Method and apparatus for screening rolling parameters, and nonvolatile storage medium

Abstract

This application discloses a method and apparatus for screening rolling parameters, as well as a non-volatile storage medium. The method includes: acquiring rolling parameters, wherein the rolling parameters include rolling process parameters and material property parameters of the object being rolled; generating a first simulation model based on the rolling parameters, wherein the first simulation model reflects the rolling process of the object being rolled using the rolling process parameters; generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model reflects the changes in impurities contained in the object being rolled during the rolling process; determining a target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results; determining a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal effect on impurity crushing.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and more specifically, to a method and apparatus for screening rolling parameters, and a non-volatile storage medium. Background Technology

[0002] Adding recycled aluminum during the smelting process significantly increases the content of second-phase impurities such as iron, making it difficult to fully break down impurity particles during rolling. This leads to problems such as ingot cracking, rolling cracking, and uneven deformation. In related technologies, rolling process optimization mainly relies on empirical trial-and-error methods, which suffer from long selection cycles and high costs for rolling parameters. Furthermore, rolling parameters selected using empirical trial-and-error methods also suffer from difficulties in precise control of the rolling process, poor impurity particle breaking effect, and low rolling efficiency.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a method and apparatus for screening rolling parameters, as well as a non-volatile storage medium, to at least solve the technical problems of long time consumption and low rolling efficiency in determining the optimal rolling parameters caused by the experimental trial-and-error method for optimizing the rolling process in related technologies.

[0005] According to one aspect of the embodiments of this application, a method for screening rolling parameters is provided, comprising: acquiring rolling parameters, wherein the rolling parameters include: rolling process parameters and material property parameters of the rolled object; generating a first simulation model based on the rolling parameters, wherein the first simulation model is used to reflect the process of rolling the rolled object using the rolling process parameters; generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model is used to reflect the changes of impurities contained in the rolled object during the rolling process; determining a target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the rolled object; determining a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal crushing effect on impurities.

[0006] Optionally, generating a first simulation model based on rolling parameters includes: processing the rolling process parameters and the material property parameters of the rolled object using finite element analysis software to obtain the first simulation model output by the finite element analysis software. The rolling process parameters include the first geometric parameters and rolling operation parameters of the rolling tool, and the material property parameters of the rolled object include the second geometric parameters and physical property parameters of the rolled object. In the first simulation model, the rolled object is composed of multiple meshes.

[0007] Optionally, generating a second simulation model based on the first simulation model and rolling parameters includes: performing a simulation operation on the first simulation model to obtain a set of simulation parameters, wherein the set of simulation parameters consists of multiple sets of simulation parameters, each set of simulation parameters corresponds to a mesh, each set of simulation parameters is used to reflect the thermo-mechanical coupling state of a mesh during the rolling process, and each mesh represents a part of the rolling object; extracting target simulation parameters from the set of simulation parameters; and generating a second simulation model based on the target simulation parameters and rolling parameters, wherein each set of target simulation parameters is used to generate a second simulation model, and each set of target simulation parameters is associated with a mesh.

[0008] Optionally, target simulation parameters are extracted from the set of simulation parameters. The target simulation parameters are determined by the following method: determining an optional grid corresponding to a preset position, wherein the preset position is located on the rolling object, and the preset position includes: a first type of position reflecting the stress state of the rolling object during the rolling process, a second type of position reflecting the thermodynamic changes of the rolling object during the rolling process, and a third type of position reflecting the deformation uniformity of the rolling object during the rolling process; determining a target grid in the optional grid, and determining a set of simulation parameters distributed on the target grid as the target simulation parameters, wherein the target simulation parameters include: a first type of history data of thermal parameters and a second type of history data of mechanical parameters distributed in the target grid, wherein the first type of history data is used to reflect the change of thermal parameters with rolling time, and the second type of history data is used to reflect the change of mechanical parameters with rolling time.

[0009] Optionally, a second simulation model is generated based on the target simulation parameters and rolling parameters, including: generating the second simulation model based on the material property parameters of the rolled object contained in the target simulation parameters and rolling parameters, wherein the material property parameters of the rolled object are used as property parameters of the second simulation model, and the second simulation model includes: a matrix domain, an impurity domain, and a void domain. The matrix domain is used to represent the microstructure of the target region, the impurity domain is used to represent the shape and location of impurities contained in the target region, and the void domain is used to represent the region in the target region where no filling material exists. The target region is the region covered by the main material in the target mesh, the target mesh is the mesh associated with the target simulation parameters, and the main material is the material with the highest proportion in the rolled object.

[0010] Optionally, the second simulation model is analyzed according to the target simulation parameters to obtain simulation results, including: replacing the boundary conditions in the simulation operation parameters with the target simulation parameters to obtain the target simulation operation parameters, wherein the boundary conditions are used to represent the external environmental conditions that affect the dynamic changes of impurities during the rolling process; and performing simulation operations on the second simulation model using the target simulation operation parameters to obtain simulation results, wherein the simulation results include: the number of impurities and the size information of each impurity.

[0011] Optionally, the target rolling parameters are determined from the multiple sets of rolling parameters based on the multiple simulation results corresponding to the multiple sets of rolling parameters, including: determining the simulation result to be screened with the most impurities from the multiple sets of simulation results; for each simulation result to be screened, determining the largest impurity size from the multiple impurity sizes contained in the simulation result to be screened; determining the smallest impurity size from the multiple largest impurity sizes; determining the target simulation result to be screened corresponding to the smallest impurity size; and determining the set of rolling parameters corresponding to the target simulation result to be screened as the target rolling parameters.

