrilateral shell elements, the node coordinates of each node of the shell element and the components of the node aerodynamic force are still 3. When encoding and decoding, the coupled data of each node is operated according to the number of components. Therefore, the physical quantity dimension data is still set to be 3. And it is determined that the node aerodynamic force data and node displacement data of the current time step on each coupling interface are included in the coupled communication as the physical quantities to be communicated. It should be noted that currently only which physical quantities to be communicated are determined, and the specific values of the physical quantities to be communicated cannot be determined.

[0059] Step S12: Form corresponding disciplinary analysis calculation grids according to the multidisciplinary coupling analysis problem, extract the coupling interface grids from the disciplinary analysis calculation grids, and calculate the number of coupling interfaces and the number of grid nodes of the coupling interfaces.

[0060] In this embodiment, according to the definition or marking of the coupling interfaces in each disciplinary solver in the multidisciplinary coupling analysis, the coupling interface grids are extracted from the disciplinary analysis calculation grids, and the number of coupling interfaces is calculated. The number of grid nodes on the coupling interfaces is calculated. Among them, if there are multiple grid surfaces in the coupling interface, the number of grid points of each grid surface is respectively counted, and the number of grid points of all the grid surfaces is accumulated and calculated to obtain the number of grid nodes of the coupling interface. It can be understood that for the case where there are multiple grid surfaces in the coupling interface, the grid points of each grid surface are respectively counted. Then the number of grid nodes on the coupling interface is obtained by accumulation. .

[0061] Specifically, in the fluid solver, all grid blocks of the wing flow field grid are traversed, and the wing coupling interface data is calculated according to the coupling interface boundary conditions set during grid generation. is 1, and at the same time, the number of grid nodes on the coupling interface is calculated according to the boundary node numbers of the grid blocks where the coupling interface is located. The wing structure grid element type of the structural solver is a quadrilateral shell element. All nodes of the wing finite element model are selected as the points of the coupling interface, and the coupling interface number data is set. is equal to 1, and the number of nodes on the coupling interface is calculated. .

[0062] Step S13: Perform numerical calculations on the physical quantities to be communicated in the grid nodes of the coupling interface to obtain the values of the physical quantities to be communicated for each grid node.

[0063] In this embodiment, the multidisciplinary coupling analysis problem is calculated by each disciplinary solver to obtain physical field distribution data; the physical quantity values to be communicated at the grid nodes of the coupling interface are calculated by using a preset data processing technology for the physical field distribution data and the grid data of the coupling interface. It can be understood that, based on the physical field distribution data calculated by the disciplinary solver in the multidisciplinary coupling analysis, through data processing technologies such as piecewise integration and variable conversion, the physical quantity values to be communicated at the grid nodes of the coupling interface are calculated. For example, in the fluid-structure coupling analysis, the physical field data calculated by the fluid includes physical quantity information such as pressure, density, and velocity. Based on the grid data of the coupling interface, the normal vector and area of the grid element are calculated, and combined with the pressure data, the magnitude and direction of the pressure load on the grid element are obtained, and then the forces on the element are distributed to the grid nodes through linear weighting. It should be noted that in the multidisciplinary coupling analysis, the physical field distribution data calculated by different disciplinary solvers has various forms and complex structures. The physical field data calculated by the fluid contains various original physical quantity information such as pressure, density, and velocity. These original physical quantity data cannot be directly used for calculating the physical quantity values to be communicated at the grid nodes of the coupling interface. Because the physical quantities to be communicated at the grid nodes of the coupling interface (such as nodal force, nodal displacement, etc.) need to be determined according to the specific coupling problem and physical mechanism, the format and unit of the original data may not meet the requirements. The data interaction between different disciplines requires that the data has consistent physical meanings and appropriate forms at the grid nodes of the coupling interface for accurate information transmission and subsequent coupling calculations. Therefore, for physical quantities such as pressure calculated by the fluid, based on the grid data of the coupling interface, the normal vector and area of the grid element are calculated, and combined with the pressure data, the magnitude and direction of the pressure load on the grid element can be obtained through piecewise integration. This is because the pressure distribution on the element surface is not uniform, and through piecewise integration, the pressure effects on the element surface can be combined to obtain the equivalent pressure load on the entire element. For example, in a two-dimensional fluid-structure coupling interface grid element, the pressure may vary along the element boundary. By dividing the element into multiple small pieces (piecewise) and multiplying the pressure on each small piece by the corresponding area of the small piece (integration operation), the total pressure resultant force on the element can be obtained. Variable conversion is used to convert the units or representation forms of different physical quantities into forms suitable for coupling calculations. For example, in some cases, the unit of a physical quantity obtained from one discipline may be one in the International System of Units, while the input unit required by another discipline is another. Through variable conversion, the units of physical quantities can be converted. At the same time, variable conversion can also convert a physical quantity from one representation form to another. For example, converting a volume-based physical quantity to a mass-based physical quantity, etc., to meet the needs of calculating the physical quantities to be communicated at the grid nodes of the coupling interface.For example, in thermal-structural coupling, the heat transfer rate obtained from the thermal discipline may be in units of joules per second (J / s), while in the structural discipline, it may need to be converted to units of watts (W) (since 1 W = 1 J / s). Additionally, it may be necessary to convert it to a physical quantity related to the structural temperature change in order to accurately communicate and calculate physical quantities such as temperature-stress at the coupling interface grid nodes.

