A data processing method and system for a metal material simulation database

Abstract

This invention provides a data processing method and system for a metal material simulation database, relating to the field of computer simulation technology. The method specifically includes: constructing a multi-dimensional metal material simulation data model based on metadata; receiving raw metal material simulation data from multiple heterogeneous data sources, sequentially parsing each piece of raw metal material simulation data, identifying and extracting the material parameters of the raw metal material simulation data; mapping the material parameters to predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data; generating a unique traceability code for each piece of structured metal material simulation data, and entering the structured metal material simulation data into the metal material simulation database based on the generated traceability code. This invention improves the accuracy and standardization of metal material simulation data entry in business operations by establishing a structured form format for materials required in different simulation fields.

Description

Technical Field

[0001] This invention relates to the field of computer simulation technology, and in particular to a data processing method and system for a metal material simulation database. Background Technology

[0002] The validity of a materials database necessitates the support of its internal data. For metallic materials simulation involving multiple software programs and application areas (such as microstructure simulation and physical simulation), efficient and accurate data entry is crucial for subsequent use. A well-designed database form not only ensures standardized data entry but also defines actual data requirements, preventing invalid data from entering. Therefore, from the perspective of materials data organization and management, the form construction approach should be clarified from the following aspects:

[0003] First, the datasets involved in different material types and application scenarios should be clearly defined. Second, it should be determined which data is related to the specific material type and which data remains unchanged regardless of the material type. Third, the specific classification of the data should be clearly defined, such as equation-based, single-point, and image-based datasets. Fourth, the influence of temperature on material data changes should be clearly defined; for example, Poisson's ratio changes with temperature. Furthermore, due to the anisotropic nature of some metallic materials, exhibiting different properties in different directions, this data adds an additional dimension to the form design. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, this invention proposes a design method for a data form in a metal material simulation database by establishing a structured form format for materials required in different simulation fields. This method aims to standardize the entry of data required in actual business operations.

[0005] On the one hand, this invention proposes a data processing method for a metal material simulation database, which includes the following steps:

[0006] Constructing a multi-dimensional simulation data model for metallic materials based on metadata;

[0007] Receive raw metallic material simulation data from multiple heterogeneous data sources;

[0008] Based on the multi-dimensional metal material simulation data model, each piece of original metal material simulation data is analyzed in sequence to identify and extract the material parameters of the original metal material simulation data.

[0009] The material parameters are mapped to the predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data.

[0010] A unique traceability code is generated for each structured metal material simulation data, and the structured metal material simulation data is entered into the metal material simulation database based on the generated traceability code.

[0011] Furthermore, the specific content of constructing a multi-dimensional metal material simulation data model based on metadata is as follows:

[0012] A parameter semantic dictionary is constructed to predefine the metadata of each material parameter in the simulation data of metallic materials; the metadata includes at least: a unique identifier for the parameter and a data tag for declaring the data type to which the material parameter belongs; the data tag includes at least: mathematical equation, single-point value, temperature sequence and image;

[0013] Establish a multi-level classification structure for simulation data of metallic materials;

[0014] A dynamic mapping rule library is constructed to store the mapping rules that associate different classification dimensions in the multi-level classification structure with the parameter semantic dictionary.

[0015] Furthermore, the first level of the multi-level classification structure is the material category, which is used to distinguish sets of materials with different performance characteristics;

[0016] The second level of the multi-level classification structure is the material grade, which is used to distinguish materials with specific chemical compositions and basic mechanical properties according to national standards, industry standards or enterprise standards.

[0017] The third level of the multi-level classification structure is the parameter type, which is used to group material parameters belonging to the same material grade according to the physical nature of the metal material simulation data;

[0018] The parameter types include, but are not limited to: general physical parameters, thermophysical parameters, plasticity parameters, and microstructure parameters; wherein the general physical parameters are parameters used to describe the basic physical properties of materials; the thermophysical parameters are parameters used to describe the thermal behavior of materials; and the plasticity parameters are parameters used to describe the plastic behavior of materials; and in the multi-level classification structure, the next level of the general physical parameters, thermophysical parameters, and plasticity parameters is associated with a parameter set; the parameter set contains the data entities and data input interfaces for all material parameters under that type of parameter;

[0019] The organization parameters are parameters used to describe the microstructure characteristics of materials; and in the multi-level classification structure, the next level of the organization parameters is the product form.

