Interpolation data general processing method and device, and electronic equipment

Abstract

This invention relates to the field of fluid-structure coupling data processing technology, and discloses a general method, apparatus, and electronic device for interpolation data processing. The method includes parsing the output data of various CFD software and establishing an index relationship between physical quantity data and spatial nodes in different computational domains; parsing the finite element analysis model to obtain the spatial coordinates and node numbers of each finite element node; using the finite element nodes as interpolation target nodes, matching CFD interpolation source nodes according to the first correspondence between CFD nodes and finite element node spatial coordinates; combining the multi-time-step physical quantity data of the source nodes to obtain standardized time-series data; relying on the second correspondence between the two types of node spatial coordinates, mapping the standardized time-series data to finite element nodes through interpolation to generate a transient load field sequence; constructing a load matrix file based on this sequence and generating a finite element node number file according to the arrangement order of the interpolation target nodes, thereby realizing the generalized processing of interpolation data across multiple simulation software.

Description

Technical Field

[0001] This invention relates to the field of fluid and structure coupling data processing technology, specifically to a general interpolation data processing method, apparatus, and electronic device. Background Technology

[0002] In the traditional coupling process of computational fluid dynamics (CFD) and finite element analysis (FEA), it is usually necessary to interpolate and map the CFD pulsating pressure data to the nodes of the structural finite element model for vibration response analysis.

[0003] However, in the existing CFD-FEA joint analysis process, there are significant differences in the data organization structure, time series expression method and region division method of the output results of different CFD software; at the same time, different FEA software have different requirements for the format, indexing method and time step consistency of input load data. When CFD results come from different software and different computational regions, and their time series data are stored in different organization methods, the existing methods are difficult to achieve unified parsing, unified indexing and unified output, which seriously restricts the universality and engineering applicability of CFD results in structural vibration analysis. In addition, the following problems exist in actual engineering: (1) Existing fluid simulation contains a large number of simulation time steps, and the number of spatial nodes and the density of time series data dimensions are large under multi-computation domain conditions, resulting in a huge dataset of transient physical quantities; if only manual sorting and organizing of data step by step and node by node is required, it is not only labor-intensive but also has extremely low processing efficiency. (2) Existing commercial software mostly adopts integrated CFD-FEA coupling method, which can realize data transfer, but there are problems such as strong software binding, closed data format and difficulty in cross-platform reuse. (3) The lack of a unified time step structure makes it impossible to meet the requirements of dynamic analysis. Therefore, there is an urgent need for a method that can automatically aggregate, verify, complete, format, and output interpolated data in one click according to time steps, so as to eliminate process bottlenecks and improve engineering reliability. Summary of the Invention

[0004] This invention provides a general interpolation data processing method, apparatus, and electronic device to solve the problems of incompatibility between various CFD and FEA software formats, fragmented and inconsistent temporal sequences of flow field data across multiple computational domains, and difficulty in accurately interpolating and adapting CFD and FEA meshes.

[0005] In a first aspect, the present invention provides a general method for processing interpolated data, the method comprising: CFD software was used to simulate the flow path of the unit, obtaining output data from different computational domains. File parsing of the output data from each CFD software was performed to obtain the index relationship between physical quantity data and spatial nodes in different computational domains. The finite element analysis model of the unit flow path was analyzed to obtain the spatial coordinates and node numbers of each finite element node. Using each finite element node as the interpolation target node, and combining the first correspondence between the spatial coordinates of CFD spatial nodes and finite element nodes, the corresponding CFD interpolation source node was determined. Based on the physical quantity data at different time steps corresponding to each CFD interpolation source node, the standardized time series data of each CFD interpolation source node was determined. Based on the relationship between the CFD interpolation source node and the... The second correspondence between the spatial coordinates of the finite element nodes is established by interpolating standardized time-series data to the finite element nodes to obtain a transient load field sequence. This transient load field sequence contains load data of the global finite element nodes at different time steps. A load matrix file is constructed based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps. The node numbers of the corresponding finite element nodes are output according to the arrangement order of the interpolation target nodes to form a node number index file. When finite element analysis of the unit flow channel is required, the load matrix file and the node number index file are used to determine the pulsating pressure load applied to each finite element node in the finite element analysis model.

[0006] The general interpolation data processing method provided by this invention first obtains the original output data of the flow channel through multi-computation domain CFD simulation, and then establishes the index relationship between physical quantities and spatial nodes by parsing the CFD file. This solves the problems of messy output formats of different CFD software and fragmented data from multiple computation domains that cannot be uniformly scheduled, and realizes the structured collection of various CFD simulation data. By parsing the finite element model, the spatial coordinates and node numbers of the global finite element nodes are extracted to obtain the basic information of the structural mesh, providing a unified coordinate reference for cross-mesh node spatial matching and accurate load mapping. Based on the first correspondence between the spatial coordinates of CFD spatial nodes and finite element nodes, the directional matching of finite element target nodes and CFD interpolation source nodes is realized. Furthermore, source nodes are automatically filtered based on spatial location neighborhood logic to improve the rationality and accuracy of interpolation data source matching and avoid load calculation distortion caused by arbitrary point selection. The original time series data of CFD interpolation source nodes is normalized to obtain standardized time series data, which solves the problems of inconsistent time steps, misaligned start and end times, and abnormal noise data in multi-computation domain and multi-CFD software simulations, unifying the time series reference and eliminating invalid data. By utilizing the second correspondence, standardized time-series data is interpolated across grids to generate transient load field sequences, achieving full-domain integration of interpolation results from multiple computational domains. This solves the problem of fragmented load data in domain-specific simulations and the inability to form a complete spatial distribution of transient loads in the flow channel. Load matrix files are constructed according to fixed rules, and corresponding node number index files are generated, transforming discrete transient loads into standardized intermediate files with fixed row and column semantics. This masks the differences in node numbering rules and load import interfaces among different FEA software, achieving universal compatibility between various CFD and FEA software, significantly reducing the development cost and adaptation difficulty of simulation data integration.