[0012] According to another aspect of the embodiments of this application, an apparatus for screening rolling parameters is also provided, comprising: an acquisition module for acquiring rolling parameters, wherein the rolling parameters include: rolling process parameters and material property parameters of the rolled object; a first generation module for generating a first simulation model based on the rolling parameters, wherein the first simulation model reflects the process of rolling the rolled object using the rolling process parameters; a second generation module for generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model reflects the changes of impurities contained in the rolled object during the rolling process; an analysis module for determining a target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the rolled object; and a determination module for determining a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal crushing effect on impurities.

[0013] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, which stores a computer program, wherein the above-described method of screening and rolling parameters is executed by running the computer program in the device where the non-volatile storage medium is located.

[0014] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the above-described method of screening rolling parameters through the computer program.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including computer instructions that, when executed by a processor, implement the steps of the above-described method for screening rolling parameters.

[0016] In this embodiment, rolling parameters are obtained, including rolling process parameters and material property parameters of the object being rolled. A first simulation model is generated based on the rolling parameters, reflecting the rolling process of the object being rolled using the rolling process parameters. A second simulation model is generated based on the first simulation model and the rolling parameters, reflecting the changes in impurities contained in the object being rolled during the rolling process. Target simulation parameters associated with the second simulation model are determined from the set of simulation parameters of the first simulation model, and the second simulation model is analyzed based on the target simulation parameters to obtain simulation results, which are used to quantify the crushing effect of impurities contained in the object being rolled. Multiple simulation results corresponding to multiple sets of rolling parameters are then used to further refine the simulation model. If a target rolling parameter is determined from multiple sets of rolling parameters, and the rolling operation corresponding to the target rolling parameter has the optimal effect on impurity crushing, a dual-level simulation strategy of macroscopic and microscopic simulation is adopted. The simulation data of the macroscopic simulation model is used as the boundary condition when simulating the microscopic simulation model. This achieves the goal of combining macroscopic and microscopic simulation to analyze the rolling effect of rolling parameters, thereby shortening the time for screening the optimal rolling parameters. Applying the screened rolling parameters to the actual rolling process can improve the rolling effect and the accuracy of the rolling process. This solves the technical problems of long time consumption and low rolling efficiency caused by the experimental trial and error method to optimize the rolling process in related technologies. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a hardware structure block diagram of a computer terminal for implementing a method for screening rolling parameters according to an embodiment of this application;

[0019] Figure 2 This is a flowchart illustrating the steps of a method for selecting rolling parameters according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram of a macroscopic model according to an embodiment of this application;

[0021] Figure 4 This is a schematic diagram of a microscopic model according to an embodiment of this application;

[0022] Figure 5 This is a comparison diagram of the simulation results of a microscopic model corresponding to different rolling parameters according to an embodiment of this application;

[0023] Figure 6 This is a structural diagram of an apparatus for screening rolling parameters according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] To better understand the embodiments of this application, the technical terms involved in the embodiments of this application are explained below:

[0027] Second phase: Other phases that are not discontinuously distributed in the matrix phase. The second phase may exist in the form of particles, fibers, plates, etc. For example, in a solid metal matrix, substances with different chemical compositions and crystal structures besides the main metal composition are called second phases.

[0028] Constitutive Relation: The mathematical relationship between a material's internal response (such as stress, strain, displacement, temperature change, current density, etc.) and these external forces when subjected to external forces (such as force, heat, electric field, etc.) is an intrinsic property of the material.

[0029] Stress history data: In this embodiment of the application, it is data used to describe the change of internal stress of the rolled object with rolling time during the rolling process.

[0030] Strain history data: In this embodiment of the application, it is data used to describe the change in the degree of deformation of the rolled object during the rolling process with the rolling time.

[0031] Temperature history data: In this embodiment of the application, it is data used to describe the temperature change trend of the rolled object during the heating and cooling process as a function of rolling time.

[0032] Speed ​​history data: In this embodiment of the application, it is data used to describe the changes in the moving speed, deformation speed and cooling speed of the rolled object with rolling time during the rolling process.

[0033] In related technologies, the control of second-phase impurity particles during the rolling process of metallic materials (such as aluminum alloys) mainly employs the following methods: one is to reduce the impurity content by adjusting the smelting process; however, this method reduces the utilization rate of scrap aluminum, which is inconsistent with the trend of resource recycling. Another method is to promote impurity breakage through multiple rolling and annealing processes, which increases the rolling process time, energy consumption, and production costs. Furthermore, rolling parameters can be optimized using Design of Experiments (DOE) methods, but this method suffers from problems such as large experimental scale, long cycle, difficulty in comprehensively covering complex working conditions, and difficulty in accurately controlling the breakage effect on impurity particles during rolling. To address this issue, the embodiments of this application provide relevant solutions, which are detailed below.

[0034] According to an embodiment of this application, a method embodiment for screening rolling parameters is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal for implementing a method for screening rolling parameters is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0036] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0037] The memory 104 can be used to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the method for screening rolling parameters in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the aforementioned method for screening rolling parameters. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0038] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0039] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0040] This application provides a method for screening rolling parameters that can operate under the above-described operating environment. Figure 2 This is a flowchart of the steps of the method for screening rolling parameters according to the embodiments of this application, as follows: Figure 2 As shown, the method includes the following steps:

[0041] Step S202: Obtain rolling parameters, which include rolling process parameters and material property parameters of the object being rolled.