[0064] Specifically, the fluid solver uses an unsteady flow method to advance the flow field by one time step in physical time. It traverses all the element faces on the coupling interface, performs a numerical integration of the pressure over the area on the element face to obtain the aerodynamic resultant force on the element surface. Numerical processing methods such as the linear weighting method are used to distribute the aerodynamic force on the element face to each node on the element face, and the aerodynamic forces at the same node are accumulated to obtain the node aerodynamic force data for all the element faces. The structural solver uses the aerodynamic force of the nodes on the surface of the wing finite element model obtained after interpolation as the external load, and based on the modal method, solves the structural control dynamics equation to advance the structural motion by one time step to obtain the displacement data of the nodes on the surface of the wing finite element model.

[0065] Step S14: Convert the current integer data forms of the number of coupling interfaces, the number of grid nodes of a single coupling interface, and the physical field dimension into real data forms of the target number of coupling interfaces, the target number of grid nodes, and the target physical field dimension, and determine the physical quantity encoding order.

[0066] In this embodiment, in order to achieve a one-time transfer of communication data, all the communication data on the coupling interface grid nodes is encoded into a one-dimensional real array, which is mainly implemented through three processes. First, perform type conversion on some of the communication data. Convert the integer-form communication data in the communication data into real-form communication data by adding a real zero or forced type conversion. The text description string data is converted into an integer data sequence through mapping and then into real-form communication data. The real-form communication data remains unchanged and is directly assigned for use. Second, sort and encode the physical quantity values to be communicated on the coupling interface grid nodes, that is, determine the arrangement order of the physical quantity values to be communicated in the one-dimensional real array according to the physical quantity data type, which is also the physical quantity encoding order. Among them, the established physical quantity encoding order in the fluid solver is: node coordinates, node aerodynamic force; the established physical quantity encoding order in the structural solver is: node coordinates, node displacement.

[0067] Specifically, the fluid solver and the structural solver respectively encode the coupling data into a one-dimensional real array in their respective solvers. First, the fluid / structural solver takes the number of grid nodes on a single coupling interface Convert the integer data to real - type data by adding a real - type data zero or through type coercion. Data such as node coordinates, node aerodynamic forces, and node displacements are already real - type data, so no conversion is required. Then, since the number of coupled interfaces in the fluid or structural solver in this instance is equal to 1, there is no need to establish the encoding order of the coupled interfaces.

[0068] Step S15: Encode the target physical field dimension and the target number of coupled interfaces to obtain a first real - type array, encode the target number of grid nodes, and fill the encoded information into the first real - type array to obtain a second real - type array.

[0069] In this embodiment, first, the overall information data of the coupled - interface grid nodes after conversion (such as the converted physical field dimension , the number of grid faces of the coupled interface after conversion ) is encoded into a one - dimensional real - type array, that is, the first real - type array. Then, the number of target grid nodes on the coupled - interface grid faces is encoded one by one, and the encoded information is filled into the first real - type array to obtain a second real - type array.