[0007] In one optional implementation, based on a second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, a normalized time-series data is mapped to the finite element node using an interpolation method to obtain a transient load field sequence, including: Based on the second correspondence between the spatial coordinates of CFD interpolation source nodes and finite element nodes, one or more CFD interpolation source nodes are determined to match each finite element node; using the standardized time series data of the matched CFD interpolation source nodes, spatial interpolation calculations are performed on each finite element node to obtain the interpolation results for each time step corresponding to the finite element node; the interpolation results of different computational domains at the same time step are aggregated to obtain the transient load field sequence.

[0008] The general interpolation data processing method provided by this invention accurately matches the nearest CFD interpolation source node to each finite element node, avoiding interpolation calculation deviations caused by blind point selection. It maps standardized time-series data to finite element nodes using interpolation, ensuring the accuracy and reliability of the load numerical solutions at each time step. Furthermore, it integrates and unifies the interpolation results from multiple computational domains at the same time step, compensating for the defects of load data fragmentation and boundary discontinuities caused by multi-computational domain partitioned simulation, outputting complete and reliable single-node multi-time-step interpolation results, and finally obtaining the transient load field sequence.

[0009] In one optional implementation, interpolation results from different computational domains at the same time step are aggregated to obtain a transient load field sequence, including: The interpolation results of the finite element nodes at each time step are classified according to the preset time step to determine the interpolation results of different computational domains at each time step; the interpolation results of each computational domain at the same time step are aggregated to construct the transient load field of the global finite element nodes at a single time step; the transient load fields corresponding to each time step are arranged and integrated in time sequence to generate a complete transient load field sequence.

[0010] The general interpolation data processing method provided by this invention sorts and organizes scattered interpolation results by time and computational domain at a preset time step, solving the problem of mixed and disordered interpolation data from multiple computational domains and the difficulty in collection and integration. Then, it merges and splices the interpolation results from each computational domain at the same time step, making up for the defects of data fragmentation and inconsistent load distribution between domains caused by multi-CFD computational domain partitioning interpolation, forming a complete instantaneous load field covering all finite element nodes. Finally, it arranges the load fields at each time step in time sequence to construct a time-continuous transient load field sequence, making up for the shortcomings of static isolation of load at a single time moment and the inability to reflect the dynamic changes of load over time.

[0011] In one optional implementation, the standardized time-series data of each CFD interpolation source node is determined based on the physical quantity data at different time steps corresponding to each CFD interpolation source node, including: The time series features of CFD interpolation source nodes under each computational domain are extracted based on the index relationship; the CFD data of each computational domain are analyzed based on the time series features, the effective time step set is screened and abnormal time step data is removed; the consistency of the effective time step set of each computational domain is judged, and the corresponding time alignment strategy is determined based on the judgment result; the original time series data of CFD interpolation source nodes under each computational domain are processed using the time alignment strategy to obtain the standardized time series data corresponding to each CFD interpolation source node.

[0012] The general interpolation data processing method provided by this invention accurately depicts the variation law of flow field data in each partition by extracting the time series features of CFD nodes in each computational domain; it filters effective time steps based on time series features and removes abnormal data with divergent simulation values ​​and iterative distortion, and removes invalid data to ensure the authenticity of load calculation; furthermore, it performs consistency comparison on the effective time steps of multiple computational domains, which can accurately identify the differences in simulation start and end times, step size and sampling frequency of different computational domains, and then match the appropriate time alignment method; finally, it unifies and standardizes the CFD time series of multiple computational domains, eliminates the problem of inconsistent time series benchmarks of different CFD software and different sub-computational domains, and generates standardized time series data with consistent time series caliber and no noise interference, providing a reliable data source with time series regularization and logical self-consistency for subsequent cross-grid spatial interpolation and fusion and aggregation of interpolation results of multiple computational domains.

[0013] In one optional implementation, a load matrix file is constructed based on the transient load field sequence of each finite element node, including: According to the arrangement order of the interpolation target nodes, the time-series load data of each finite element node are integrated; the load data of the global finite element nodes at the same time step are integrated into a single row of data; the single row of data corresponding to all time steps is summarized in turn to generate a load matrix file. Each row in the load matrix file is used to represent a corresponding time step, and each column is used to represent a finite element node.

[0014] The interpolation data general processing method provided by this invention collects the time-series load data of each finite element node in a fixed node order, and organizes the originally scattered single-node multi-time-step load data in an orderly manner; constructs a two-dimensional load matrix with time steps as rows and finite element nodes as columns, and transforms the irregular transient load data into a standardized data format with a fixed structure, providing a unified and standardized data organization form for the general import of loads into multiple FEA software.

[0015] In one optional implementation, the node numbers of the corresponding finite element nodes are output according to the arrangement order of the interpolation target nodes to form a node number index file, including: Match and extract the node numbers of the corresponding finite element nodes one by one according to the arrangement order of the interpolation target nodes; organize the node numbers of the global finite element nodes in the order of arrangement to form a node number index file. The node arrangement order of the node number index file is consistent with the arrangement order of each column of the load matrix file.

[0016] The interpolation data processing method provided by this invention strictly matches the column order of the load matrix to generate a node number index file, establishing a one-to-one mapping relationship between the column positions of the load matrix and the actual node numbers of the finite element model. This solves the problem that the load matrix only contains load values ​​and cannot correspond to the actual nodes of the structure. It also resolves the adaptation difficulties caused by the differences in node numbering rules among different FEA software. Changing FEA software does not require modifying the load matrix structure; node matching can be completed solely based on the index file, ensuring that transient loads are accurately applied to the target nodes of the finite element model.