[0042] This application provides a rolling parameter optimization method based on simulation calculation and experimental verification. The method determines the optimal rolling parameters for crushing effect through simulation calculation. In actual production, using the rolling parameters determined by simulation calculation can promote the effective crushing of impurity particles and eliminate problems such as rolling cracking and uneven deformation caused by impurities. In step S202, rolling parameters are received. Each set of received rolling parameters includes two categories: rolling process parameters and material property parameters of the rolled object. The rolling process parameters describe the environment and rolling tools related to the rolling operation and can be manually adjusted. The material property parameters of the rolled object describe the material characteristics of the rolled object itself and are related to the rolled object. The rolling tools mentioned above include rolling mills (including: rolls, stands, transmission systems, hydraulic systems, lubrication systems, and control systems, etc.), and the rolled object can be a metal ingot. The rolled object usually contains components different from the main components of the ingot (i.e., impurities). Generally, the impurities contained in the rolled object are called second-phase impurities. Second-phase impurities may be in the form of particles, such as iron-aluminum interalloy compounds (FeAl3), iron particles, etc.

[0043] Step S204: Generate a first simulation model based on the rolling parameters, wherein the first simulation model is used to reflect the rolling process of the object being rolled using the rolling process parameters.

[0044] After receiving the rolling parameters in step S202, in step S204, a macroscopic model (i.e., the first simulation model) is constructed based on the acquired rolling parameters. The macroscopic simulation model is used to simulate the rolling process of the rolled object. The macroscopic model can show the process of the rolled object in the form of an ingot being transformed into a rolled object in the form of a sheet under the action of the rolling tool.

[0045] Optionally, generating a first simulation model based on rolling parameters includes: processing the rolling process parameters and the material property parameters of the rolled object using finite element analysis software to obtain the first simulation model output by the finite element analysis software. The rolling process parameters include the first geometric parameters and rolling operation parameters of the rolling tool, and the material property parameters of the rolled object include the second geometric parameters and physical property parameters of the rolled object. In the first simulation model, the rolled object is composed of multiple meshes.

[0046] The macroscopic model (i.e. the first simulation model) can be generated based on finite element analysis software. By inputting the rolling parameters obtained in step S202 into the finite element analysis software, a macroscopic model representing the process of rolling the object using the rolling process parameters in step S202 can be obtained. Figure 3 This is a schematic diagram of a macroscopic model. Figure 3 It is a macroscopic model output by finite element analysis software, such as Figure 3 As shown, the macroscopic model includes rolling tools (rolls) and the object being rolled. Figure 3 The rolled object shown is in the form of a plate after being rolled into a sheet, called a rolled plate. Before rolling, the rolled object is in the form of an ingot; due to Figure 3 The model simultaneously displays both the rolling tool and the rolled object. Therefore, it can be understood that when constructing the macroscopic model, the parameters input into the finite element analysis software include: relevant parameters of the rolling operation (included in the rolling process parameters) and relevant parameters of the rolled object (included in the material property parameters of the rolled object). The aforementioned relevant parameters of the rolling operation include: geometric parameters describing the shape of the rolling tool (i.e., the first geometric parameters), such as the diameter, width, and surface roughness of the rolls; and rolling operation parameters used to control the specific degree of rolling, such as rolling speed (the unit can be set to meters (m) / minute (min)), pressure (the unit can be set to millimeters (mm) / pass), rolling temperature, and the coefficient of friction between the rolls and the sheet metal. The relevant parameters of the rolled object include: geometric parameters describing the shape of the rolled object (i.e., second geometric parameters), such as the original dimensions of the ingot (length, width, and thickness), and physical property parameters describing the physical properties of the material of the rolled object (i.e., physical property parameters), such as the density, elastic modulus, Poisson's ratio, yield strength, thermal conductivity, specific heat capacity, coefficient of linear expansion, constitutive relation, etc.

[0047] After simulating the input rolling parameters, the finite element analysis software outputs a macroscopic model describing the rolling process (i.e., the first simulation model). In the first simulation model, the rolling object is divided into multiple mesh elements (or meshes). Each mesh element represents a small part of the rolling object and can be used to accurately capture the stress, strain distribution, and temperature changes inside the material.

[0048] The method provided in this embodiment constructs a macroscopic simulation model (i.e., the first simulation model) corresponding to the input rolling parameters, simulating the rolling process of the object. The macroscopic simulation model can show the changes of the object in the macroscopic dimension during the rolling process. The simulation results of the macroscopic simulation model will be applied to the subsequent microscopic simulation, achieving the purpose of joint macroscopic and microscopic analysis, thereby improving the accuracy of the analysis results.

[0049] Step S206: Generate a second simulation model based on the first simulation model and rolling parameters, wherein the second simulation model is used to reflect the changes of impurities contained in the rolled object during the rolling process.

[0050] After the macroscopic model (i.e. the first simulation model) is constructed in step S204, in step S206, the simulation data of the macroscopic model and the rolling parameters obtained in step S202 are combined to construct the microscopic model (i.e. the second simulation model). The microscopic model focuses on the changes of impurities contained in the rolled object during the rolling process. Through the microscopic model, the position and morphology changes of the second-phase impurity particles in the rolled object during the rolling process can be observed.