[0020] The next level after the product form is the application scenario, which is used to identify the specific process in which the material is processed; and the next level after the application scenario is associated with a set of parameters.

[0021] Furthermore, the mapping rule is: a mapping relationship from the combination of dimensions such as material category, material grade, parameter type, product form and application scenario in the multi-level classification structure to the set of unique parameter identifiers in the parameter semantic dictionary.

[0022] Furthermore, based on the multi-dimensional metal material simulation data model, each original metal material simulation data is sequentially analyzed to identify and extract the specific content of the material parameters of the original metal material simulation data:

[0023] The original metal material simulation data is parsed using a pre-configured multimodal document parser, and processable data objects are extracted from the original metal material simulation data; wherein the processable data objects include: text objects, table objects and image objects;

[0024] For the extracted image objects, each image and its associated caption text are treated as a data unit;

[0025] Based on a parametric semantic dictionary, a semantic template library for metal material simulation data is constructed, including: mathematical equation semantic template, single-point value semantic template, and temperature sequence semantic template. The mathematical equation semantic template, single-point value semantic template, and temperature sequence semantic template all adopt a parametric placeholder structure, and the priority order of the mathematical equation semantic template, temperature sequence semantic template, and single-point value semantic template is set to decrease sequentially.

[0026] Iterate through the extracted text and table objects, divide the currently traversed text or table object into data blocks, and divide it into several independent data segments to be identified. Then, perform data cleaning and standardization on each data segment to be identified.

[0027] Based on a semantic template library for metal material simulation data, each processed data segment to be identified is matched with a mathematical equation semantic template, a temperature sequence semantic template, and a single-point value semantic template in order of priority using regular expressions. During the matching process, if the current data segment to be identified successfully matches any semantic template, the matching of the current data segment to be identified ends, and the data entity and its corresponding value are extracted from the current data segment to be identified as a data unit. If the current data segment to be identified fails to match any semantic template, the current data segment to be identified is marked as invalid data and discarded.

[0028] Each data cell is used as a material parameter in the original metal material simulation data.

[0029] Furthermore, the specific content of mapping the material parameters to the predefined dimensions of the multi-dimensional metallic material simulation data model to generate structured metallic material simulation data is as follows:

[0030] For any material parameter, based on the parameter semantic dictionary, query the parameter's unique identifier and data label;

[0031] Based on the dynamic mapping rule base, determine the level to which the material parameter belongs in the multi-level classification structure of the metal material simulation data;

[0032] Based on the level of the material parameter in the multi-level classification structure of the metal material simulation data, the data entity in the material parameter is associated with the corresponding parameter set in the multi-level classification structure. Starting from the parameter set in the multi-level classification structure, each level in the multi-level classification structure is traversed upwards to generate a data entry path for the material parameter.

[0033] Based on the data entry path of the material parameter, the numerical value or image of the material parameter is used as the data to be entered at the end of the data entry path to generate the structured metal material simulation data of the material parameter.

[0034] On the other hand, the present invention proposes a data processing system for a metal material simulation database, the system comprising:

[0035] The data acquisition module is used to receive raw metal material simulation data from multiple heterogeneous data sources;

[0036] The data extraction module is used to parse each piece of original metal material simulation data in turn by calling a predefined multi-dimensional metal material simulation data model based on metadata, and to identify and extract the material parameters of the original metal material simulation data.

[0037] The data matching module is used to map the material parameters to the predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data.

[0038] The data entry module is used to generate a unique traceability code for each structured metal material simulation data, and to enter the structured metal material simulation data into the metal material simulation database based on the generated traceability code.