[0070] Specifically, encoding all the coupled data into a one - dimensional array includes: the fluid / structural solver first encodes the overall information data such as the physical field dimension of the coupled - interface grid nodes , the number of coupled interfaces in the solver into a one - dimensional array, that is, the first real - type array; then encodes the wing coupled - interface data. First, the number of nodes on the wing surface is continuously encoded into the one - dimensional array to obtain a second real - type array.

[0071] As Figure 2 shows, a fluid - solver coupled - data encoding format diagram is disclosed. First is the physical field dimension , the number of coupled interfaces , the number of nodes , then the node coordinates ( ) to ( ), and finally the node aerodynamic forces ( ) to ( ). Similarly, the structural - solver coupled - data encoding format is as Figure 3 shows. First is the physical field dimension , the number of coupled interfaces , the number of nodes , then the node coordinates ( ) to ( ), and finally the node displacements ( ) to ( ).

[0072] Step S16: Perform cyclic encoding on the physical quantity to be communicated according to the physical quantity encoding order, and fill the encoding result into the second real array to obtain a target real array.

[0073] In this embodiment, the communication data (physical quantity to be communicated) is cyclically encoded one by one according to the physical quantity encoding order, and the communication data is cyclically encoded into the second real array through each coupling interface to obtain a target real array. Among them, the target real array is a one-dimensional coupled data array.

[0074] Specifically, after obtaining the second real array, the fluid solver encodes the node coordinates and node aerodynamic forces on the surface of the wing fluid mesh into the second real array respectively according to the corresponding physical quantity encoding order; the structure solver encodes the node coordinates and node displacements of the wing finite element model into the second real array, and after encoding through each coupling interface one by one according to the physical quantity encoding order, a target real array is obtained.

[0075] It can be seen that the present application discloses a multi-disciplinary coupled surface grid point communication data encoding method, including: determining the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in a multi-disciplinary coupled analysis problem; forming a corresponding disciplinary analysis calculation grid according to the multi-disciplinary coupled analysis problem, so as to extract a coupled interface grid from the disciplinary analysis calculation grid, and calculating the number of coupled interfaces and the number of grid nodes of the coupled interface; performing numerical calculations on the physical quantities to be communicated in the grid nodes of the coupled interface to obtain the values of the physical quantities to be communicated of each grid node; converting the number of coupled interfaces in the current integer data form, the number of grid nodes of a single coupled interface, and the physical field dimension into a target number of coupled interfaces, a target number of grid nodes, and a target physical field dimension in the real data form respectively, and determining the encoding order of physical quantities; performing encoding processing on the target physical field dimension and the target number of coupled interfaces to obtain a first real array, performing encoding processing on the target number of grid nodes, and filling the encoded information into the first real array to obtain a second real array; performing cyclic encoding on the physical quantities to be communicated according to the encoding order of physical quantities, and filling the encoding result into the second real array to obtain a target real array. Thus, by uniformly converting key information such as the number of coupled interfaces in the integer data form, the number of grid nodes of a single coupled interface, and the physical field dimension into the real data form, the data types are more consistent in the subsequent encoding processing, avoiding additional processing steps and potential errors that may be caused by inconsistent data types, thereby improving the overall efficiency of data processing. Encoding according to the encoding order of physical quantities reduces chaos and uncertainty in the encoding process, improves the accuracy and speed of encoding, and further enhances the data processing efficiency of the entire multi-disciplinary coupled analysis. After a series of encoding processes, a target real array is obtained. This way of integrating various types of physical quantities to be communicated into a unified format (target real array) is conducive to data communication between different disciplinary solvers in multi-disciplinary coupled analysis. It enables all relevant coupled data to be carried in a single data transfer, avoiding communication overhead and time delay that may be caused by multiple transfers of different types of data, thereby enhancing the effect of data communication and improving the overall operation efficiency of multi-disciplinary coupled analysis.

[0076] Referring to Figure 4 As shown, an embodiment of the present invention discloses a multi-disciplinary coupled surface grid point communication data decoding method, including:

[0077] Step S21: Obtain a target real array encoded by using the multi-disciplinary coupled surface grid point communication data encoding method described above.