[0051] Optionally, generating a second simulation model based on the first simulation model and rolling parameters includes: performing a simulation operation on the first simulation model to obtain a set of simulation parameters, wherein the set of simulation parameters consists of multiple sets of simulation parameters, each set of simulation parameters corresponds to a mesh, each set of simulation parameters is used to reflect the thermo-mechanical coupling state of a mesh during the rolling process, and each mesh represents a part of the rolling object; extracting target simulation parameters from the set of simulation parameters; and generating a second simulation model based on the target simulation parameters and rolling parameters, wherein each set of target simulation parameters is used to generate a second simulation model, and each set of target simulation parameters is associated with a mesh.

[0052] As mentioned in step S206, the method provided in this application embodiment will use the simulation data of the macroscopic model (i.e., the first simulation model) and the rolling parameters obtained in step S202 to construct a microscopic model to describe the microscopic changes in the rolling process. The simulation data of the macroscopic model (i.e., the first simulation model) is the simulation result obtained after the simulation operation of the macroscopic model is completed. Since the rolling object is divided into multiple grid units (or grids) in the first simulation model, and the simulation operation of the macroscopic model (i.e., the first simulation model) is a thermodynamic analysis process, the series of simulation data generated by the simulation operation of the macroscopic model includes the history data of parameters such as stress, strain, speed and temperature of different grid units in the rolling process. That is to say, the set of simulation parameters obtained by performing the simulation operation on the first simulation model contains multiple sets of simulation parameters, and each set of simulation parameters is related to a grid. The set of simulation parameters related to each grid includes the following data: history data of parameters such as stress, strain, speed and temperature, which are used to describe the thermodynamic coupling state of the location of the grid (the specific location on the rolling object) in the rolling process.

[0053] After performing simulation operations on the first simulation model, a set of simulation parameters (i.e., target simulation parameters) closely related to the impurity crushing effect are extracted from the simulation data set. These target simulation parameters and the rolling parameters provided by the user in step S202 are used to jointly construct a micro-model. Normally, each grid-related simulation data can construct a micro-model. However, in the method provided in this application embodiment, a corresponding micro-model is not constructed for each grid. Instead, after identifying the position most related to the impurity crushing effect, a micro-model (i.e., the second simulation model) that reflects the micro-changes of the rolled object during the rolling process is constructed based on the simulation data (i.e., target simulation parameters) associated with the grid at that position. In this way, the method provided in this application embodiment not only narrows the scope of microscopic analysis of the rolled object, but also improves the accuracy of the analysis, enabling a deeper understanding of the behavior of impurities during the rolling process, and thus accurately controlling their crushing effect.

[0054] According to some optional embodiments of this application, target simulation parameters are extracted from the set of simulation parameters. The target simulation parameters are determined by the following method: determining an optional grid corresponding to a preset position, wherein the preset position is located on the rolling object, and the preset position includes: a first type of position for reflecting the stress state of the rolling object during the rolling process, a second type of position for reflecting the thermodynamic changes of the rolling object during the rolling process, and a third type of position for reflecting the deformation uniformity of the rolling object during the rolling process; determining a target grid in the optional grid, and determining a set of simulation parameters distributed on the target grid as the target simulation parameters, wherein the target simulation parameters include: a first type of history data of thermal parameters and a second type of history data of mechanical parameters distributed in the target grid, wherein the first type of history data is used to reflect the change of thermal parameters with rolling time, and the second type of history data is used to reflect the change of mechanical parameters with rolling time.

[0055] The locations most relevant (closely relevant) to the impurity crushing effect include the surface, center (the first simulation model is a three-dimensional model, and the center is not the center of a certain face of the rolled object, but the volume center), head, and tail of the rolled object. Among them, the set of simulation parameters (the simulation operation results of the first simulation model) associated with the mesh (i.e., the selectable mesh) located on the surface of the rolled object (i.e., the first type of location) can accurately reflect the stress state of the rolled object during the rolling process. This is because, in the rolling process, the surface of the rolled object (plate or ingot) is in direct contact with the rolls and bears the maximum external force (such as friction, pressure, etc.). The manner and magnitude of these external forces directly affect the thickness and surface quality of the plate (the rolled object after the rolling operation). The set of simulation parameters (the simulation results of the first simulation model) associated with the mesh located at the center of the rolled object (i.e., the second type of position) can accurately reflect the thermodynamic changes of the rolled object during the rolling process. This is because, during rolling (cold rolling or hot rolling), the temperature distribution and heat conduction state at the center of the plate can more accurately reflect the overall thermodynamic changes of the rolled object (including changes caused by thermal parameters and changes caused by mechanical parameters). Since the head and tail of the plate experience different speed changes, temperature distributions, and contact conditions with the rolls during entry and exit from the rolling tool, the set of simulation parameters (the simulation results of the first simulation model) associated with the mesh located at the head and tail of the rolled object (i.e., the third type of position) can accurately reflect the deformation uniformity of the rolled object during the rolling process.