[0017] Secondly, the present invention provides a general interpolation data processing apparatus, the apparatus comprising: The data acquisition module is used to simulate and calculate the flow channel of the unit using CFD software to obtain output data in different computational domains. The file parsing module is used to parse the output data of various CFD software to obtain the index relationship between physical quantity data and spatial nodes in different computational domains. The finite element model analysis module is used to analyze the finite element analysis model of the unit's flow channel to obtain the spatial coordinates and node numbers of each finite element node. The interpolation source node determination module is used to determine the CFD interpolation source node corresponding to each interpolation target node by taking each finite element node as the interpolation target node and combining the first correspondence between the spatial coordinates of the CFD spatial node and the finite element node. The data standardization module is used to determine the standardized time series data of each CFD interpolation source node based on the physical quantity data of each time step corresponding to each CFD interpolation source node. The interpolation mapping module is used to map standardized time series data to finite element nodes using interpolation based on the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, thereby obtaining a transient load field sequence. The transient load field sequence contains load data of the global finite element node at different time steps. The load matrix file construction module is used to construct a load matrix file based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps. The node number index file construction module is used to output the node numbers of the corresponding finite element nodes according to the arrangement order of the interpolation target nodes, forming a node number index file. When finite element analysis is required for the unit flow channel, the load matrix file and the node number index file are used to determine the pulsating pressure load applied to each finite element node in the finite element analysis model.

[0018] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the interpolation data general processing method of the first aspect or any corresponding embodiment described above.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the interpolation data general processing method of the first aspect or any corresponding embodiment described above.

[0020] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the general interpolation data processing method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating a general interpolation data processing method according to an embodiment of the present invention; Figure 3 This is a structural block diagram of a general interpolation data processing apparatus according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0025] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0026] As an optional application scenario of this invention, the specific application environment architecture or specific hardware architecture on which the execution of the general interpolation data processing method depends is described here. For example... Figure 1 As shown, the architecture system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0027] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0028] According to an embodiment of the present invention, a general method for processing interpolated data is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] This embodiment provides a general method for processing interpolated data, which can be used in the aforementioned mobile terminals, such as mobile phones and tablets. Figure 2 This is a flowchart of a general interpolation data processing method according to an embodiment of the present invention, such as... Figure 2As shown, the process includes the following steps: Step S201: Use CFD software to simulate and calculate the flow channel of the unit to obtain output data of different computational domains.

[0030] In one optional embodiment, the unit's flow channel geometry is complex and the flow field gradient varies greatly, making single-domain simulation unsuitable. The flow channel is divided into multiple independent computational domains. The fluid dynamics control equations are discretized and solved using CFD software, generating discrete grid nodes in each computational domain. The raw flow field physical quantities of each CFD spatial node at each time step are calculated and output, providing the raw flow field data source for subsequent interpolation. Specifically, interpolation result files from different CFD software or different computational domains of the same CFD software are acquired, including various data types such as CSV, HDF5, VTK, and TXT. The interpolation result files store key information such as node number, coordinates, interpolation results, and time step index.

[0031] Step S202: Parse the output data of each CFD software to obtain the index relationship between physical quantity data and spatial nodes in different computational domains.

[0032] In one optional embodiment, the spatial nodes of the CFD are discrete nodes of the CFD fluid simulation grid, storing coordinates and flow field physical quantities at each time step. The computational domain is a sub-computational region where the complex unit flow channel is divided into multiple independent sub-regions for CFD simulation, such as the volute region (SP), fixed guide vane region (SV), movable guide vane region (GV), cover plate and bottom ring region (GAP), and tailrace region (DT). Different vendors' CFD software output results have inconsistent file formats and data storage structures. It is necessary to extract the physical quantity values, node spatial coordinates, and node numbers for each computational domain from the binary or text result files through file parsing and decoding. Simultaneously, an index mapping relationship between CFD spatial node numbers, coordinates, and time-series physical quantities needs to be established.

[0033] Specifically, the parsing method needs to be determined based on the storage method of time-series data in each computation domain. The storage method includes storage methods based on time steps as the basic unit, storage methods based on nodes or probes as the basic unit, etc.

[0034] When the data file is identified as having time steps as its basic unit, the following parsing steps are performed: (1) Time stamp parsing: Extract the time step stamp corresponding to the file from the data file or its file name and metadata; (2) Regional grouping feature identification: Determine whether there are regional grouping or segmented output features in the time step file; when features exist, classify the data records into regions according to the pre-set or user-specified region identifier field; the region identifier field is used to indicate the computing domain or sub-region to which each data record belongs. Among them, the region identifier field is an abstract concept and can be any information carrier that can distinguish the region affiliation, without limiting its specific form or name.

[0035] (3) Node information parsing: After completing the region classification, the node numbers and their corresponding spatial coordinate information contained in the parsing file are parsed to establish the mapping relationship between the node numbers and the unified node index.

[0036] (4) Parsing of physical quantity fields: Parse the physical quantity data corresponding to each node at this time step, and establish a relationship with the node index, time index and calculation domain identifier.

[0037] When the data file is identified as having nodes or probes as its basic units, the following parsing steps are performed: (1) Node identifier resolution: Identify the region identifier and node number or probe identifier corresponding to the data file from the data file name or file content, and map them to the unified node index; (2) Time series parsing: Parse the multiple time step information contained in the file and extract the corresponding time identifiers; (3) Physical quantity time series analysis: Analyze the physical quantity data corresponding to the node at each time step, and establish a corresponding relationship with the node index and time index.

[0038] Step S203: Analyze the finite element analysis model of the unit flow channel to obtain the spatial coordinates and node numbers of each finite element node.