[0078] In this embodiment, according to the communication mapping relationship between the disciplinary solvers established by multidisciplinary coupling analysis, the fluid solver transfers all the encoded coupling data to the structural solver at once, and the structural solver transfers all the encoded coupling data to the fluid solver at once. Therefore, each disciplinary solver can obtain the target real-type data sent by other disciplinary calculators through the communication mapping relationship. For example, in fluid-structure interaction analysis, after encoding the node coordinates and node aerodynamic forces, the fluid solver transfers the coupling data to the structural solver through the solver communication mapping relationship. The structural solver receives the coupling data and calculates the aerodynamic interpolation matrix.

[0079] Step S22: Extract the target physical field dimension, the number of target coupling interfaces, and the number of target grid nodes from the target real-type array, and perform data format conversion on the target physical field dimension, the number of target coupling interfaces, and the number of target grid nodes to obtain the physical field dimension, the number of coupling interfaces, and the number of grid nodes in integer data format.

[0080] Step S23: Obtain the corresponding communication data from the encoded physical quantities according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces, and the number of grid nodes.

[0081] In this embodiment, after receiving the one-dimensional real-type coupling data, the disciplinary solver performs a decoding operation on the coupling data to decode the one-dimensional coupling data into an array of individual physical quantities. The decoding operation can also be implemented through three processes. First, obtain the overall information data of the coupling interface grid nodes from the encoded data, such as the physical field dimension and the number of coupling interfaces . Then loop times, and each time obtain the communication data on the coupling interface grid points of one type from the encoded data. According to the arrangement order of the physical quantity data established during the encoding process, restore the communication data obtained each time to the physical quantity with the same physical meaning. Finally, when all the coupling data is decoded, convert the communication data to the original type, convert the integer data from real-type data to integer data by discarding the decimal part or forced type conversion. The text string of the real-type sequence is first converted from real-type data to integer data, and then according to the same mapping conversion, the character sequence is matched according to the integer data.

[0082] Specifically, the fluid / structure solver obtains the overall information data of the coupling interface grid nodes from the received one-dimensional coupling data array: the physical quantity dimension and the number of coupling interfaces ; then, obtain the physical quantity data on the wing surface from the coupling data. First, obtain the number of coupling interface nodes , and convert it from real - type data to integer - type data by truncating the fractional part or through type coercion; the fluid solver sequentially obtains data in the quantity of according to the physical quantity encoding order established during encoding: node coordinates, node aerodynamic force; the structural solver sequentially obtains data in the quantity of according to the physical quantity encoding order established during encoding: node coordinates, node displacement. And assign the obtained coupling data of each type to the solver parameters with the same physical meaning.

[0083] In this embodiment, after obtaining the corresponding communication data from the encoded physical quantities according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces, and the number of grid nodes, it further includes: using the currently decoded communication data of any one disciplinary solver as control point information, and constructing a corresponding target interpolation function by using the control point information and the initial interpolation function; performing interpolation calculation on the other communication data except the current communication data by using the target interpolation function to obtain the interpolated communication data. It can be understood that the fluid solver uses the fluid node coordinates included in itself and the structure node coordinates obtained by decoding as control points, and establishes a displacement interpolation matrix based on the Radial Basis Function (RBF) method . Taking the structure node displacement obtained by decoding as the known vector, performing a matrix - vector product with the displacement interpolation matrix to obtain the displacement of the wing surface nodes of the fluid grid. Similarly, the structural solver uses the fluid node coordinates obtained by decoding and the structure node coordinates included in itself as control points, and establishes an aerodynamic force interpolation matrix based on the principle of virtual work . Taking the aerodynamic force of the fluid nodes obtained by decoding as the known vector, performing a matrix - vector product with the aerodynamic force interpolation matrix to obtain the aerodynamic force of the wing surface nodes of the structural grid.