[0039] Thirdly, this application proposes an electronic device, comprising: one or more processors, and a memory for storing instructions, which, when executed by the one or more processors, cause the one or more processors to perform the data processing method for a metal material simulation database.

[0040] Fourthly, this application proposes a computer-readable storage medium storing executable instructions that, when executed, cause a processor to perform the data processing method for a metal material simulation database.

[0041] Fifthly, this application proposes a computer program product, including a computer program or instructions, which, when executed by a processor, implements the data processing method for a metal material simulation database.

[0042] The beneficial effects of adopting the above technical solution are as follows:

[0043] The form design method proposed in this invention considers several aspects, including simulation software, material types, required temperatures, data types, and whether the materials are anisotropic. It categorizes the data according to actual needs in business operations, achieving standardized data entry. Specifically, material data is first classified into several major categories, such as general physical parameters, thermophysical parameters, plasticity parameters, and microstructure parameters. Except for general physical parameters, each category of data is further classified according to different metal raw material types, such as bars, plates, pipes, and powders. Different entry methods are set for different data types, enabling accurate entry of metal material simulation data.

[0044] Furthermore, this invention achieves automated transformation from raw heterogeneous data to structured information by constructing a multi-dimensional data model based on metadata and implementing an intelligent processing flow that integrates multimodal document parsing, semantic template matching, and dynamic rule mapping. This invention can automatically identify and extract material parameters from metallic material simulation data, accurately analyze complex data types such as mathematical equations and temperature sequences, and dynamically associate them with the corresponding dimensions of the data model, while assigning each data point a unique traceable code. This process not only significantly improves the efficiency and accuracy of data entry and reduces reliance on manual intervention, but also provides a high-quality, traceable data foundation for subsequent simulation analysis, fundamentally enhancing the credibility of simulation results and the reusability of data assets. Attached Figure Description

[0045] Figure 1 This is a flowchart of a data processing method for a metal material simulation database in this embodiment;

[0046] Figure 2 This is a schematic diagram of the structure of the multi-dimensional metal material simulation data model based on metadata in this embodiment;

[0047] Figure 3 This is a structural diagram of a data processing system for a metal material simulation database in this embodiment. Detailed Implementation

[0048] To facilitate understanding of this application, specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. The following embodiments are illustrative of the invention but are not intended to limit its scope. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0049] Example 1:

[0050] This embodiment provides a data processing method for a metal material simulation database, such as... Figure 1 As shown, the method includes the following steps:

[0051] Construct a multi-dimensional simulation data model for metallic materials based on metadata.

[0052] To address the technical challenge of "how to enable computer systems to intelligently manage and retrieve simulation data of complex metallic materials," this embodiment designs a data classification structure based on business logic, using metadata. This structure clearly indicates that subsequent data processing is based on this rigorous classification structure, which can meet actual business needs.

[0053] The specific content of constructing a multi-dimensional metal material simulation data model based on metadata is as follows:

[0054] Construct a parameter semantic dictionary to predefine metadata for each material parameter in the metal material simulation data; the metadata includes at least: a unique identifier for the parameter and a data tag for declaring the data type to which the material parameter belongs; the data tag includes at least: mathematical equation, single-point value, temperature sequence, and image.

[0055] Establish a multi-level classification structure for simulation data of metallic materials.

[0056] The first level of the multi-level classification structure is the material category, which is used to distinguish sets of materials with different performance characteristics.

[0057] In this embodiment, as Figure 2 As shown, the material categories include, but are not limited to: high-temperature alloys, titanium alloys, and castings.

[0058] The second level of the multi-level classification structure is the material grade, which is used to distinguish materials with specific chemical compositions and basic mechanical properties according to national standards, industry standards, or enterprise standards.

[0059] In this embodiment, the material grade serves as a standardized identifier, ensuring compliance with the material's chemical composition and basic properties. For example... Figure 2 As shown, the category of high-temperature alloys is further divided into materials such as GH4169 and GH3625.