[0039] In one optional embodiment, the CFD fluid mesh and the FEA structural mesh are two independent discrete meshes, and there is no natural matching relationship between them in terms of node number, mesh density, node numbering rules, and spatial topology. Therefore, it is necessary to analyze the FEA finite element model to extract the three-dimensional spatial coordinates and inherent node numbers of all discrete finite element nodes in the FEA, providing the original coordinate and numbering basis for subsequent cross-mesh spatial neighborhood matching and later index file construction.

[0040] Step S204: Using each finite element node as the interpolation target node, and combining the first correspondence between the spatial coordinates of the CFD spatial nodes and the finite element nodes, determine the CFD interpolation source node corresponding to each interpolation target node.

[0041] In one optional embodiment, each finite element node is used as the interpolation target node to be assigned values. Based on a first correspondence relationship and using the three-dimensional coordinates of the finite element node as a reference, a spatial neighborhood distance search is performed among all CFD spatial nodes in the global computational domain. One or more CFD nodes with spatially adjacent locations are selected and designated as the CFD interpolation source nodes of the target node. The first correspondence relationship is a spatial neighborhood association between the original CFD spatial nodes and finite element nodes in the global domain, constructed based on three-dimensional spatial coordinates.

[0042] Step S205: Determine the standardized time series data of each CFD interpolation source node based on the physical quantity data of each time step corresponding to each CFD interpolation source node.

[0043] In one optional embodiment, the original time-series data from multi-computation domain and multi-CFD software simulations suffer from issues such as inconsistent time steps, inconsistent start and end times, and abnormal noise in local time-step data. The original multi-time-step physical quantities of each interpolation source node are extracted based on index relationships, and then processed to generate standardized time-series data with unified timing rules.

[0044] Step S206: Based on the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, the standardized time series data is mapped to the finite element node using an interpolation method to obtain the transient load field sequence. The transient load field sequence contains the load data of the global finite element node at different time steps.

[0045] In one optional embodiment, a spatial interpolation algorithm is used based on the second correspondence to numerically solve and map the standardized temporal physical quantities of the CFD interpolation source nodes to the corresponding finite element nodes step by step; then, the interpolation results of multiple computational domains at the same time step are integrated to form a transient load field sequence. The second correspondence is the spatial positional association between the selected and matched CFD interpolation source nodes and finite element nodes.

[0046] Step S207: Construct a load matrix file based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps.

[0047] In one optional embodiment, the time-series load data of each node is reconstructed into a two-dimensional matrix structure according to a uniform interpolation target node arrangement order. Rows represent individual time steps and lists represent individual finite element nodes, and the discrete transient load data is regularized into a matrix format to construct a load matrix file.

[0048] Step S208: Output the node numbers of the corresponding finite element nodes according to the arrangement order of the interpolation target nodes, forming a node number index file.

[0049] In one optional embodiment, the load matrix file only stores load values ​​and does not carry the original node numbers of the FEA model, thus it cannot directly correspond to the actual structural nodes. Following the target node order that is completely consistent with the column arrangement of the load matrix, the original finite element node numbers corresponding to each position are extracted, generating a node number index file. This establishes a mapping relationship between the matrix column numbers and the actual FEA node numbers, providing a numbering mapping basis for the FEA software to accurately locate the structural nodes corresponding to the loads. When finite element analysis of the unit's flow channel is required, the load matrix file and the node number index file are used to determine the pulsating pressure loads applied to each finite element node in the finite element analysis model. After the pulsating pressure loads are applied, the FEA software performs structural finite element simulation calculations, ultimately outputting structural simulation data such as the transient displacement field, transient stress field, strain distribution, structural vibration response, and node dynamics results.

[0050] The load matrix file and node number index file adopt a standardized custom format independent of various CFD and FEA software, shielding the differences in output formats, node numbering rules, and data interfaces of different CFD software. When changing upstream CFD software, it is only necessary to follow the unified process of this method to complete the parsing of new CFD data, time series standardization, and cross-grid interpolation aggregation, and still generate the load matrix file and the node number index file with consistent arrangement logic according to the fixed row and column rules, without modifying the downstream adaptation logic. When changing downstream FEA software, it is not necessary to re-perform CFD simulation and interpolation calculation, but only to parse the node numbers of the new FEA model, match the fixed arrangement order to regenerate the node number index file, and establish a one-to-one mapping relationship between the column order of the load matrix and the node numbers of any FEA software based on the index file. The CFD data processing and FEA load are decoupled through two standardized intermediate files, without the need to develop separate adaptation interfaces for different simulation software, thereby achieving universal compatibility and adaptation for multiple CFD and multiple FEA software.

[0051] The general interpolation data processing method provided in this embodiment first obtains the original output data of the flow channel through multi-computation domain CFD simulation, and then establishes the index relationship between physical quantities and spatial nodes by parsing the CFD file. This solves the problems of messy output formats of different CFD software and fragmented data from multiple computation domains that cannot be uniformly scheduled, and realizes the structured collection of various CFD simulation data. By parsing the finite element model, the spatial coordinates and node numbers of the global finite element nodes are extracted to obtain the basic information of the structural mesh, providing a unified coordinate reference for cross-mesh node spatial matching and accurate load mapping. Based on the first correspondence between the spatial coordinates of CFD spatial nodes and finite element nodes, the directional matching of finite element target nodes and CFD interpolation source nodes is realized. Furthermore, source nodes are automatically filtered based on spatial location neighborhood logic to improve the rationality and accuracy of interpolation data source matching and avoid load calculation distortion caused by arbitrary point selection. The original time series data of CFD interpolation source nodes is normalized to obtain standardized time series data, which solves the problems of inconsistent time steps, misaligned start and end times, and abnormal noise data in multi-computation domain and multi-CFD software simulations, unifying the time series reference and eliminating invalid data. By utilizing the second correspondence, standardized time-series data is interpolated across grids to generate transient load field sequences, achieving full-domain integration of interpolation results from multiple computational domains. This solves the problem of fragmented load data in domain-specific simulations and the inability to form a complete spatial distribution of transient loads in the flow channel. Load matrix files are constructed according to fixed rules, and corresponding node number index files are generated, transforming discrete transient loads into standardized intermediate files with fixed row and column semantics. This masks the differences in node numbering rules and load import interfaces among different FEA software, achieving universal compatibility between various CFD and FEA software, significantly reducing the development cost and adaptation difficulty of simulation data integration.