[0084] After obtaining the nodal displacements on the surface of the fluid mesh wing, mesh deformation methods such as RBF-TFI (RBF-Transfinite Interpolation) are used to calculate the coordinates of the internal mesh nodes. The steps of using the RBF-TFI method are as follows: First, taking the vertices of the mesh blocks on the coupling interface as control points and the vertices of the internal mesh blocks as interpolation base points, using the RBF method, the vertex displacements of the internal mesh blocks are calculated according to the displacements of the mesh blocks on the coupling interface. Secondly, taking the vertices of all mesh blocks as control points, the RBF is used to accurately solve the nodal displacements of the edges of each mesh block. Then, according to the nodal displacements of the mesh block edges, the two-dimensional TFI method based on arc length coordinates is used to quickly calculate the nodal displacements of each mesh block face. Finally, according to the nodal displacements of the mesh faces of the mesh blocks, the three-dimensional TFI method based on arc length coordinates is used to quickly calculate the displacement amounts of the internal points of the mesh blocks. After the displacement amounts of all nodes are calculated, they are added to the current node coordinates to obtain the new node coordinates, and the geometric information of the mesh (such as: node coordinates, centroid coordinates, volume, area, area vector) and the Jacobi transformation coefficient matrix are recalculated.

[0085] In this way, after decoding the communication data, the currently decoded communication data of any discipline solver can be used as control point information, and the corresponding target interpolation function can be constructed in combination with the initial interpolation function. For example, the fluid solver constructs a displacement interpolation matrix using the structural node coordinates obtained by decoding and its own fluid node coordinates, and the structural solver constructs an aerodynamic force interpolation matrix using the aerodynamic forces of the fluid nodes obtained by decoding and its own structural node coordinates. This way of constructing the interpolation function based on the decoded data enables different discipline solvers to effectively utilize each other's decoded data for further calculation and analysis, improving the data utilization efficiency. Using the constructed target interpolation function to perform interpolation calculations on the communication data other than the current communication data, the interpolated communication data can be obtained. For example, the nodal displacements on the surface of the fluid mesh wing are calculated through the displacement interpolation matrix, and the nodal aerodynamic forces on the surface of the structural mesh wing are calculated through the aerodynamic force interpolation matrix. Interpolation calculation can, based on the existing data, supplement and improve the missing or data that needs to be refined according to the relationship between the data, thereby improving the accuracy of the multi-disciplinary coupling analysis in simulating the actual physical process and more accurately reflecting the physical phenomena and system behaviors.

[0086] When the number of coupling iteration steps does not exceed the set maximum number of coupling iteration steps, the physical time is incremented by a coupling time step, and the number of coupling iteration steps is incremented by 1. Jump to execute the time advancement of the fluid and structural solvers until reaching the steps required by the maximum number of coupling analysis steps. Figure 5The wing flutter analysis process based on the encoding and decoding methods is shown, in which a loose coupling strategy format with first-order coupling accuracy is adopted. Specifically, in the initialization stage: after starting, first parse the coupling configuration file to generate a global communication domain. Initialize the fluid solver and the structural solver respectively. Generate the fluid / structural solver communication domain, and extract the coupling interface data in the two solvers respectively. In the flutter analysis stage: import the disciplinary solver module, and the global communication domain extracts the physical coordinates of all processes. The fluid solver and the structural solver perform time marching operations respectively. At the same time, the fluid solver establishes a communication domain process mapping relationship according to the physical coordinates and extracts the fluid coupling data on the wing surface. Determine whether the maximum selected iteration step is satisfied. If not, perform the following fluid coupling data encoding operations: 1. Conduct fluid coupling data communication and send the encoded fluid coupling data. 2. The structural solver receives the fluid coupling data and decodes the fluid coupling data. 3. Interpolate the nodal aerodynamic force. 4. The structural solver extracts the structural coupling data on the wing surface and encodes the structural coupling data. 5. Conduct structural coupling data communication and send the encoded structural coupling data. 6. The fluid solver receives the structural coupling data and decodes the structural coupling data. 7. Interpolate the nodal displacement. 8. The fluid solver performs fluid mesh deformation and recalculates the geometric data. In the iteration stage: accumulate a time step for the physical time. Increment the coupling iteration step number by 1, and then return to the step of determining whether the maximum selected iteration step is satisfied to continue the iteration until the maximum selected iteration step condition is met and the process ends.

