Storage method and database for cfd verification and validation benchmark data

Abstract

The application discloses a kind of CFD verification and confirmation mark mould data storage method and database, belong to aerodynamic database technical field, including steps: CFD verification and confirmation mark mould data warehousing;Extract mark mould example basic information again, parse, organize example test / calculating result structure data, design form CFD verification and confirmation mark mould data table;The CFD verification and confirmation mark mould data table includes core data table.The application can realize the dynamic storage of different standard examples of incoming flow state data and result data, reduce data redundancy, improve data scalability, can ensure that database platform can accurately, efficiently provide data services for CFD software credibility evaluation or related research.

Description

Technical Field

[0001] This invention relates to the field of pneumatic database technology, and more specifically, to a method and database for storing CFD verification and validation model data. Background Technology

[0002] With the continuous improvement of numerical computing capabilities and methods, the interdisciplinary integration of computer science with fluid mechanics, aerospace engineering, and other disciplines has developed rapidly, resulting in a proliferation of CFD software for simulating and solving various flow problems. The reliability of CFD software determines its practical application value, and scientific and objective verification and validation are the only way to evaluate the reliability of CFD software and an important means of ensuring its quality.

[0003] Reliable validation and verification standard data are not only fundamental support for the establishment and development of wind tunnel testing and CFD technologies, but also indispensable standard, basic, and functional verification bases in the development of various aircraft. Aerodynamic research institutions both domestically and internationally have always attached great importance to the collection and management of standard data. To support the validation and verification research of CFD software, many international institutions have collected and organized various dedicated standard datasets and established corresponding databases. As international conferences held to evaluate the level and capability of calculation methods in predicting aircraft aerodynamic forces and moments, the AIAA High Lift and Drag Prediction Conferences publicly release the typical standard data collected. The EU's FLOWNET database includes 56 validation and verification-specific standard case data; the QNET-CFD knowledge base contains a large amount of industrial experimental and CFD data. Currently, there are almost no publicly shared validation and verification standard databases in China. Some research institutions have internal databases or datasets for conducting CFD credibility analysis. To support the automated testing and credibility evaluation of the CFD series software for the National Numerical Wind Tunnel Engineering project, and to provide standard case data support for CFD-related research, this study aims to address these issues. The verification and validation system has collected and organized several classic domestic and international standard calculation examples as well as a number of independently designed experimental standard calculation examples, and built a CFD verification and validation database platform to store and manage these data.

[0004] Currently, for structured aerodynamic results data, existing aerodynamic databases typically create separate tables for different data types. Each data type table pre-defines all incoming flow states and result parameter fields. When aerodynamic data is entered, it is stored in the corresponding location by matching field names, with default fields left empty. This existing technology has the following technical problems:

[0005] (1) Although the incoming flow state parameters of different data types in the same example are different, they have a large overlap, resulting in data redundancy in the table.

[0006] (2) Pre-setting data type tables and parameter fields can satisfy the storage of existing types and parameters, but when new experiments or calculation data types and parameters appear, they cannot be dynamically added, lacking good scalability;

[0007] (3) There are many data types in the standard example, with more than a dozen common types. When storing example data, the preset parameter fields of each data type table will have a large number of empty parameters, wasting storage space.

[0008] (4) Due to the differences in parameters of different calculation cases, the empty parameters are unclear, and the data query function needs to add multiple judgments, which affects the query performance. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and database for storing CFD verification and validation standard model data. This method can dynamically store incoming state data and result data of different standard examples, reduce data redundancy, improve data scalability, and ensure that the database platform can accurately and efficiently provide data services for CFD software credibility evaluation or related research.

[0010] The objective of this invention is achieved through the following solution:

[0011] A method for storing CFD verification and validation model data includes the following steps:

[0012] CFD verification and confirmation of standard model data entry;

[0013] Next, the basic information of the standard case is extracted, and the structural data of the case experiment / calculation results is parsed and organized to design and form a CFD verification and validation standard case data table. The CFD verification and validation standard case data table includes a core data table. A standard parameter table is designed in the core data table structure to store and manage the incoming flow status and result parameters of all cases. The parameter names and parameter identifiers are limited by standard specifications and are unique. The standard parameter table is associated with the flow status table and the result data table through a parameter mapping table. The parameter mapping table serves as an intermediate table to store fields. The fields include parameter types, which determine whether the parameter is a state parameter or a result parameter of a data type. If it is a state parameter, it is associated with the flow status table; if it is a result parameter of a data type, it is associated with the result data table. The flow status data and result data are dynamically stored. In the flow status table, in addition to the fixed fields that exist in each case, the remaining fields are dynamically represented by parameter codes. The mapping table is used to determine which parameter the state field specifically represents. Similarly, in the result data table, in addition to the fixed fields, the remaining fields are also dynamically represented by parameter codes. The specific meaning of the parameters is obtained by referring to the standard parameter table through the parameter codes.