[0052] In some optional implementations, step S206 above includes: Step a1: Based on the second correspondence between the spatial coordinates of the CFD interpolation source nodes and the finite element nodes, determine one or more CFD interpolation source nodes that match each finite element node.

[0053] In one optional embodiment, based on the spatial coordinate position association between the established CFD interpolation source nodes and finite element nodes, and taking a single finite element node as the interpolation target unit, one or more source nodes that are spatially adjacent are locked from the pre-selected set of CFD interpolation source nodes according to the three-dimensional spatial coordinate neighborhood distance logic.

[0054] Specifically, within each CFD calculation region, at least one or more representative CFD interpolation source nodes are selected, such as: calculation nodes at typical locations within the region; locations corresponding to finite element load-sensitive areas; or monitoring points specified by the user.

[0055] Step a2: Using the standardized time series data of the matched CFD interpolation source nodes, perform spatial interpolation calculations on each finite element node to obtain the interpolation results for each time step of the finite element node.

[0056] In one optional embodiment, based on the matched CFD interpolation source node as the calculation benchmark, standardized time-series physical quantity data, after anomaly removal and time alignment calibration, is invoked. Based on the principle of spatial interpolation numerical algorithms and combined with the spatial position weight allocation rules between the source node and the finite element target node, physical quantity numerical solutions are performed step-by-step. The time-series load data of the discrete CFD source node is mapped and converted to the finite element node, and the interpolated physical quantity numerical results corresponding to each finite element node at each time step are obtained.

[0057] Step a3: Aggregate the interpolation results of different computational domains at the same time step to obtain the transient load field sequence.

[0058] In one optional embodiment, multiple CFD computational domains perform interpolation operations independently, and the interpolation results at the same simulation time step are scattered and stored in each computational domain, making it impossible to form a complete global node load distribution; it is necessary to aggregate the interpolation results of different computational domains at the same time step to form a transient load field sequence.

[0059] After completing the interpolation calculation from CFD data to finite element nodes, the interpolation results are subjected to global consistency verification and quality control processing to determine the rationality of the interpolation results in terms of spatial distribution and temporal evolution.

[0060] First, construct the following two types of comparable datasets: (1) CFD original or reconstructed result dataset before interpolation; (2) Finite element node interpolation result dataset after interpolation.

[0061] For the datasets before and after interpolation, a comparative analysis of the spatial distribution of physical quantities at the same time step is conducted, focusing on: the consistency of the overall distribution pattern of physical quantities; the consistency of extreme value locations and trends; and whether there are abnormal amplification, attenuation, or abrupt changes in local regions.

[0062] Furthermore, visualizations, such as two-dimensional or three-dimensional cloud maps based on spatial field distribution, are generated for the datasets before and after interpolation. By comparing the visualization results before and after interpolation, at least one of the following anomalies is identified: non-physical oscillations in the interpolation result in local regions; significant distortion in the interpolation result at boundaries or interface regions; and a significant deviation between the overall distribution of the interpolation result and the original CFD data. When the above anomalies are detected, the corresponding time step or spatial region is marked for subsequent processing or user confirmation. After the interpolation result passes spatial consistency and visualization verification, it is confirmed that it meets the load output requirements and is allowed to proceed to subsequent steps.

[0063] The general interpolation data processing method provided in this embodiment accurately matches the nearest CFD interpolation source node to each finite element node, avoiding interpolation calculation deviations caused by blind point selection. Standardized time-series data is mapped to finite element nodes using interpolation, ensuring the accuracy and reliability of the load numerical solutions at each time step. Furthermore, the interpolation results from multiple computational domains at the same time step are integrated and unified to compensate for the load data fragmentation and boundary discontinuities caused by multi-computational domain partitioned simulation, outputting complete and reliable single-node multi-time-step interpolation results, ultimately obtaining the transient load field sequence.

[0064] In some alternative implementations, step a3 above includes: Step a31: Classify the interpolation results of the finite element nodes at each time step according to the preset time step, and determine the interpolation results of different computational domains at each time step.

[0065] In one optional embodiment, the preset time step refers to the standard discrete-time sampling moment uniformly defined after time alignment across multiple computational domains, serving as a unified benchmark for the normalization of time-series data across all computational domains. The interpolation results of each finite element node are accompanied by the identifier of its respective CFD computational domain and the original time step information. Furthermore, the original simulation time steps across multiple computational domains may have inconsistent start and end points and step sizes. Using the time-standardized preset time step as a unified benchmark scale, all scattered interpolation results are first aggregated according to the time step dimension, and then further split within the same time step according to the computational domain dimension, accurately dividing the interpolation results belonging to different computational domains under each standard time step.

[0066] Step a32: Aggregate the interpolation results corresponding to each computational domain at the same time step to construct the transient load field of the global finite element nodes at a single time step.

[0067] In one optional embodiment, under the same preset time step, each independent computational domain can only generate the interpolation results of the finite element nodes within its own region. The data between subdomains is fragmented and the boundaries have no continuous transition. Under a fixed single time step dimension, the discrete interpolation results of multiple computational domains are spliced ​​and integrated, the boundary data is smoothly connected, and redundant data is deduplicated, and aggregated into a complete spatial load distribution covering the finite element nodes of the entire flow channel, constituting the transient load field corresponding to that moment.