[0060] The third level of the multi-level classification structure is the parameter type, which is used to group material parameters belonging to the same material grade according to the physical nature of the metal material simulation data.

[0061] The parameter types include, but are not limited to: general physical parameters, thermophysical parameters, plasticity parameters, and microstructure parameters. The general physical parameters are those used to describe the fundamental physical properties of materials; the thermophysical parameters are those used to describe the thermal behavior of materials; and the plasticity parameters are those used to describe the plastic behavior of materials. Furthermore, in the multi-level classification structure, each of the general physical parameters, thermophysical parameters, and plasticity parameters is associated with a parameter set at its next level. This parameter set contains data entities and data entry interfaces for all material parameters under that parameter type.

[0062] The organization parameters are parameters used to describe the microstructure characteristics of materials; and in the multi-level classification structure, the next level of the organization parameters is the product form.

[0063] In this embodiment, as Figure 2 As shown, simulation data for metallic materials belonging to the same material grade are initially classified into: general physical parameters, thermophysical parameters, plastic mechanical parameters, and microstructure parameters. General physical parameters include parameters such as density and hardness that do not change with the material type or state. Microstructure parameters are specifically categorized into different metallic raw material types such as bars, plates, tubes, and powders.

[0064] The next level after the product form is the application scenario, which is used to identify the specific process in which the material is processed; and the next level after the application scenario is associated with a set of parameters.

[0065] In this embodiment, the data from the simulation application scenarios involved in each raw material type are listed below. Among them, the mechanical processing simulation application scenarios are divided into two major categories: shot peening and pipe machining; the welding simulation application scenarios are divided into six major categories: brazing, friction welding, diffusion welding, electron beam welding, argon arc welding, and laser welding.

[0066] A dynamic mapping rule library is constructed to store the mapping rules that associate different classification dimensions in the multi-level classification structure with the parameter semantic dictionary.

[0067] The mapping rule is: the mapping relationship from the combination of dimensions such as material category, material grade, parameter type, product form and application scenario in the multi-level classification structure to the set of unique parameter identifiers in the parameter semantic dictionary.

[0068] It receives raw metal material simulation data from multiple heterogeneous data sources.

[0069] In this embodiment, the received raw metal material simulation data comes from multiple heterogeneous data sources, including experimental test data provided by the company's internal material testing center, product performance data sheets provided by material suppliers, standard parameters in international / national / industry standard databases, simulation result data output by process simulation software, and verified material parameters extracted from academic literature and patents.

[0070] Based on the multi-dimensional metal material simulation data model, each original metal material simulation data is analyzed sequentially to identify and extract the material parameters of the original metal material simulation data.

[0071] Based on the multi-dimensional metal material simulation data model, each original metal material simulation data is analyzed sequentially to identify and extract the specific content of the material parameters of the original metal material simulation data:

[0072] The original metal material simulation data is parsed by a pre-configured multimodal document parser, and processable data objects are extracted from the original metal material simulation data; wherein the processable data objects include: text objects, table objects and image objects.

[0073] In this embodiment, the processable data objects parsed by the multimodal document parser from the original metal material simulation data are: text objects for extracting descriptive information such as material grade, parameter name, and application scenario; table objects for extracting structured single-point data or discrete sequence data; and image objects for identifying and extracting material property curves and microstructure morphology.

[0074] For each extracted image object, each image and its associated caption text are treated as a data unit.

[0075] Based on a parametric semantic dictionary, a semantic template library for metal material simulation data is constructed, including: mathematical equation semantic templates, single-point value semantic templates, and temperature sequence semantic templates. The mathematical equation semantic templates, single-point value semantic templates, and temperature sequence semantic templates all adopt a parametric placeholder structure, and the priority order of the mathematical equation semantic templates, temperature sequence semantic templates, and single-point value semantic templates is set to decrease sequentially.

[0076] The mathematical equation semantic template is used to identify the functional relationship between material parameters; the single-point value semantic template is used to identify the constant value of material parameters under specific conditions; and the temperature sequence semantic template is used to identify the discrete value set of material parameters at different temperature points.