[0014] The entered standard model data is stored according to the CFD verification and confirmation standard model data table formed by the design.

[0015] Furthermore, the CFD verification and confirmation of the standard model data entry includes the following sub-steps: standardizing and organizing all the entered standard model data according to 10 elements, specifically formatting the standard model case as the basic unit; wherein, the entire standard model case file includes subfolders for storing different types of files and a case analysis data table; the case analysis data table is formed by parsing and organizing the case information and data content of the subfolders storing different types of files into the standard model data entry template, which is used for database uploading.

[0016] Furthermore, the naming format of the example analysis data table is "example name_analysis data table", the file format is .xlsx, and the table stores the standard model information, example information, experimental / calculation result data information, experimental / calculation result status data information, and result data of different data types in a hierarchical manner through the sheet table. All data are associated through the table name and the parameters stored in the table, and the overall structure matches the database data structure.

[0017] Furthermore, the subfolders used to store different types of files include nine standard model example element folders;

[0018] The first standard model example element folder is used to store the calculation result files of the standard model example;

[0019] The second standard case element folder is used to store the test data files of the standard case.

[0020] The third standard model example element folder is used to store example description files;

[0021] The fourth standard model example element folder is used to store the numerical model files of the standard model examples;

[0022] The fifth standard model example element folder contains the structured and unstructured mesh files for the standard model example simulation calculations;

[0023] The sixth standard model case element folder is used to store the input parameter files corresponding to the parameters related to the case status;

[0024] The seventh standard model case element folder is used to store images describing the standard model case information;

[0025] The eighth standard model example element folder is used to store references;

[0026] The ninth standard model example folder is used to store solvers and data processing tools.

[0027] Furthermore, the CFD verification and validation benchmark data table also includes a framework control table, a metadata table, a quality control management table, a system management table, and a basic information table.

[0028] Furthermore, the fields stored in the parameter mapping table also include standard parameter serial number, parameter code, and example data serial number.

[0029] Furthermore, the state parameters include Mach number, total temperature and total pressure; the data types include aerodynamic forces and heat flux.

[0030] When the parameter type value is the first identifier set, it indicates that the parameter is a state parameter and is associated with the flow state table. The first identifier is a unique identifier. When the parameter type value is the second identifier set, it indicates that the parameter is a result parameter and is associated with the result data table. The second identifier is a non-unique identifier, and there are multiple of them, which are used to correspond to result parameters of different data types. The result parameters include aerodynamic result parameters and thermal flow result parameters.

[0031] Furthermore, the fixed fields in the flow state table include state number, data type, and source information, while the remaining fields in the flow state table include Mach number, Reynolds number, total temperature, and total pressure.

[0032] Furthermore, the fixed fields in the results data table include the result sequence number and the state sequence number, while the remaining fields in the results data table include the lift coefficient, drag coefficient, pressure coefficient, and velocity field.

[0033] A database for CFD verification and validation of model data, used to perform the storage method described above.

[0034] The beneficial effects of this invention include:

[0035] For CFD verification and validation standard case data with complex structures, high dimensionality, and variable parameters, the storage method of this invention designs and applies a flexible data structure to dynamically store incoming status data and result data of different standard cases, reducing data redundancy and improving data scalability. Based on this data structure, the storage method can complete the design of standard case data quality inspection and metadata management, ensuring that the database platform can accurately and efficiently provide data services for CFD software credibility evaluation or related research. Application results demonstrate that the verification and validation database platform of this invention achieves effective management and efficient application of standard case data, providing strong support for the verification and validation of national numerical wind tunnel projects and related domestic CFD software. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart illustrating the overall process of data storage method and data structure design for CFD verification and validation of the standard model in this embodiment of the invention.

[0038] Figure 2 This is for verifying and confirming the data elements of the standard simulation example in the embodiments of the present invention;

[0039] Figure 3 This is the design of the parsed data table structure in the embodiments of the present invention;

[0040] Figure 4 This is the core data table for the example in this embodiment of the invention;

[0041] Figure 5 This is a standard parameter structure design in the embodiments of the present invention;

[0042] Figure 6 In this embodiment of the invention, all newly added parameters are directly extended through the interface;

[0043] Figure 7 This is a diagram illustrating the data entry and storage behavior in an embodiment of the present invention.

[0044] Figure 8 This is a schematic diagram of the metadata management structure in an embodiment of the present invention;

[0045] Figure 9 This is a metadata spectrum illustration of the DLR-F11 example in an embodiment of the present invention;

[0046] Figure 10 This is a list of metadata for the DLR-F11 example in an embodiment of the present invention.

[0047] Figure 11 This is the CFD verification and validation database functional structure in this embodiment of the invention;

[0048] Figure 12 This is the data quality inspection process for the standard simulation examples in this embodiment of the invention. Detailed Implementation

[0049] All features disclosed in all embodiments of this specification, or steps in all methods or processes implied in the disclosure, may be combined and / or extended or replaced in any way, except for mutually exclusive features and / or steps.