[0068] Specifically, the system determines whether the following conditions exist: multiple CFD regions correspond to the same finite element node; different CFD regions spatially overlap in the finite element model; and the same node obtains multiple physical quantity values ​​at the same time step. When multiple interpolation results are detected for the same finite element node at the same time step, the interpolation results are processed according to preset aggregation rules. These aggregation rules include: weighted synthesis, averaging synthesis, and selection based on priority rules.

[0069] Step a33: Arrange and integrate the transient load fields corresponding to each time step in time sequence to generate a complete transient load field sequence.

[0070] In one optional embodiment, a single transient load field can only characterize the instantaneous spatial load distribution at a certain preset time step, and cannot reflect the characteristics of load change over time. Using the simulation time series as the sequential reference, the transient load fields corresponding to all discrete preset time steps are time-sequentially aligned and sequentially connected, combining the load distribution at a single moment into a time-sequentially evolving, time-continuous global transient load field sequence.

[0071] The general interpolation data processing method provided in this embodiment sorts and organizes scattered interpolation results by time and computational domain at a preset time step, solving the problem of mixed and disordered interpolation data from multiple computational domains that are difficult to collect and integrate. Then, the interpolation results from each computational domain at the same time step are fused and stitched together, making up for the defects of data fragmentation and inconsistent load distribution between domains caused by multi-CFD computational domain partitioning interpolation, forming a complete instantaneous load field covering all finite element nodes. Finally, the load fields at each time point are arranged sequentially according to time sequence to construct a time-continuous transient load field sequence, making up for the shortcomings of static isolation of load at a single time point and inability to reflect the dynamic changes of load over time.

[0072] In some optional implementations, step S205 above includes: Step b1: Extract the time series features of CFD interpolation source nodes in each computational domain based on the index relationship.

[0073] In one optional embodiment, based on the index mapping relationship between nodes and physical quantity data, the system is partitioned and located according to different computational domains, and the original time-series data of physical quantities for each CFD interpolation source node are retrieved one by one across all simulation time steps. Time-series features such as the fluctuation patterns, amplitude ranges, and trends of physical quantities over time are extracted from the original time-series data to characterize the temporal changes of the flow field in each computational domain. These time-series features include: the number of time steps, the time step interval, the time step sequence, and the amplitude characteristics and trends of physical quantities over time.

[0074] Step b2 involves analyzing the CFD data of each computational domain based on time series characteristics, filtering the set of valid time steps, and removing abnormal time step data.

[0075] In one optional embodiment, the extracted time series features are used as the discrimination criteria, and the values ​​of each time step in each computational domain are compared and verified against the normal variation law of the physical quantities of the flow field. The time steps that deviate from the feature law, have abrupt changes and divergence, or do not conform to the physical mechanism of the flow field are judged as abnormal time steps and removed. The time steps with normal variation law and simulation effectiveness are retained, and a set of effective time steps exclusive to each computational domain is formed.

[0076] Specifically, based on the time series characteristics, the values ​​of each time step in each computational domain are analyzed to determine whether at least one of the following situations exists: missing or abnormal time steps, irregular time step intervals, abnormal abrupt changes or non-physical oscillations in physical quantities; based on the analysis results, a set of effective time steps that can be used for interpolation calculation is determined, and time steps that do not meet the requirements of completeness or stability are removed, and only data within representative time periods are retained. Data regions or time periods that do not meet the requirements are marked and skipped for interpolation processing.

[0077] Step b3: Perform consistency judgment on the effective time step set of each computation domain, and determine the corresponding time alignment strategy based on the judgment result.

[0078] In one optional embodiment, the start and end times, time step length, sampling frequency, and other timing parameters of the effective time step set of each computation domain are decomposed respectively. The differences in timing parameters of multiple computation domains are compared horizontally to complete the consistency verification of the time step set. According to the type of difference, such as different step lengths, misaligned start and end times, inconsistent sampling densities, etc., the time step set is classified and adapted, and the corresponding time regularization, interpolation, or benchmark alignment method is matched in a targeted manner to determine the exclusive time alignment strategy adapted to multiple computation domains.

[0079] Specifically, after completing the screening of valid interpolation data, a consistency judgment is performed on the set of retained valid time steps to determine whether there are inconsistencies in the number, interval, or order of time steps between different CFD data sources, and the corresponding time alignment strategy is determined accordingly, including: time step reconstruction, time step completion, time step screening, and time step resampling.

[0080] Step b4: The original time series data of the CFD interpolation source nodes in each computational domain are processed using a time alignment strategy to obtain the standardized time series data corresponding to each CFD interpolation source node.

[0081] In one optional embodiment, according to the corresponding time alignment strategy, and with a unified standard time reference, the original time series data of CFD in each computing domain are subjected to time series resampling, missing time points are filled in, and time step regularization and calibration are performed to eliminate the differences in time series parameters caused by different computing domains and different CFD software. This ensures that the physical quantity data of all CFD interpolation source nodes are unified under the same time scale, forming standardized time series data with consistent time series reference, no abnormal interference, and applicable across computing domains.

[0082] The general interpolation data processing method provided in this embodiment accurately characterizes the variation law of flow field data in each partition by extracting the time series features of CFD nodes in each computational domain; it filters effective time steps based on time series features and removes abnormal data with divergent simulation values ​​and iterative distortion, and removes invalid data to ensure the authenticity of load calculation; furthermore, it performs consistency comparison on the effective time steps of multiple computational domains, which can accurately identify the differences in simulation start and end times, step size and sampling frequency of different computational domains, and then match the appropriate time alignment method; finally, it unifies and standardizes the CFD time series of multiple computational domains, eliminates the problem of inconsistent time series benchmarks of different CFD software and different sub-computational domains, and generates standardized time series data with consistent time series caliber and no noise interference, providing a reliable data source with time series regularization and logical self-consistency for subsequent cross-grid spatial interpolation and fusion and aggregation of interpolation results of multiple computational domains.