[0056] Therefore, in this embodiment, when extracting target simulation parameters, it is necessary to first determine the grid (selectable grid) located at the position most relevant to the impurity crushing effect (i.e., the preset position), and then determine one or more grids among the selectable grids as the (target) grids for generating the micro model; extract the simulation parameters associated with the target grids as the target simulation parameters for constructing the micro model. In the method provided in this application embodiment, the extracted target simulation parameters are used as the boundary conditions of the second simulation model. Therefore, the extracted target simulation parameters mainly include the history data of thermal parameters (i.e., the first type of history data) and the history data of mechanical parameters (i.e., the second type of history data) that comprehensively reflect the local thermo-mechanical coupling state of the plate. The history data of thermal parameters (i.e., the first type of history data) mainly includes: temperature history data, such as the temperature change curve of the rolled object with rolling time, which is used to describe the temperature change of the rolled object during the rolling process; the history data of mechanical parameters (i.e., the second type of history data) mainly includes: stress history data (such as the stress change curve of the rolled object with rolling time), strain history data (such as the deformation change curve of the rolled object with rolling time), speed history data, as well as stress peak value, strain rate, etc.

[0057] Using the above method, after determining the grid (i.e. the target grid) located at the position most relevant to the impurity crushing effect, an independent micro-model is constructed for each grid. By analyzing the micro-model, the micro-changes of the part of the rolled object represented by that grid during the rolling process, especially the changes in shape and position, can be analyzed. This can narrow the scope of micro-analysis, reduce the number of micro-models to be constructed, reduce the amount of data processing during micro-analysis, and improve the speed of screening rolling parameters.

[0058] It should be noted that the number of micro-models constructed above can be adjusted. The number of target meshes selected from the optional meshes can be adjusted according to the predefined number of inputs, thereby adjusting the number of micro-models constructed. If only one target mesh is selected from the optional meshes, only one micro-model will be constructed; if multiple target meshes are selected from the optional meshes, multiple micro-models will be constructed.

[0059] Optionally, a second simulation model is generated based on the target simulation parameters and rolling parameters, including: generating the second simulation model based on the material property parameters of the rolled object contained in the target simulation parameters and rolling parameters, wherein the material property parameters of the rolled object are used as property parameters of the second simulation model, and the second simulation model includes: a matrix domain, an impurity domain, and a void domain. The matrix domain is used to represent the microstructure of the target region, the impurity domain is used to represent the shape and location of impurities contained in the target region, and the void domain is used to represent the region in the target region where no filling material exists. The target region is the region covered by the main material in the target mesh, the target mesh is the mesh associated with the target simulation parameters, and the main material is the material with the highest proportion in the rolled object.

[0060] Microscopic models can be constructed using the Euler method (CEL). Figure 4 This is a schematic diagram of a microscopic model, such as... Figure 4 As shown, since the micro-model (i.e., the second simulation model) is built for each (target) mesh, the size of the micro-model is the same as the size of the mesh; for example, the mesh size is 1 mm. If the size of the microscopic model is 1 mm, then the size of the microscopic model is 1 mm. 1mm. When constructing the microscopic model, the spatial domain of the microscopic model is initialized according to the size and shape of the target mesh, such as... Figure 4As shown, the microscopic model comprises three main parts: the matrix domain, the impurity domain, and the void domain. The matrix domain represents the area in the target mesh covered by the dominant material, which is the material with the highest proportion in the rolled object. For example, if the rolled object is an aluminum alloy, the dominant material is aluminum and its alloying elements. The microstructure of the aluminum alloy matrix includes grain distribution, grain boundaries, and microstructural characteristics, forming the foundational region of the microscopic model. The impurity domain is the area covered by impurities in the target mesh. For example, if the rolled object is an aluminum alloy, the impurity could be iron particles. In this case, the impurity domain is the area covered by iron particles in the target mesh. The impurity domain is used to study the response of impurities under thermal and mechanical loads. The void domain in the microscopic model is the area in the target mesh that is not filled with material. However, the rolling operation causes deformation of the rolled object. As the rolled object deforms, the void domain may be filled with impurity materials and matrix materials. Therefore, simulation analysis of the void domain is significant for understanding the flow and deformation mechanisms of materials.

[0061] By using the above method, a microscopic model containing the aluminum matrix domain, impurity domain, and vacancy domain is established. Based on the microscopic model, the deformation and fracture behavior of impurity particles during the rolling process can be studied, which can improve the accuracy of microscopic analysis and realize precise control of the fracture behavior of second-phase impurity particles (such as iron particles).

[0062] Step S208: Determine the target simulation parameters associated with the second simulation model from the simulation parameter set of the first simulation model, and analyze the second simulation model according to the target simulation parameters to obtain simulation results. The simulation results are used to quantify the crushing effect of impurities contained in the rolled object.

[0063] After constructing the microscopic model (i.e., the second simulation model) in step S206, in step S208, target simulation parameters related to the microscopic model (i.e., the second simulation model) are determined from the simulation parameter set of the macroscopic model (i.e., the first simulation model). The simulation parameter set of the macroscopic model (i.e., the first simulation model) is obtained after performing simulation operations on the macroscopic model, and the target simulation parameters are parameters related to impurity fragmentation in the simulation parameter set. After adding the target simulation parameters as boundary conditions for the simulation calculation of the second simulation model, the analysis of the second simulation model is completed, and simulation results are obtained. Based on the simulation results, the fragmentation effect of impurities in the rolled object can be evaluated. For example, the degree to which impurities are fragmented into fine particles after rolling can be used to evaluate the fragmentation effect of the rolling operation corresponding to the rolling parameters provided in step S202.

[0064] Optionally, the second simulation model is analyzed according to the target simulation parameters to obtain simulation results, including: replacing the boundary conditions in the simulation operation parameters with the target simulation parameters to obtain the target simulation operation parameters, wherein the boundary conditions are used to represent the external environmental conditions that affect the dynamic changes of impurities during the rolling process; and performing simulation operations on the second simulation model using the target simulation operation parameters to obtain simulation results, wherein the simulation results include: the number of impurities and the size information of each impurity.