[0050] To address the technical problems mentioned in the background, embodiments of the present invention provide the following technical solutions:

[0051] For CFD verification and validation standard case data with complex structures, high dimensionality, and variable parameters, the invention proposes a standard storage format based on 10 elements. For structured data, a flexible data structure is also designed to dynamically store incoming status data and result data from different standard cases, reducing data redundancy and improving data scalability. Based on the designed flexible data structure, data quality inspection and metadata management of the standard case results can be completed, ensuring that the database platform can accurately and efficiently provide data services for CFD software credibility evaluation or related research.

[0052] In further implementation, Figure 1 The overall process of CFD verification and validation of the standard model data storage method and data structure design in the embodiments of the present invention includes the following steps:

[0053] Step 1: Standardization of CFD Validation and Validation Standard Model Data. In practice, the CFD validation and validation standard model data consists of screened and organized high-reliability and representative standard model experiments, numerical calculations, and exact solutions. This data is used to determine the reliability of the CFD software and for related aerodynamic science research. The validation and validation standard model data is large in volume, and its storage, management, and exchange are relatively complex. Therefore, the main data to be stored should be structured, standardized, and normalized as much as possible. In this invention, all stored standard model data is formatted and organized according to 10 elements. The standard model data is stored in units of calculation examples. The entire standard model calculation example file contains 9 subfolders for storing different types of files and 1 calculation example analysis data table, such as... Figure 2 As shown. The nine subfolders for storing different file types are named: Computational, Experimental, Description, Geometries, Grid, Input, Picture, Reference, and Utilities.

[0054] The Computational folder stores the calculation results files for the standard model examples, including highly recognized and accurate numerical calculation results (including analytical solutions). The file naming format is "example name_cal_data type_mesh type", with data types including force, torque, pressure distribution, friction distribution, velocity type, etc., and mesh types being structured (str) and unstructured (unstr). The file format is .dat. The Experimental folder stores the experimental data files for the standard model examples, with the file naming format "example name_exp_data type" and the file format being .dat. The Description folder stores the example description files. The example description file details the source, purpose, and experimental information of the standard model case, as well as the geometric description, mesh description, computational state parameters, boundary conditions, comparative reference data, and references. The file name format is "Case Name_Case Description", and the file format is .doc. The Geometries folder is used to store the numerical model files of the standard model case. The numerical model files are geometric files that describe the shape of the standard model. The file format is .iges or .tin. The Grid folder is used to store the structured and unstructured mesh files of the standard model case simulation calculation. The file name format is "Case Name_str / unstr", and the file format is .cgns or plot3D. The mesh folder also includes a "Basic Information File for Case Study.txt" file, which mainly describes information such as reference length, mesh quantity, and boundary layer height. The Input folder stores input parameter files corresponding to parameters related to the case study status, with a fixed filename and format: input.para. The Picture folder stores images describing the standard case study information, including experimental diagrams, simulation diagrams, and mesh diagrams, in .jpg or .png format. The Reference folder stores references in PDF format. The Utilities folder stores solvers, data processing tools, etc. The parsed data table is formed by parsing and organizing the case study information and data content from the above folders into the standard case study data import template. It is used for database upload. The parsed data table is named "Case Study Name_Parsed Data Table" and is in .xlsx format. It stores standard case information, case study information, experimental / calculation result data, experimental / calculation result status data, and result data of different data types in a hierarchical manner through sheets. All data are associated through table names and parameters stored in the tables, which matches the overall database data structure and can appropriately improve the parsing and import speed of case study data. Each sheet has a fixed naming convention, as follows: Figure 3 As shown.

[0055] Step 2, Data Structure Design. In practical implementation, a good data structure can greatly improve the performance of data retrieval, insertion, and deletion operations. The database platform's data structure design must meet the following requirements: application scenario needs such as CFD software credibility evaluation; separation of the main and auxiliary computational tasks; appropriate data redundancy; and the ability to handle potential new requirements and subsequent large data volumes.

[0056] In view of the above considerations, the verification and validation database tables designed in this invention include several major categories such as core data tables, framework control tables, metadata tables, quality control management tables, system management tables, and basic information tables. All standard case study data is stored in the core data tables. The core data table structure is centered around the case study information table, logically linking it to case study data type tables, case study result data tables, standard model information tables, file information tables, etc., as illustrated in the diagram below. Figure 4 As shown.