[0083] In some optional implementations, step S207 above, which constructs a load matrix file based on the transient load field sequence of each finite element node, includes: Step c1: Integrate the time-series load data of each finite element node according to the arrangement order of the interpolation target nodes.

[0084] In one optional embodiment, the time-series load data of each finite element node in the transient load field sequence are discretely distributed without a uniform arrangement order. A fixed interpolation target node sorting rule is preset, and the complete full-time-step time-series load data of each finite element node is collected one by one in strict accordance with this order, so that the scattered single-node time-series loads are organized into a unified node order.

[0085] Step c2 integrates the load data of the global finite element nodes at the same time step into a single row of data.

[0086] In one optional embodiment, using a single time step as the statistical unit, the instantaneous load values ​​of each finite element node are extracted sequentially according to the interpolation target node arrangement order at the current time step. The load values ​​of all nodes at the same time step are continuously spliced ​​together to form a complete one-dimensional data row, so that a single row of data can fully carry the load distribution information of all finite element nodes at a certain time step.

[0087] Step c3: Summarize the single-row data corresponding to all time steps in sequence to generate a load matrix file. Each row in the load matrix file is used to represent a corresponding time step, and each column is used to represent a finite element node.

[0088] In one optional embodiment, the single-row load data generated at each time step are stacked sequentially according to the temporal logic of the simulation time from earliest to latest, constructing a two-dimensional matrix structure. Each row corresponds to a time step, and each column corresponds to a finite element node with a fixed order, resulting in a load matrix file.

[0089] The general interpolation data processing method provided in this embodiment collects the time-series load data of each finite element node in a fixed node order, and organizes the originally scattered single-node multi-time-step load data into an orderly manner; constructs a two-dimensional load matrix with time steps as rows and finite element nodes as columns, and transforms the irregular transient load data into a standardized data format with a fixed structure, providing a unified and standardized data organization form for the general import of loads into multiple FEA software.

[0090] In some optional implementations, step S208 above, which outputs the node numbers of the corresponding finite element nodes according to the arrangement order of the interpolation target nodes, forming a node number index file, includes: Step d1: Match and extract the node numbers of the corresponding finite element nodes one by one according to the arrangement order of the interpolation target nodes.

[0091] In one optional embodiment, a sorting rule is pre-defined for all interpolation target nodes, and each interpolation target node is associated with a node number inherent to the finite element node. Using the predetermined node arrangement order as the traversal basis, each interpolation target node in the sequence is located sequentially, and its corresponding node number in the finite element model is matched and retrieved, thus completing the accurate extraction of the number one by one.

[0092] Step d2: Arrange the node numbers of the global finite element nodes in the order of arrangement to form a node number index file.

[0093] In one optional embodiment, the extracted finite element node numbers are systematically collected and organized according to the original arrangement order of the interpolation target nodes; an index file is generated by encapsulating the data in a text or standard file format, and the arrangement order of the node numbers within the index file is constrained to be completely synchronized and aligned with the column arrangement order representing the finite element nodes in the load matrix file. A fixed mapping logic is established between the load matrix column position, the index file sequence number, and the FEA native node number.

[0094] The general interpolation data processing method provided in this embodiment strictly matches the column order of the load matrix to generate a node number index file, establishing a one-to-one mapping relationship between the column positions of the load matrix and the actual node numbers of the finite element model. This solves the problem that the load matrix only contains load values ​​and cannot correspond to the actual nodes of the structure. It also solves the adaptation problem caused by the differences in node numbering rules among different FEA software. Changing FEA software does not require modifying the load matrix structure; node matching can be completed solely based on the index file, ensuring that transient loads can be accurately applied to the target nodes of the finite element model.

[0095] This embodiment also provides a general interpolation data processing apparatus for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0096] This embodiment provides a general interpolation data processing device, such as... Figure 3 As shown, it includes: The data acquisition module 301 is used to use CFD software to perform simulation calculations on the unit flow channel to obtain output data in different calculation domains. The file parsing module 302 is used to parse the output data of various CFD software to obtain the index relationship between physical quantity data and spatial nodes in different computational domains. The finite element model analysis module 303 is used to analyze the finite element analysis model of the unit flow channel to obtain the spatial coordinates and node numbers of each finite element node. The interpolation source node determination module 304 is used to determine the CFD interpolation source node corresponding to each interpolation target node by taking each finite element node as the interpolation target node and combining the first correspondence between the spatial coordinates of the CFD spatial node and the finite element node. The data standardization module 305 is used to determine the standardized time series data of each CFD interpolation source node based on the physical quantity data of each time step corresponding to each CFD interpolation source node. The interpolation mapping module 306 is used to map standardized time series data to finite element nodes by interpolation according to the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, so as to obtain the transient load field sequence. The transient load field sequence contains the load data of the global finite element node at different time steps. The load matrix file construction module 307 is used to construct a load matrix file based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps. The node number index file construction module 308 is used to output the node number of the corresponding finite element node according to the arrangement order of the interpolation target node, forming a node number index file. When it is necessary to perform finite element analysis on the unit flow channel, the load matrix file and the node number index file are used to determine the pulsating pressure load applied to each finite element node in the finite element analysis model.

[0097] The general interpolation data processing apparatus provided in this embodiment of the invention can execute the general interpolation data processing method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0098] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0099] The following is a detailed reference. Figure 4 This diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 402 or a program loaded from memory 408 into random access memory (RAM) 403. The RAM 403 also stores various programs and data required for the operation of the electronic device. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0100] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0101] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 409, or installed from a memory 408, or installed from a ROM 402. When the computer program is executed by the processor 401, it performs the functions defined in the general interpolation data processing method of the embodiments of the present invention.