[0077] The extracted text and table objects are traversed, and the data of the currently traversed text or table object is divided into several independent data segments to be identified. Data cleaning and standardization are then performed on each data segment to be identified.

[0078] In this embodiment, text objects are segmented into independent sentences or paragraphs using periods, semicolons, or line breaks. Table objects are segmented by rows or cells, thus treating each sentence or each table cell / row as an independent "data to be identified." Data cleaning and standardization typically include methods such as unified character encoding, standardized unit symbols, correction of common typos, and standardization of mathematical operators.

[0079] Based on a semantic template library for metal material simulation data, each processed data segment to be identified is matched with a mathematical equation semantic template, a temperature sequence semantic template, and a single-point value semantic template in order of priority using regular expressions. During the matching process, if the current data segment to be identified successfully matches any semantic template, the matching of the current data segment to be identified ends, and the data entity and its corresponding value in the current data segment to be identified are extracted and treated as a data unit. If the current data segment to be identified fails to match any semantic template, the current data segment to be identified is marked as invalid data and discarded.

[0080] In this embodiment, the matching order of mathematical equations, temperature sequences, and single-point values ​​conforms to the matching principle of "from complex to simple," which can effectively reduce misjudgments. For example, it avoids misjudging a simple equation as a single-point value. Data entities refer to physical quantities with unique identifiers defined by the parameter semantic dictionary, such as density, yield strength, elastic modulus, and thermal conductivity.

[0081] Each data cell is used as a material parameter in the original metal material simulation data.

[0082] The material parameters are mapped to the predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data.

[0083] The specific content of mapping the material parameters to the predefined dimensions of the multi-dimensional metallic material simulation data model to generate structured metallic material simulation data is as follows:

[0084] For any material parameter, based on the parameter semantic dictionary, query the parameter's unique identifier and data label.

[0085] Based on the dynamic mapping rule base, determine the level to which the material parameter belongs in the multi-level classification structure of the metal material simulation data.

[0086] Based on the level of the material parameter in the multi-level classification structure of the metal material simulation data, the data entity in the material parameter is associated with the corresponding parameter set in the multi-level classification structure. Starting from the parameter set in the multi-level classification structure, each level in the multi-level classification structure is traversed upwards to generate a data entry path for the material parameter.

[0087] Based on the data entry path of the material parameter, the numerical value or image of the material parameter is used as the data to be entered at the end of the data entry path to generate the structured metal material simulation data of the material parameter.

[0088] A unique traceability code is generated for each structured metal material simulation data, and the structured metal material simulation data is entered into the metal material simulation database based on the generated traceability code.

[0089] In this embodiment, encoding algorithms such as hashing and rule concatenation are used to uniquely encode each batch of data to achieve traceability. Each data batch refers to a set of material parameter data from the same data carrier, entered into the system at the same time, and for the same material type. Using standard database operation languages ​​(such as SQL), structured data objects are stored in designated tables in the database via INSERT commands. For data that varies with temperature, a series of temperature-data correspondence values ​​are entered using hyperlinks; for equation-based data, corresponding variable values ​​are set to complete the entry.

[0090] In this embodiment,

[0091] Example 2:

[0092] This embodiment describes a data processing system for a metal material simulation database, such as... Figure 3 As shown, the system includes:

[0093] The data acquisition module is used to receive raw metal material simulation data from multiple heterogeneous data sources.

[0094] The data extraction module is used to parse each piece of original metal material simulation data sequentially by calling a predefined multi-dimensional metal material simulation data model based on metadata, and to identify and extract the material parameters of the original metal material simulation data.

[0095] The data matching module is used to map the material parameters to the predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data.

[0096] The data entry module is used to generate a unique traceability code for each structured metal material simulation data, and to enter the structured metal material simulation data into the metal material simulation database based on the generated traceability code.

[0097] Example 3:

[0098] This embodiment proposes an electronic device, including: one or more processors, and a memory, wherein the memory is used to store instructions, and when the instructions are executed by the one or more processors, the one or more processors execute the data processing method of a metal material simulation database.