[0057] The data structure of validation and verification standard cases is complex. The parameter structures for different data types within the same case, or even for the same data type across different cases, vary significantly, especially between steady and unsteady cases. To address this, traditional aerodynamic databases typically use separate tables for different data types, pre-setting all incoming flow states and result parameter fields for each data type. Aerodynamic data is then entered by matching field names and storing it in the corresponding location, with default fields left empty. This data structure design has several significant drawbacks:

[0058] 1) Although the incoming flow state parameters of different data types in the same calculation case are different, they largely overlap, resulting in data redundancy in the table;

[0059] 2) Pre-setting data type tables and parameter fields can satisfy the storage of existing types and parameters, but it cannot dynamically add new data types and parameters when new experiments or calculations occur, lacking good scalability;

[0060] 3) There are many data types in the standard example, with more than a dozen common types. When storing example data, the preset parameter fields of each data type table will have a large number of empty parameters, wasting storage space.

[0061] 4) Due to the differences in parameters between different calculation cases, the null parameters are unclear, and the data query function needs to add multiple judgments, which affects the query performance.

[0062] To address the aforementioned shortcomings, this invention designs a novel data structure applicable to verification and validation database platforms. It employs a more flexible dynamic storage method to construct the flow status table and result data table, the structure and parameter settings of which are as follows: Figure 5 As shown.

[0063] This invention designs a standard parameter table to store and manage the incoming flow state and result parameters for all calculation examples. Parameter names and identifiers are uniquely defined by standard specifications. The standard parameter table is associated with the flow state table and result data table through a parameter mapping table. The parameter mapping table, as an intermediate table, stores fields such as standard parameter serial number, parameter code (COL1, COL2, etc.), calculation example data serial number, and parameter type. The parameter type determines whether the parameter is a state parameter such as Mach number, total temperature, or total pressure, or a result parameter of data type such as aerodynamics or heat flux. Specifically, when the parameter type value is "state," it indicates that the parameter is a state parameter and is associated with the flow state table; when the parameter type value is "force," it indicates that the parameter is an aerodynamic result parameter; and when the value is "heat," it indicates that the parameter is a heat flux result parameter and is associated with the result data table. Flow state data and result data are stored dynamically. In the flow state table, in addition to fixed fields such as state number, data type, and source information that exist for each calculation case, other fields such as Mach number, Reynolds number, total temperature, and total pressure are dynamically represented by parameter codes such as COL1, COL2, etc. The specific parameter represented by each state field is determined by mapping it to the standard parameter table. Similarly, in the result data table, in addition to the result number and state number fields, other fields such as lift coefficient, drag coefficient, pressure coefficient, and velocity are also dynamically represented by parameter codes such as COL1, COL2, etc. The specific meaning of these parameters is obtained by mapping them to the standard parameter table.

[0064] The above method strikes a suitable balance between data redundancy and processing speed, resolving the problem of aerodynamic data redundancy. When data types or parameters in a calculation need to be added, modified, or deleted, this can be done through the basic information management interface, such as... Figure 6 Maintain the standard parameter table and data type table, and flexibly and conveniently add parameters to ensure that the data structure has good scalability.

[0065] Under the above-described inventive concept, the design of each table in the embodiments of the present invention is explained as follows:

[0066] 1) Standard Model Table (T_CASE_MODEL)

[0067] Serial Number Field Name Field meaning Data types 1 MODEL_NAME Standard Model Name String 2 MODEL_DESC Standard Model Description Text 3 INSTRUCTION illustrate Text 4 createDate Creation Date String

[0068] 2) Case Study Table (T_CASE)

[0069]

[0070]

[0071] 3) Case Study Data Table (T_CASE_DATA)

[0072] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 REF_AREA Reference area Double 3 REF_LEN_VER Reference length (vertical) String 4 REF_LEN_HOR Reference length (horizontal) String 5 X Torque reference point X Double 6 Y Torque reference point Y Double 7 Z Torque reference point Z Double 8 INSTRUCTION illustrate Text 9 OBJECT object String 10 OBJECT_EN ObjectEN String 11 TEST_MEDIA Test medium String 12 QUALITY quality String 13 IXX Moment of inertia IXX String 14 IYY Moment of inertia IYY String 15 IZZ Moment of inertia IZZ String 16 ORIGIN source String 17 SOURCE_INFO Source information String 18 SOURCE Data source String 19 MODEL Half-mold / Full-mold String 20 UNIT Geometric units String

[0073] 4) Data type table (T_CASE_TEST_TYPE)

[0074]

[0075]

[0076] 5) Flow Status Table (T_CASE_STATE_FLOW)

[0077]

[0078] 6) Results Data Table (T_CASE_RESULT_DATA)

[0079]

[0080]

[0081] 7) Standard Parameter Table (T_STANDARD_PARAM)

[0082] Serial Number Field Name Field meaning Data types 1 NAME Parameter name String 2 CODE Parameter code String 3 NOTE Remark String 4 DATATYPE Data types String

[0083] 8) Parameter mapping table (T_PARAM_MAPPING)

[0084]

[0085] 9) File table (T_CASE_FILE)

[0086] All FILE type fields store file information in the CWM_FILE table. The format of the FILE field is: [{"id":"FILEID","name":"file name","fileType":"C_File"}], where FILEID is the FILEID in the CWM_FILE table.