[0102] Figure 4The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0103] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the general interpolation data processing method shown in the above embodiments is implemented.

[0104] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0105] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A general method for processing interpolated data, characterized in that, The method includes: CFD software was used to simulate and calculate the flow channel of the unit to obtain output data in different computational domains; File parsing of the output data of various CFD software yields the index relationship between physical quantity data and spatial nodes in different computational domains; The finite element analysis model of the unit's flow channel is analyzed to obtain the spatial coordinates and node numbers of each finite element node; Using each finite element node as the interpolation target node, and combining the first correspondence between the spatial coordinates of the CFD spatial nodes and the finite element nodes, the CFD interpolation source node corresponding to each interpolation target node is determined. Based on the physical quantity data of each CFD interpolation source node at different time steps, the standardized time series data of each CFD interpolation source node are determined. Based on the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, the standardized time series data is mapped to the finite element node using an interpolation method to obtain a transient load field sequence. The transient load field sequence contains load data of the global finite element node at different time steps. A load matrix file is constructed based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps. The node numbers of the corresponding finite element nodes are output according to the arrangement order of the interpolation target nodes to form a node number index file. When finite element analysis is required for the unit flow channel, the load matrix file and the node number index file are used to determine the pulsating pressure load applied to each finite element node in the finite element analysis model.

2. The method according to claim 1, characterized in that, Based on the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, the standardized time-series data is mapped to the finite element node using an interpolation method to obtain a transient load field sequence, including: Based on the second correspondence between the spatial coordinates of the CFD interpolation source nodes and the finite element nodes, determine one or more CFD interpolation source nodes that match each finite element node. Using the standardized time series data of the matched CFD interpolation source nodes, spatial interpolation calculations are performed on each finite element node to obtain the interpolation results of each time step corresponding to the finite element node. The interpolation results from different computational domains at the same time step are aggregated to obtain the transient load field sequence.

3. The method according to claim 2, characterized in that, By aggregating the interpolation results from different computational domains at the same time step, a transient load field sequence is obtained, including: The interpolation results of the finite element nodes at each time step are classified according to the preset time step to determine the interpolation results of different computational domains at each time step. The interpolation results corresponding to each computational domain at the same time step are aggregated to construct the transient load field of the global finite element node at a single time step; The transient load fields corresponding to each time step are arranged and integrated in time sequence to generate a complete transient load field sequence.

4. The method according to claim 1, characterized in that, Based on the physical quantity data at different time steps corresponding to each CFD interpolation source node, the standardized time series data of each interpolation source node are determined, including: Based on the index relationship, extract the time series features of CFD interpolation source nodes under each computational domain; Based on the time series characteristics, the CFD data of each computational domain are analyzed to filter the effective time step set and remove abnormal time step data. Consistency determination is performed on the effective time step set of each computation domain, and the corresponding time alignment strategy is determined based on the determination result. The original time series data of CFD interpolation source nodes in each computational domain are processed using the time alignment strategy described above to obtain the standardized time series data corresponding to each CFD interpolation source node.

5. The method according to claim 1, characterized in that, A load matrix file is constructed based on the transient load field sequence of each finite element node, including: The temporal load data of each finite element node are integrated according to the arrangement order of the interpolation target nodes. The load data of the global finite element nodes at the same time step are integrated into a single row of data; The single-row data corresponding to all time steps are summarized in sequence to generate a load matrix file. Each row in the load matrix file is used to represent a corresponding time step, and each column is used to represent a finite element node.

6. The method according to claim 1, characterized in that, Based on the arrangement order of the interpolation target nodes, the node numbers of the corresponding finite element nodes are output to form a node number index file, including: Match and extract the node numbers of the corresponding finite element nodes one by one according to the arrangement order of the interpolation target nodes; The node numbers of the global finite element nodes are arranged in the order of arrangement to form a node number index file. The node arrangement order of the node number index file is consistent with the column arrangement order of the load matrix file.

7. A general-purpose interpolation data processing device, characterized in that, The device includes: The data acquisition module is used to simulate and calculate the flow channel of the unit using CFD software to obtain output data in different computational domains. The file parsing module is used to parse the output data of various CFD software to obtain the index relationship between physical quantity data and spatial nodes in different computational domains. The finite element model analysis module is used to analyze the finite element analysis model of the unit flow channel to obtain the spatial coordinates and node numbers of each finite element node. The interpolation source node determination module is used to determine the CFD interpolation source node corresponding to each interpolation target node by taking each finite element node as the interpolation target node and combining the first correspondence between the spatial coordinates of the CFD spatial node and the finite element node. The data standardization module is used to determine the standardized time series data of each CFD interpolation source node based on the physical quantity data of each time step corresponding to each CFD interpolation source node. The interpolation mapping module is used to map the standardized time series data to the finite element nodes using an interpolation method based on the second correspondence between the spatial coordinates of the CFD interpolation source node and the finite element node, so as to obtain the transient load field sequence, which contains the load data of the global finite element node at different time steps. The load matrix file construction module is used to construct a load matrix file based on the transient load field sequence of each finite element node. The load matrix file contains load data corresponding to different finite element nodes at different time steps. The node number index file construction module is used to output the node number of the corresponding finite element node according to the arrangement order of the interpolation target node, forming a node number index file. When it is necessary to perform finite element analysis on the unit flow channel, the load matrix file and the node number index file are used to determine the pulsating pressure load applied to each finite element node in the finite element analysis model.

8. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the general interpolation data processing method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the general interpolation data processing method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to perform the general interpolation data processing method according to any one of claims 1 to 6.

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