[0099] The electronic device may be a mobile phone, computer, or tablet computer, etc., and includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, implements a data processing method for a metal material simulation database as described in the embodiments. It is understood that the electronic device may also include an input / output (I / O) interface and communication components.

[0100] The processor is used to execute all or part of the steps in the data processing method for a metal material simulation database as described in the above embodiments. The memory is used to store various types of data, which may include, for example, instructions for any application or method in an electronic device, as well as application-related data.

[0101] The processor can be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic components, and is used to execute the data processing method for a metal material simulation database described in the above embodiments.

[0102] Example 4:

[0103] This embodiment proposes a computer-readable storage medium that stores executable instructions. When these instructions are executed, if they are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0104] The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the data processing method for a metal material simulation database described in various embodiments of this application.

[0105] The aforementioned storage media include: flash memory, hard disks, multimedia cards, card-type memory (e.g., SD (Secure Digital Memory Card) or DX (Memory Data Register, MDR) memory), random access memory (RAM), static random-access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, disks, optical discs, servers, APP (Application) application stores, and other media capable of storing program verification codes. These media store computer programs, which, when executed by a processor, can implement the various steps of the data processing method for a metal material simulation database described above.

[0106] Example 5:

[0107] This embodiment proposes a computer program product, including a computer program or instructions, which, when executed by a processor, implements the data processing method for a metal material simulation database.

[0108] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a computer program product.

[0109] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0110] The scope of protection of this application is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from the scope and spirit of this disclosure. If such modifications and variations fall within the scope of this disclosure and its equivalents, then the intent of this disclosure also includes these modifications and variations.

Claims

1. A data processing method for a metal material simulation database, characterized in that, This method includes the following steps: Constructing a multi-dimensional simulation data model for metallic materials based on metadata; the specific content is as follows: Construct a parameter semantic dictionary to predefine the metadata of each material parameter in the simulation data of metallic materials; The metadata includes at least: a unique identifier for the parameter and a data tag for declaring the data type to which the material parameter belongs; the data tag includes at least: a mathematical equation, a single-point value, a temperature series, and an image. Establish a multi-level classification structure for simulation data of metallic materials; A dynamic mapping rule library is constructed to store the mapping rules that associate different classification dimensions in the multi-level classification structure with the parameter semantic dictionary; Receive raw metallic material simulation data from multiple heterogeneous data sources; Based on the multi-dimensional metal material simulation data model, each piece of original metal material simulation data is analyzed in sequence to identify and extract the material parameters of the original metal material simulation data. The material parameters are mapped to predefined dimensions of the multi-dimensional metallic material simulation data model to generate structured metallic material simulation data; specifically: For any material parameter, based on the parameter semantic dictionary, query the parameter's unique identifier and data label; Based on the dynamic mapping rule base, determine the level to which the material parameter belongs in the multi-level classification structure of the metal material simulation data; Based on the level of the material parameter in the multi-level classification structure of the metal material simulation data, the data entity in the material parameter is associated with the corresponding parameter set in the multi-level classification structure. Starting from the parameter set in the multi-level classification structure, each level in the multi-level classification structure is traversed upwards to generate a data entry path for the material parameter. Based on the data entry path of the material parameter, the value or image in the material parameter is used as the data to be entered at the end of the data entry path to generate the structured metal material simulation data of the material parameter. A unique traceability code is generated for each structured metal material simulation data, and the structured metal material simulation data is entered into the metal material simulation database based on the generated traceability code.