[0087]

[0088]

[0089] 10) File type table (T_CASE_FILE_TYPE)

[0090] Serial Number Field Name Field meaning Data types 1 TYPE_NAME Type Name String 2 INSTRUCTION illustrate String

[0091] 11) File Category Table (T_CASE_FILE_CATEG)

[0092] Serial Number Field Name Field meaning Data types 1 CATEG_NAME Category Name String 2 INSTRUCTION illustrate String

[0093] 12) Calculation result file table (T_CASE_FILE_RESULT)

[0094] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 FILE_NAME File Name File 3 FILE_SIZ File size (KB) String 4 CREATOR Creator String 5 CREAT_TIME Creation time DateTime 6 REMARK Remark Text 7 CATEG_ID File Category String 8 TYPE_ID File type String

[0095] 13) Test Result File Table (T_CASE_FILE_TEST_RESULT)

[0096] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 FILE_NAME File Name File 3 FILE_SIZE File size (KB) String 4 CREATOR Creator String 5 CREAT_TIME Creation time DateTime 6 REMARK Remark Text 7 CATEG_ID File Category String 8 TYPE_ID File type String

[0097] 14) Geometry File Information Table (T_CASE_FILE_GEOM)

[0098]

[0099]

[0100] 15) Grid file information table (T_CASE_FILE_GRID)

[0101] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 GRID_SOURCE Grid source String 3 TOPOLOGY Topology String 4 DISTR_CHARACTER Distribution characteristics String 5 GRID_DIM Grid Dimension String 6 GRID_SCALE Grid size String 7 GRID_TYPE Grid type String 8 GRID_FIEL_FORMAT Grid file format String 9 GRID_DESC describe Text 10 FILE_NAME File Name File 11 FILE_SIZE File size (KB) String 12 CREATOR Creator String 13 CREAT_TIME Creation time DateTime 14 REMARK Remark Text 15 CATEG_ID File Category String 16 TYPE_ID File type String

[0102] 16) Control input file (T_CASE_FILE_INPUT)

[0103] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 FILE_NAME File Name File 3 FILE_SIZE File size (KB) String 4 CREATOR Creator String 5 CREAT_TIME Creation time DateTime 6 REMARK Remark Text 7 CATEG_ID File Category String 8 TYPE_ID File type String

[0104] 17) References List (T_CASE_FILE_REFS)

[0105]

[0106]

[0107] 18) Specialized Tools Table (T_CASE_FILE_UTILITIES)

[0108] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 FILE_NAME File Name File 3 FILE_SIZE File size (KB) String 4 CREATOR Creator String 5 CREATE_TIME Creation time DateTime 6 REMARK Remark String 7 GATEG_ID File Category String 8 TYPE_ID File type String

[0109] 19) Case description file (T_CASE_FILE_DESCRIPTION)

[0110] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 FILE_NAME File Name File 3 FILE_SIZE File size (KB) String 4 CREATOR Creator String 5 CREAT_TIME Creation time DateTime 6 REMARK Remark Text 7 CATEG_ID File Category String 8 TYPE_ID File type String

[0111] 20) Case study image file table (T_CASE_FILE_IMAGE)

[0112] Serial Number Field Name Field meaning Data types 1 T_CASE_241_ID Case ID, associated case table 2 CREATOR Creator String 3 CREATE_TIIME Creation time DateTime 4 REMARK Remark Text 5 FILE_NAME File Name File 6 FILE_SIZE File size (KB) String 7 CATEG_ID File Category String 8 TYPE_ID File type String

[0113] 21) Tag Map (T_CASE_LABEL_MAP)

[0114] Serial Number Field Name Field meaning Data types 1 T_CASE_CATEG_241_ID Category ID, associated category table String 2 T_CASE_LABEL_241_ID Tag ID, associated tag table String

[0115] 22) Label table (T_CASE_LABEL)

[0116] Serial Number Field Name Field meaning Data types 1 T_CASE_CATEG_241_ID Category ID, associated category table String 2 LABEL_NAME Label Name String 3 INSTRUCTION illustrate String

[0117] Step 3: Input and store example data

[0118] There are two main methods for verifying and confirming the import of standard case studies. The first method involves directly importing the case study compressed package, which automatically creates all information and relationships for the case study. This method is simple and convenient, and is mainly used for importing all information for a single case study at once. The second method involves manually creating the case study information and then importing each data file separately. This method is relatively complex and is mainly used for adding or replacing parts of files or data from an already imported case study. Case study data entry behavior is as follows: Figure 7 As shown.

[0119] To comprehensively, objectively, and scientifically evaluate the reliability of CFD simulations of different flow phenomena, representative standard examples are needed for each type of flow phenomenon. Furthermore, to facilitate retrieval and organize interface data formats, each example needs to be categorized and labeled accordingly. The front-end interface can quickly locate specific examples through label filtering; therefore, the example label data structure design needs to be relatively flexible and easily expandable. A label classification table and a label table are used to manage specific label types and content, and a label mapping table associates label values ​​with specific examples.