[0087] Thus, by sequentially extracting and converting key information (such as the target physical field dimension, the number of target coupling interfaces, the number of target grid nodes, etc.) from the target real-type array into integer data form, the basic parameter settings of each physical quantity before encoding can be accurately restored, laying a foundation for the subsequent accurate decoding of physical quantity data. For example, clarifying the physical field dimension can determine the number of components of each physical quantity, and then accurately restore the original form of physical quantities such as nodal coordinates and nodal forces, ensuring that the data can restore its original physical meaning and format after decoding, guaranteeing the accuracy of the data. And during the decoding and restoration process, the encoded physical quantities of each physical quantity data type are decoded and restored according to the physical quantity encoding order established during the encoding process, so that the decoding operation can be carried out strictly in accordance with the rules during encoding, and the one-dimensional coupling data is accurately decoded into an array of individual physical quantities. This effectively avoids chaos and errors during the data restoration process, ensures that the communication data can be restored in the correct form and corresponding relationship, and improves the accuracy of data processing.

[0088] Refer to Figure 6 As shown, the present invention also correspondingly discloses a multi-disciplinary coupling surface grid point communication data encoding device, including:

[0089] An information determination module 11, configured to determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the data to be communicated and coupled in a multi-disciplinary coupling analysis problem;

[0090] A data calculation module 12, configured to form a corresponding disciplinary analysis calculation grid according to the multi-disciplinary coupling analysis problem, extract a coupling interface grid from the disciplinary analysis calculation grid, and calculate the number of coupling interfaces and the number of grid nodes of the coupling interfaces;

[0091] A numerical calculation module 13, configured to perform numerical calculations on the physical quantities to be communicated in the grid nodes of the coupling interfaces to obtain the values of the physical quantities to be communicated of each grid node;

[0092] A form conversion module 14, configured to convert the number of coupling interfaces, the number of grid nodes of a single coupling interface, and the physical field dimension in the current integer data form into a target number of coupling interfaces, a target number of grid nodes, and a target physical field dimension in the real data form respectively, and determine the physical quantity encoding order;

[0093] A first encoding module 15, configured to perform encoding processing on the target physical field dimension and the target number of coupling interfaces to obtain a first real array, perform encoding processing on the target number of grid nodes, and fill the encoded information into the first real array to obtain a second real array;

[0094] A second encoding module 16, configured to perform cyclic encoding on the physical quantities to be communicated according to the physical quantity encoding order, and fill the encoding result into the second real array to obtain a target real array.

[0095] It can be seen that this application discloses determining the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in a multi-disciplinary coupled analysis problem; forming corresponding disciplinary analysis calculation grids according to the multi-disciplinary coupled analysis problem to extract coupled interface grids from the disciplinary analysis calculation grids, and calculating the number of coupled interfaces and the number of grid nodes of the coupled interfaces; performing numerical calculations on the physical quantities to be communicated in the grid nodes of the coupled interfaces to obtain the values of the physical quantities to be communicated for each grid node; converting the number of current integer-form coupled interfaces, the number of grid nodes of a single coupled interface, and the physical field dimension into a target number of coupled interfaces, a target number of grid nodes, and a target physical field dimension in real number form respectively, and determining the encoding order of physical quantities; performing encoding processing on the target physical field dimension and the target number of coupled interfaces to obtain a first real number array, performing encoding processing on the target number of grid nodes, and filling the encoded information into the first real number array to obtain a second real number array; performing cyclic encoding on the physical quantities to be communicated according to the encoding order of physical quantities, and filling the encoding results into the second real number array to obtain a target real number array. Thus, by uniformly converting key information such as the number of integer-form coupled interfaces, the number of grid nodes of a single coupled interface, and the physical field dimension into real number form, the data types are more consistent in the subsequent encoding process, avoiding additional processing steps and potential errors that may be caused by inconsistent data types, thereby improving the overall efficiency of data processing. Encoding according to the encoding order of physical quantities reduces chaos and uncertainty in the encoding process, improves the accuracy and speed of encoding, and further enhances the data processing efficiency of the entire multi-disciplinary coupled analysis. After a series of encoding processes, a target real number array is obtained. This way of integrating various types of physical quantities to be communicated into a unified format (target real number array) is conducive to data communication between different disciplinary solvers in multi-disciplinary coupled analysis. It enables all relevant coupled data to be carried in one data transfer, avoiding communication overhead and time delay that may be brought by multiple transfers of different types of data, thereby enhancing the effect of data communication and improving the overall operation efficiency of multi-disciplinary coupled analysis.