[0065] As mentioned in the above embodiments, in this embodiment, after determining the (target) mesh for constructing the microscopic model (i.e., the second simulation model) at the location most relevant (closely relevant) to the impurity fragmentation effect, a microscopic model is constructed for each selected target mesh. During the simulation of each microscopic model, the parameters (i.e., target simulation parameters) associated with the target mesh corresponding to the microscopic model and used to reflect the thermo-mechanical coupling state will be used as boundary conditions to be applied when simulating the microscopic model. Therefore, in this embodiment, before performing simulation analysis on the constructed microscopic model, the target simulation parameters (including temperature history data, stress history data, strain history data, etc.) extracted from the macroscopic model are integrated into a complete set of boundary conditions. Then, the target simulation parameters (including temperature history data, stress history data, strain history data, etc.) are used to replace the general boundary conditions used in the conventional method for microscopic model simulation analysis. Next, after completing the boundary condition replacement, the microscopic model is simulated and analyzed using the simulation parameters with replaced boundary conditions (i.e., the target simulation operation parameters). Under the new boundary conditions, the deformation, breakage and diffusion behavior of impurity particles under specific external environmental conditions (thermal conditions defined by the target simulation parameters) are simulated; thus completing the simulation analysis of the microscopic model.

[0066] In this embodiment, simulation operation parameters with replaced boundary conditions (i.e., target simulation operation parameters) are used to perform simulation analysis on the micro-model, which can more realistically and accurately reflect the local thermo-mechanical coupling state of the rolled object during the rolling process. The simulation analysis results of the obtained micro-model (i.e., simulation results) contain information on the number and size of impurities (the size of each impurity contained in the target mesh) that can quantify the impurity breakage effect. Therefore, the degree of impurity breakage and dispersion caused by the rolling operation corresponding to the rolling parameters given in step S202 can be quantitatively evaluated based on the simulation results of the micro-model.

[0067] If only one micro-model is constructed, the effect of rolling operation defined by a set of rolling parameters corresponding to that micro-model on impurity crushing is quantitatively evaluated based on the simulation results corresponding to that micro-model. If multiple micro-models are constructed, the average number of impurities and the average size of impurities are determined based on the multiple simulation results corresponding to the multiple micro-models. The effect of rolling operation defined by a set of rolling parameters corresponding to these multiple micro-models on impurity crushing is quantitatively evaluated based on the average number of impurities and the average size of impurities.

[0068] The method provided in this embodiment uses the simulation results of the macroscopic model as the boundary conditions used in the microscopic simulation operation. It can accurately analyze the dynamic changes of the second-phase impurities under rolling conditions, and quantify the crushing effect of the rolling operation on the impurities by using information on the number and size of the impurities. Compared with the single parameter adjustment method, it can more comprehensively consider the non-uniformity inside the rolled object, significantly improve the accuracy of impurity particle crushing control, and improve the rolling effect.

[0069] Step S210: Determine the target rolling parameter from the multiple sets of rolling parameters based on the multiple simulation results corresponding to the multiple sets of rolling parameters. Among them, the rolling operation corresponding to the target rolling parameter has the best effect on impurity crushing.

[0070] In the solution provided in this application embodiment, if a set of rolling parameters is received, the method described in steps S202 to S208 is only executed on the set of rolling parameters. In this case, the rolling effect produced by rolling the rolling object described in step S202 using the rolling process parameters provided in step S202 can be determined according to the simulation results output in step S208, and then the rolling effect of the set of rolling parameters can be evaluated.

[0071] If multiple sets of rolling parameters are received, the methods described in steps S202 to S208 are executed for each set of rolling parameters. Then, in step S210, after completing the macroscopic and microscopic simulations corresponding to the multiple sets of rolling parameters, the simulation results of different rolling parameters are compared to identify the set of rolling parameters with the optimal effect on impurity particle crushing (i.e., the target rolling parameters). The optimal crushing effect is determined by the number of impurities contained in the rolled object after rolling and the size of the largest impurity. The target rolling parameters determined in step S210 can minimize the risks of ingot cracking, rolling cracking, and uneven deformation while ensuring the overall performance of the rolled plate.

[0072] According to some optional embodiments of this application, the target rolling parameters are determined from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, including: determining the simulation result to be screened with the most impurities from multiple sets of simulation results; for each simulation result to be screened, determining the largest impurity size from multiple impurity sizes contained in the simulation result to be screened; determining the smallest impurity size from multiple largest impurity sizes; determining the target simulation result to be screened corresponding to the smallest impurity size; and determining a set of rolling parameters corresponding to the target simulation result to be screened as the target rolling parameters.