[0120] The case study labels are mainly divided into navigation labels and retrieval labels. Navigation labels are mainly classified in three aspects: velocity range, basic flow characteristics, and engineering applications. Retrieval labels are classified according to verification and validation evaluation indicators, such as data source, time domain attributes, data type, aerodynamic characteristics, and model type. The specific classification is shown in Table 1.

[0121] Table 1. Classification of Examples

[0122]

[0123]

[0124] In an optional implementation, the following steps are also included:

[0125] Step 4, Standard Case Data Quality Inspection

[0126] High-quality standard cases are the foundation for CFD software verification and validation, and can be directly used for CFD software reliability assessment. The standard cases stored in the verification and validation database are recognized as having high-quality experimental or computational data. To ensure the quality of data in the platform's database and reduce errors, duplications, and useless data caused by human factors, data quality checks are required for both newly added and historical cases. Through data quality checks, hidden data quality issues in the storage, management, and application of standard cases can be promptly identified, located, and resolved. Problematic data can be transferred and processed, and data quality can be evaluated and monitored. This continuous improvement in standard case data quality management effectively enhances the efficiency and reliability of the verification and validation database construction.

[0127] The key to data quality inspection lies in determining the quality inspection model, rules, and plan. Standard case data quality inspection involves configuring the data source and establishing a data quality inspection model. Quality inspection rules are set according to CFD data standards, and weights are assigned to the rules based on specific quality inspection content to form a quality inspection plan. The quality inspection plan is executed, and the corresponding results are analyzed to generate a quality inspection report. This automates the detection of the core data correctness of the case. The simplified process includes quality inspection rule management, quality inspection plan management, quality inspection analysis, and quality inspection statistics, such as... Figure 12 As shown.

[0128] The data quality inspection function includes data source management, quality inspection rule management, quality inspection template management, quality inspection plan management, quality inspection analysis, quality inspection statistics, and task execution records. It obtains the core data table of the computational example by configuring the data source and directly verifies the parameter values ​​in the database table. In existing technologies where tables are created separately for different data types, the same parameter values ​​in all data type tables are repeatedly checked during the quality inspection of historical computational example data already in the database, increasing the difficulty of implementing the quality inspection function and increasing the detection time. However, based on the technical solution of this invention, all parameters and parameter values ​​only involve the data type table, standard parameter table, flow status table, and result data table, which is very user-friendly for the implementation of the quality inspection function, reducing quality inspection time and accelerating error point location.

[0129] In an optional implementation, the following steps are also included:

[0130] Step 5, Standard Model Pneumatic Metadata Management

[0131] The metadata for a calculation case is metadata that describes aerodynamic data. The metadata management function is implemented based on the technical solution of this invention. By configuring information such as the database IP address, port, user, and password, it directly retrieves the data structure information of a specific calculation case from the database table, enabling intuitive and efficient querying and analysis of the calculation case data structure. The metadata management module includes a metadata information table, a metadata node table, a connection information table, and a calculation case table, and their entity relationships are as follows: Figure 8 As shown.

[0132] The core function of metadata management is to provide macro-level data information for computational examples. The platform's metadata management intuitively displays information such as the standard model to which the computational example belongs, basic information about the example, data information, data types, flow state parameters, and result parameters in a list or graph format. Figure 9 , Figure 10 As shown.

[0133] Verification and validation standard examples involve diverse data types and complex, variable parameters. Existing data structures often result in data redundancy and wasted storage space. The technical solution of this invention addresses the issue of variable parameters in standard examples, providing a flexible and easily manageable data structure for incoming flow status and result data. This structure dynamically manages aerodynamic parameters, reduces data redundancy, and ensures unlimited scalability in data structure management for aerodynamic data types and parameters.

[0134] Verification of the technical effects of this invention:

[0135] The technology of this invention can be practically applied to the construction of verification and validation database platforms, achieving good results. The verification and validation database platform constructed using this invention is a shared database established based on the national numerical wind tunnel engineering verification and validation standard system, and has functions such as data entry, data management, data application, online document display, data quality inspection, metadata management, system management, and interface management. Data entry provides standardized entry of basic information, results data, and related documents for computational examples. During data entry, validation rules are invoked for data verification and approval to ensure accuracy. Data management offers management of standard models, tags, standard parameters, data types, velocity domains, engineering applications, and basic flow characteristics, enabling categorized, hierarchical management, maintenance, and expansion of computational examples. Data application provides functions such as browsing, querying, downloading, analysis, and plotting computational examples. Online file display provides online previews of numerical model files, text files, office documents, images, and audio / video files. Data quality inspection provides quality inspection rules and develops specific quality inspection plans for data management and applications, enabling batch data quality inspection. Metadata management provides definitions and descriptions of database platform objects and data structures. System management provides user management, permission management, log management, and maintenance functions such as data cleanup and backup. Interface management provides interfaces for the CFD software credibility evaluation platform and automated testing platform, enabling cross-platform querying and automatic extraction of standard computational example data. The specific functional structure is as follows: Figure 11 As shown.