[0096] Furthermore, the embodiment of this application also discloses an electronic device, Figure 7 It is a structural diagram of an electronic device 20 shown according to an exemplary embodiment, and the content in the figure should not be considered as any limitation to the scope of use of this application.

[0097] Figure 7Schematic diagram of the structure of an electronic device 20 provided by an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. Among them, the memory 22 is used to store a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0098] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows is any communication protocol applicable to the technical solution of the present application, and no specific limitation is imposed on it here; the input / output interface 25 is used to obtain external input data or output data to the outside, and its specific interface type can be selected according to specific application needs, and no specific limitation is made here.

[0099] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor used to process data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, and the AI processor is used to process computing operations related to machine learning.

[0100] In addition, as a carrier for resource storage, the memory 22 may be a read-only memory, a random access memory, a disk, or an optical disc, etc. The resources stored thereon may include an operating system 221, a computer program 222, etc., and the storage method may be temporary storage or permanent storage.

[0101] Among them, the operating system 221 is used to manage and control each hardware device on the electronic device 20 and the computer program 222, so as to implement the operation and processing of the massive data 223 in the memory 22 by the processor 21. It can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the method executed by the electronic device 20 disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program that can be used to complete other specific tasks. The data 223 may include not only the data transmitted by the external device received by the electronic device, but also the data collected by its own input / output interface 25, etc.

[0102] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the foregoing disclosed method is implemented. For the specific steps of this method, reference may be made to the corresponding content disclosed in the foregoing embodiments, and details will not be elaborated herein.

[0103] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts between the various embodiments, reference can be made to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and reference can be made to the description of the method part for related parts.

[0104] Those skilled in the art may further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application. The steps of the methods or algorithms described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of the two. The software modules can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disk, removable disk, CD-ROM (Compact Disc-Read Only Memory), or any other form of storage medium known in the technical field.

[0105] Finally, it should also be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0106] The above has introduced the solution provided by the present invention in detail. Specific examples are used herein to illustrate the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for encoding communication data of coupling surface grid points in wing aerodynamic / structural coupling simulation analysis, characterized in that: include: Determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated in the aircraft wing aerodynamic / structural coupling simulation analysis problem; According to the wing aerodynamic / structural coupling simulation analysis problem, a corresponding subject analysis calculation grid is formed to extract a coupling interface grid from the subject analysis calculation grid, and the number of coupling interfaces and the number of grid nodes of the coupling interfaces are calculated; wherein the coupling interface is the wing surface of the aircraft model; Performing numerical calculation on the physical quantity to be communicated in the grid nodes of the coupling interface to obtain the value of the physical quantity to be communicated of each of the grid nodes; Convert the number of coupling interfaces, the number of grid nodes of a single coupling interface, and the physical field dimension in current integer data forms into the target number of coupling interfaces, the target number of grid nodes, and the target physical field dimension in real data forms, respectively, and determine the physical quantity encoding order; The target physical field dimension and the target coupling interface quantity are encoded to obtain a first real array, and the target grid node quantity is encoded, and the encoded information is filled into the first real array to obtain a second real array; The physical quantity to be communicated is cyclically encoded according to the physical quantity encoding order, and the encoding result is filled into the second real type array to obtain a target real type array.

2. The method for encoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 1, characterized in that: Before determining the physical quantity data type, physical field dimension, and physical quantity of the coupled data to be communicated in the wing aerodynamic / structural coupling simulation analysis problem of the aircraft, the method further includes: Generate a calculation example folder for the wing aerodynamic / structural coupling simulation analysis problem; wherein the calculation example folder is used to store the folders of each subject solver and the corresponding coupling framework configuration file; When the wing aerodynamic / structural coupling simulation analysis problem is obtained, the example folder is called to simulate the wing aerodynamic / structural coupling simulation analysis problem to obtain a coupling interface involved in the coupling analysis.