[0073] As mentioned in the above embodiments, if multiple sets of rolling parameters are received, the set of impurity parameters (i.e., target impurity parameters) with the best crushing effect on impurities can be selected based on the simulation results of the corresponding micro-model for each set. The following method can be used to quantify the crushing effect of rolling operation on impurities based on the simulation results of the micro-model: For the micro-model simulation results (i.e. simulation results) corresponding to different rolling parameters, the first step is to select based on the number of impurities contained in the simulation results. The more impurities there are, the better the crushing effect on impurities. Therefore, the simulation results with the most impurities are selected first as the objects to be selected for the next step (i.e., simulation results to be selected). Next, for each simulation result to be screened with the largest number of impurities, the smallest impurity size is determined from the largest impurity size contained in each simulation result to be screened. By comparing the largest impurity sizes contained in different simulation results to be screened, the simulation result to be screened with the best impurity crushing effect (i.e., the target simulation result to be screened) is determined. The smaller the impurity size, the better the impurity crushing effect. Therefore, after determining the smallest impurity size (i.e., the minimum impurity size) among multiple maximum impurity sizes, the rolling parameters that produce the simulation result corresponding to the minimum impurity size (i.e., the target simulation result to be screened) are determined as the target rolling parameters with the best impurity crushing effect.

[0074] The method provided in this embodiment not only quantifies the impact of different rolling parameters on the fragmentation effect of second-phase impurities, but also determines the optimal set of rolling parameters for impurity fragmentation, meeting the stringent requirements for impurity fragmentation degree and size control in sheet metal production. This significantly improves the controllability and efficiency of the rolling process, reduces potential adverse effects on sheet metal quality, and provides technical support for subsequent performance improvements and cost reductions in aluminum alloy sheets.

[0075] The method provided in this application, after evaluating the rolling effect that the rolling operation defined by the rolling parameters can produce by combining macroscopic and microscopic models, can further verify through experiments the actual crushing effect of the rolling parameters selected by the simulation calculation method on impurities. It can quickly and cost-effectively determine the optimal combination of rolling parameters (including rolling temperature, speed, and pressure) for impurity crushing, so as to promote the effective crushing of impurity particles and eliminate the rolling cracking and uneven deformation problems caused by second-phase impurities.

[0076] Figure 5 This is a comparison chart of the simulation results of the microscopic model corresponding to different rolling parameters. For example, in step S202, the following two sets of rolling parameters were input: The first set of rolling parameters includes: rolling process parameters: roll radius 0.5 m, roll length 1.8 m, friction coefficient 1, plate thickness 0.1 m, width 1.5 m, length 3 m, pass reduction 80%, number of passes 1, rolling speed 1.5 m / s, temperature 450℃; the rolling object is aluminum alloy, which contains iron particles as impurities. The material properties of the iron particles are: density 2600 kg / m³, elastic modulus 70 GPa, Poisson's ratio 0.33, specific heat capacity 1050 joules per kilogram per degree Celsius (J / (kg℃)), thermal conductivity 174 watts per meter per degree Celsius (W / (m℃)), and coefficient of linear expansion 2.2. The constitutive relations are as follows: stress 72.75 MPa - strain 0.00, stress 79.67 MPa - strain 0.01, stress 85.26 MPa - strain 0.02, stress 87.65 MPa - strain 0.03, stress 88.18 MPa - strain 0.05, stress 87.65 MPa - strain 0.07, stress 85.78 MPa - strain 0.14, stress 83.65 MPa - strain 0.28, stress 80.71 MPa - strain 0.48, stress 77.51 MPa - strain 0.67.

[0077] In the second set of rolling parameters, the reduction per pass is 20%, the number of passes is 4, and the material properties of the iron particles are: density 7870 kg / m³, elastic modulus 200 GPa, Poisson's ratio 0.29, specific heat capacity 448 J / (kg℃), thermal conductivity 20 W / (m℃), and coefficient of linear expansion 2.2. The constitutive relations are: stress 409 MPa - strain 0, stress 548 MPa - strain 0.79. These two sets of parameters are then used as the two sets of rolling parameters input in step S202. The remaining rolling process parameters and aluminum alloy material property parameters are the same as those in the first set of rolling parameters. These two sets of parameters are then used as the two sets of rolling parameters input in step S202. The methods described in steps S202 to S208 are performed on these two sets of rolling parameters to conduct simulation experiments (or actual rolling experiments), and the results are obtained. Figure 5 The simulation results of the microscopic model shown are as follows, Figure 5 In the diagram, A represents the simulation result of the micromodel corresponding to the first set of rolling parameters, and B represents the simulation result of the micromodel corresponding to the second set of rolling parameters. Figure 5 As shown, the rolling operation corresponding to the first set of rolling parameters has a better effect on crushing iron particles.

[0078] Through the above steps, it is possible to combine simulation operations at different levels to analyze the rolling effect produced by the input rolling parameters. The output of the macroscopic simulation is used as the boundary condition for the microscopic simulation. The boundary condition provides the key areas in the rolling operation. Simulating the microscopic model under the constraints of the boundary condition can not only reflect the changes in the environment of impurities, but also accurately simulate the range, thus achieving the purpose of providing rolling effect analysis and improving the efficiency of screening rolling parameters. Since the screening results can be used for actual production activities after the rolling parameters are screened, the rolling efficiency in actual production can also be improved.

[0079] Figure 6 This is a structural diagram of the apparatus for screening rolling parameters according to an embodiment of this application, as shown below. Figure 6 As shown, the device for screening rolling parameters includes: an acquisition module 60 for acquiring rolling parameters, wherein the rolling parameters include rolling process parameters and material property parameters of the rolled object; a first generation module 62 for generating a first simulation model based on the rolling parameters, wherein the first simulation model reflects the rolling process of the rolled object using the rolling process parameters; a second generation module 64 for generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model reflects the changes of impurities contained in the rolled object during the rolling process; an analysis module 66 for determining the target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the rolled object; and a determination module 68 for determining the target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal crushing effect on impurities.