[0136] The database platform of this invention can centrally store and manage hundreds of typical domestic and foreign standard model calculation examples, such as DLR-F6, HB-2, CT-1 high angle of attack standard model, and CHN-T1 standard model, as well as 69 accurate solution examples. It covers more than a dozen aerodynamic data types, including aerodynamics, pressure distribution, heat flux, dynamic derivative, and deformation, as well as various basic flow characteristic problems such as attached flow, separated flow, and free shear flow, and typical engineering applications such as high aspect ratio aircraft, low aspect ratio aircraft, and multibody separation. It achieves full life cycle coverage of standard models for verification and validation.

[0137] It should be noted that, within the scope of protection defined in the claims of this invention, the following embodiments can be combined and / or extended or replaced in any logical manner from the above specific embodiments, such as the disclosed technical principles, disclosed technical features or implicitly disclosed technical features.

[0138] Example 1

[0139] A method for storing CFD verification and validation model data includes the following steps:

[0140] CFD verification and confirmation of standard model data entry;

[0141] Next, the basic information of the standard case is extracted, and the structural data of the case experiment / calculation results is parsed and organized to design and form a CFD verification and validation standard case data table. The CFD verification and validation standard case data table includes a core data table. A standard parameter table is designed in the core data table structure to store and manage the incoming flow status and result parameters of all cases. The parameter names and parameter identifiers are limited by standard specifications and are unique. The standard parameter table is associated with the flow status table and the result data table through a parameter mapping table. The parameter mapping table serves as an intermediate table to store fields. The fields include parameter types, which determine whether the parameter is a state parameter or a result parameter of a data type. If it is a state parameter, it is associated with the flow status table; if it is a result parameter of a data type, it is associated with the result data table. The flow status data and result data are dynamically stored. In the flow status table, in addition to the fixed fields that exist in each case, the remaining fields are dynamically represented by parameter codes. The mapping table is used to determine which parameter the state field specifically represents. Similarly, in the result data table, in addition to the fixed fields, the remaining fields are also dynamically represented by parameter codes. The specific meaning of the parameters is obtained by referring to the standard parameter table through the parameter codes.

[0142] The entered standard model data is stored according to the CFD verification and confirmation standard model data table formed by the design.

[0143] Example 2

[0144] Based on Example 1, the CFD verification and confirmation of the standard model data entry includes the following sub-steps: standardizing and organizing all the standard model data into the database according to 10 elements, specifically using the standard model case as the basic unit for formatting; wherein, the entire standard model case file includes subfolders for storing different types of files and a case analysis data table; the case analysis data table is formed by parsing and organizing the case information and data content of the subfolders storing different types of files into the standard model data entry template, and is used for database uploading.

[0145] Example 3

[0146] Based on Example 2, the naming format of the example analysis data table is "example name_analysis data table", the file format is .xlsx, and the table stores the standard model information, example information, experimental / calculation result data information, experimental / calculation result status data information, and result data of different data types in a hierarchical manner through the sheet table. All data are associated through the table name and the parameters stored in the table, and the overall structure matches the database data structure.

[0147] Example 4

[0148] Based on Example 2, the subfolders used to store different types of files include 9 standard model example element folders;

[0149] The first standard model example element folder is used to store the calculation result files of the standard model example;

[0150] The second standard case element folder is used to store the test data files of the standard case.

[0151] The third standard model example element folder is used to store example description files;

[0152] The fourth standard model example element folder is used to store the numerical model files of the standard model examples;

[0153] The fifth standard model example element folder contains the structured and unstructured mesh files for the standard model example simulation calculations;

[0154] The sixth standard model case element folder is used to store the input parameter files corresponding to the parameters related to the case status;

[0155] The seventh standard model case element folder is used to store images describing the standard model case information;

[0156] The eighth standard model example element folder is used to store references;

[0157] The ninth standard model example folder is used to store solvers and data processing tools.

[0158] Example 5

[0159] Based on Example 1, the CFD verification and validation benchmark data table also includes a framework control table, a metadata table, a quality control management table, a system management table, and a basic information table.

[0160] Example 6

[0161] Based on Example 1, the fields stored in the parameter mapping table also include standard parameter serial number, parameter code, and example data serial number.

[0162] Example 7

[0163] Based on Example 1, the state parameters include Mach number, total temperature and total pressure; the data types include aerodynamic forces and heat flux.

[0164] When the parameter type value is the first identifier set, it indicates that the parameter is a state parameter and is associated with the flow state table. The first identifier is a unique identifier. When the parameter type value is the second identifier set, it indicates that the parameter is a result parameter and is associated with the result data table. The second identifier is a non-unique identifier, and there are multiple of them, which are used to correspond to result parameters of different data types. The result parameters include aerodynamic result parameters and thermal flow result parameters.