2. The data processing method for a metal material simulation database according to claim 1, characterized in that, The first level of the multi-level classification structure is the material category, which is used to distinguish sets of materials with different performance characteristics; The second level of the multi-level classification structure is the material grade, which is used to distinguish materials with specific chemical compositions and basic mechanical properties according to national standards, industry standards or enterprise standards. The third level of the multi-level classification structure is the parameter type, which is used to group material parameters belonging to the same material grade according to the physical nature of the metal material simulation data; The parameter types include: general physical parameters, thermophysical parameters, plasticity parameters, and microstructure parameters; wherein the general physical parameters are parameters used to describe the basic physical properties of materials; the thermophysical parameters are parameters used to describe the thermal behavior of materials; and the plasticity parameters are parameters used to describe the plastic behavior of materials; and in the multi-level classification structure, the next level of the general physical parameters, thermophysical parameters, and plasticity parameters are all associated with a parameter set; the parameter set contains data entities and data input interfaces for all material parameters under each type of parameter. The organization parameters are parameters used to describe the microstructure characteristics of materials; and in the multi-level classification structure, the next level of the organization parameters is the product form. The next level after the product form is the application scenario, which is used to identify the specific process in which the material is processed; and the next level after the application scenario is associated with a set of parameters.

3. The data processing method for a metal material simulation database according to claim 2, characterized in that, The mapping rule is: the mapping relationship from the combination of dimensions such as material category, material grade, parameter type, product form and application scenario in the multi-level classification structure to the set of unique parameter identifiers in the parameter semantic dictionary.

4. The data processing method for a metal material simulation database according to claim 3, characterized in that, Based on the multi-dimensional metal material simulation data model, each original metal material simulation data is analyzed sequentially to identify and extract the specific content of the material parameters of the original metal material simulation data: The original metal material simulation data is parsed using a pre-configured multimodal document parser, and processable data objects are extracted from the original metal material simulation data. The processable data objects include: text objects, table objects, and image objects; For the extracted image objects, each image and its associated caption text are treated as a data unit; Based on a parametric semantic dictionary, a semantic template library for metal material simulation data is constructed, including: mathematical equation semantic template, single-point value semantic template, and temperature sequence semantic template. The mathematical equation semantic template, single-point value semantic template, and temperature sequence semantic template all adopt a parametric placeholder structure, and the priority order of the mathematical equation semantic template, temperature sequence semantic template, and single-point value semantic template is set to decrease sequentially. Iterate through the extracted text and table objects, divide the currently traversed text or table object into data blocks, and divide it into several independent data segments to be identified. Then, perform data cleaning and standardization on each data segment to be identified. Based on a semantic template library for metal material simulation data, each processed data segment to be identified is matched with a mathematical equation semantic template, a temperature sequence semantic template, and a single-point value semantic template in order of priority using regular expressions. During the matching process, if the current data segment to be identified successfully matches any semantic template, the matching of the current data segment to be identified ends, and the data entity and its corresponding value are extracted from the current data segment to be identified as a data unit. If the current data segment to be identified fails to match any semantic template, the current data segment to be identified is marked as invalid data and discarded. Each data cell is used as a material parameter in the original metal material simulation data.

5. A data processing system for a metal material simulation database, used to implement the data processing method for a metal material simulation database as described in any one of claims 1-4, characterized in that, The system includes: The data acquisition module is used to receive raw metal material simulation data from multiple heterogeneous data sources; The data extraction module is used to parse each piece of original metal material simulation data in turn by calling a predefined multi-dimensional metal material simulation data model based on metadata, and to identify and extract the material parameters of the original metal material simulation data. The data matching module is used to map the material parameters to the predefined dimensions of the multi-dimensional metal material simulation data model to generate structured metal material simulation data. The data entry module is used to generate a unique traceability code for each structured metal material simulation data, and to enter the structured metal material simulation data into the metal material simulation database based on the generated traceability code.

6. An electronic device, characterized in that, include: One or more processors, and a memory for storing instructions that, when executed by the one or more processors, cause the one or more processors to perform a data processing method for a metal material simulation database according to any one of claims 1-4.

7. A computer-readable storage medium storing executable instructions, characterized in that, When the instruction is executed, it causes the processor to perform the data processing method for a metal material simulation database as described in any one of claims 1-4.

8. A computer program product, characterized in that, It includes a computer program or instructions that, when executed by a processor, implement the data processing method for a metal material simulation database as described in any one of claims 1-4.

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