3. The method for encoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 1, characterized in that: The physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupled data to be communicated in the wing aerodynamic / structural coupling simulation analysis problem of the aircraft include: According to the wing aerodynamic / structural coupling simulation analysis problem and the mechanism of iterative exchange between different disciplines, the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated participating in the coupling communication in the wing aerodynamic / structural coupling simulation analysis problem are determined.

4. The method for encoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 1, characterized in that: Calculate the number of mesh nodes for the coupling interface, including: If there are multiple mesh surfaces in the coupling interface, the number of mesh points of each mesh surface is counted respectively, and the number of mesh points of all the mesh surfaces is cumulatively calculated to obtain the number of mesh nodes of the coupling interface.

5. The method for encoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 1, characterized in that: The performing numerical calculation on the physical quantity to be communicated in the grid nodes of the coupling interface to obtain the value of the physical quantity to be communicated of each grid node includes: Calculating the wing aerodynamic / structural coupling simulation analysis problem according to the solvers of various disciplines to obtain physical field distribution data; The physical field distribution data and the mesh data of the coupling interface are processed by a preset data processing technology to calculate the physical quantity values ​​to be communicated on the mesh nodes of the coupling interface.

6. The method for encoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 1, characterized in that: The target real type array is a one-dimensional coupled data array.

7. A method for decoding communication data of coupling surface grid points in wing aerodynamic / structural coupling simulation analysis, characterized in that: include: Obtain a target real array encoded by the method for encoding data of grid point communication of coupling surface of wing aerodynamic / structural coupling simulation analysis according to any one of claims 1 to 6; Extracting target physical field dimensions, target coupling interface quantity, and target grid node quantity from the target real array, and converting the target physical field dimensions, target coupling interface quantity, and target grid node quantity into data format to obtain the physical field dimensions, coupling interface quantity, and grid node quantity in the form of integer data; Corresponding communication data is obtained from the encoded physical quantity according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces and the number of grid nodes.

8. The method for decoding communication data of coupling surface grid points of wing aerodynamic / structural coupling simulation analysis according to claim 7, characterized in that: After obtaining corresponding communication data from the encoded physical quantity according to the physical quantity encoding order, the physical field dimension, the number of coupling interfaces and the number of grid nodes, the method further includes: Using the current communication data decoded by any subject solver as control point information, and using the control point information and the initial interpolation function to construct a corresponding target interpolation function; The target interpolation function is used to perform interpolation calculation on other communication data except the current communication data to obtain interpolated communication data.

9. A wing aerodynamic / structural coupling simulation analysis coupling surface grid point communication data encoding device, characterized in that: include: An information determination module is used to determine the physical quantity data type, physical field dimension, and physical quantity to be communicated of the coupling data to be communicated in the wing aerodynamic / structural coupling simulation analysis problem of the aircraft; A data calculation module is used to form a corresponding subject analysis calculation grid according to the wing aerodynamic / structural coupling simulation analysis problem, to extract a coupling interface grid from the subject analysis calculation grid, and to calculate the number of coupling interfaces and the number of grid nodes of the coupling interfaces; wherein the coupling interface is the wing surface of the aircraft model; A numerical calculation module, used for performing numerical calculation on the physical quantity to be communicated in the grid nodes of the coupling interface to obtain the value of the physical quantity to be communicated of each grid node; A form conversion module, used to convert the number of coupling interfaces, the number of grid nodes of a single coupling interface, and the physical field dimension in the current integer data form into the target number of coupling interfaces, the target number of grid nodes, and the target physical field dimension in the real data form, and determine the physical quantity coding order; A first encoding module is used to encode the target physical field dimension and the target coupling interface quantity to obtain a first real array, and encode the target grid node quantity, and fill the encoded information into the first real array to obtain a second real array; The second encoding module is used to perform cyclic encoding on the physical quantity to be communicated according to the physical quantity encoding order, and fill the encoding result into the second real type array to obtain a target real type array.

10. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the method according to any one of claims 1 to 8.

Images