[0165] Example 8

[0166] Based on Example 1, the fixed fields in the flow state table include state number, data type and source information, while the remaining fields in the flow state table include Mach number, Reynolds number, total temperature and total pressure.

[0167] Example 9

[0168] Based on Example 1, the fixed fields in the result data table include the result number and the state number, while the remaining fields in the result data table include the lift coefficient, drag coefficient, pressure coefficient, and velocity field.

[0169] Example 10

[0170] A database for CFD verification and validation of standard model data, used to perform the storage method as described in any of Examples 1 to 9.

[0171] The units described in the embodiments of the present invention can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0172] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0173] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

Claims

1. A method for storing CFD verification and validation model data, characterized in that, Includes the following steps: CFD verification and confirmation of standard model data entry; Then, extract the basic information of the standard case, analyze and organize the structural data of the case test / calculation results, and design and form a CFD verification and validation standard case data table; The CFD verification and validation benchmark data table includes a core data table. Within this core data table structure, a standard parameter table is designed to store and manage the incoming flow status and result parameters for all computational examples. Parameter names and identifiers are uniquely defined by standard specifications. The standard parameter table is associated with the flow status table and result data table through a parameter mapping table. The parameter mapping table serves as an intermediate table for storing fields. Each field includes a parameter type, which determines whether the parameter is a status parameter or a result parameter of a data type. If it is a status parameter, it is associated with the flow status table; if it is a result parameter of a data type, it is associated with the result data table. Flow status data and result data are dynamically stored. In the flow status table, in addition to fixed fields present in every computational example, the remaining fields are dynamically represented using parameter codes. The mapping table is used to determine which parameter each status field represents in the standard parameter table. Similarly, in the result data table, in addition to fixed fields, the remaining fields are also dynamically represented using parameter codes. The specific meaning of each parameter is obtained by referencing the standard parameter table using the parameter code. The state parameters include Mach number, total temperature and total pressure; the data types include aerodynamic forces and heat flux; when the parameter type value is a set first identifier, it indicates that the parameter is a state parameter and is associated with the flow state table, where the first identifier is a unique identifier; when the parameter type value is a set second identifier, it indicates that the parameter is a result parameter and is associated with the result data table, where the second identifier is a non-unique identifier, and there are multiple identifiers to correspond to result parameters of different data types, including aerodynamic result parameters and heat flux result parameters; The fixed fields in the flow state table include state number, data type, and source information. The remaining fields in the flow state table include Mach number, Reynolds number, total temperature, and total pressure. The fixed fields in the results data table include the result number and the status number. The remaining fields in the results data table include the lift coefficient, drag coefficient, pressure coefficient, and velocity field. The entered standard model data is stored according to the CFD verification and confirmation standard model data table formed by the design.

2. The method for storing CFD verification and validation model data according to claim 1, characterized in that, The CFD verification and confirmation of the standard model data entry includes the following sub-steps: standardizing all the standard model data according to 10 elements, specifically formatting the standard model case as the basic unit; wherein, the entire standard model case file includes subfolders for storing different types of files and a case analysis data table; the case analysis data table is formed by parsing and organizing the case information and data content of the subfolders storing different types of files into the standard model data entry template, which is used for database upload.

3. The method for storing CFD verification and validation model data according to claim 2, characterized in that, The naming format of the example analysis data table is "example name_analysis data table", and the file format is .xlsx. It stores the standard model information, example information, experimental / calculation result data information, experimental / calculation result status data information, and result data of different data types in a hierarchical manner through sheets. All data are associated through the table name and the parameters stored in the table, and the overall structure matches the database data structure.

4. The method for storing CFD verification and validation model data according to claim 2, characterized in that, The subfolders used to store different types of files include 9 standard model example element folders; The first standard model example element folder is used to store the calculation result files of the standard model example; The second standard case element folder is used to store the test data files of the standard case. The third standard model example element folder is used to store example description files; The fourth standard model example element folder is used to store the numerical model files of the standard model examples; The fifth standard model example element folder contains the structured and unstructured mesh files for the standard model example simulation calculations; The sixth standard model case element folder is used to store the input parameter files corresponding to the parameters related to the case status; The seventh standard model case element folder is used to store images describing the standard model case information; The eighth standard model example element folder is used to store references; The ninth standard model example folder is used to store solvers and data processing tools.

5. The method for storing CFD verification and validation model data according to claim 1, characterized in that, The CFD verification and validation benchmark data table also includes a framework control table, a metadata table, a quality control management table, a system management table, and a basic information table.

6. The method for storing CFD verification and validation model data according to claim 1, characterized in that, The fields stored in the parameter mapping table also include standard parameter serial number, parameter code, and example data serial number.

7. A database for CFD verification and validation of standard model data, characterized in that, Used to perform the storage method as described in any one of claims 1 to 6.

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