[0080] use Figure 6 When the device for screening rolling parameters shown selects the rolling parameters with the optimal effect on impurity crushing, the acquisition module 60 receives the rolling parameters to be screened or verified for impurity crushing effect. These rolling parameters include: rolling process parameters (temperature range, speed range, and pressure, etc.) used to control the rolling operation and material property parameters of the rolled object. The first generation module 62 constructs a first simulation model for each set of hot rolling parameters, representing the rolling process of the rolled object from a macroscopic perspective. The second generation module 64 uses the grid-shaped rolled object from the first simulation model to construct a second simulation model describing the rolling process of the grid from a microscopic perspective. When constructing the microscopic model, the focus is mainly on the head, tail, volume center, and surface grids (i.e., the target grid) of the rolled object. Analysis module 66 extracts the history data related to the target grid management from the simulation parameters set of the first simulation model, and uses the extracted history data as the boundary conditions for the simulation operation of the micro-model to complete the simulation analysis of the micro-model; Determination module 68 is used to quantify the effect of each set of rolling parameters on impurity crushing based on the micro-model simulation results corresponding to each set of rolling parameters, so as to select the set of rolling parameters with the best effect on impurity crushing (i.e., the target rolling parameters) when there are multiple sets of rolling parameters.

[0081] It should be noted that, Figure 6 Preferred embodiments of the shown examples can be found in [reference needed]. Figure 2 The relevant descriptions of the embodiments shown will not be repeated here.

[0082] This application also provides a non-volatile storage medium storing a computer program, wherein the above-mentioned method for screening and rolling parameters is executed by running the computer program in the device where the non-volatile storage medium is located.

[0083] The aforementioned non-volatile storage medium is used to store a program that performs the following functions: acquiring rolling parameters, wherein the rolling parameters include rolling process parameters and material property parameters of the rolled object; generating a first simulation model based on the rolling parameters, wherein the first simulation model reflects the rolling process of the rolled object using the rolling process parameters; generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model reflects the changes of impurities contained in the rolled object during the rolling process; determining a target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the rolled object; determining a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal crushing effect on impurities.

[0084] This application also provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor is configured to execute the above-mentioned method of screening and rolling parameters through the computer program.

[0085] The processor in the aforementioned electronic device is used to run a program that performs the following functions: acquiring rolling parameters, wherein the rolling parameters include rolling process parameters and material property parameters of the object being rolled; generating a first simulation model based on the rolling parameters, wherein the first simulation model reflects the rolling process of the object being rolled using the rolling process parameters; generating a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model reflects the changes in impurities contained in the object being rolled during the rolling process; determining a target simulation parameter associated with the second simulation model from the set of simulation parameters of the first simulation model, and analyzing the second simulation model based on the target simulation parameter to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the object being rolled; determining a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the optimal crushing effect on impurities.

[0086] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the above-described method for screening and rolling parameters.

[0087] It should be noted that each module in the above-mentioned device for screening rolling parameters can be a program module (e.g., a set of program instructions to implement a certain function) or a hardware module. For the latter, it can be manifested in the following forms, but is not limited to them: each of the above modules is manifested as a processor, or the functions of each of the above modules are implemented by a processor.

[0088] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0089] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0093] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0094] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for screening rolling parameters, characterized in that, include: Obtain rolling parameters, wherein the rolling parameters include: rolling process parameters and material property parameters of the object being rolled; A first simulation model is generated based on the rolling parameters, wherein the first simulation model is used to reflect the process of rolling the object using the rolling process parameters; A second simulation model is generated based on the first simulation model and the rolling parameters, wherein the second simulation model is used to reflect the changes of impurities contained in the rolled object during the rolling process; In the simulation parameter set of the first simulation model, a target simulation parameter associated with the second simulation model is determined, and the second simulation model is analyzed according to the target simulation parameter to obtain simulation results. The simulation results are used to quantify the crushing effect of impurities contained in the rolled object. Based on the simulation results corresponding to the multiple sets of rolling parameters, a target rolling parameter is determined from the multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the best effect on crushing the impurities.

2. The method according to claim 1, characterized in that, A first simulation model is generated based on the rolling parameters, including: The rolling process parameters and the material property parameters of the rolled object are processed using finite element analysis software to obtain the first simulation model output by the finite element analysis software. The rolling process parameters include: the first geometric parameters and rolling operation parameters of the rolling tool. The material property parameters of the rolled object include: the second geometric parameters and physical property parameters of the rolled object. In the first simulation model, the rolled object is composed of multiple meshes.

3. The method according to claim 1, characterized in that, A second simulation model is generated based on the first simulation model and the rolling parameters, including: The simulation operation is performed on the first simulation model to obtain the simulation parameter set, wherein the simulation parameter set consists of multiple sets of simulation parameters, each set of simulation parameters corresponds to a grid, each set of simulation parameters is used to reflect the thermo-mechanical coupling state of a grid in the rolling process, and each grid represents a part of the rolling object; Extract the target simulation parameters from the set of simulation parameters; The second simulation model is generated based on the target simulation parameters and the rolling parameters, wherein each set of target simulation parameters is used to generate one second simulation model, and a set of target simulation parameters is associated with one mesh.

4. The method according to claim 3, characterized in that, The target simulation parameter is extracted from the set of simulation parameters, wherein the target simulation parameter is determined by the following method: Determine the optional grid corresponding to the preset position, wherein the preset position is located on the rolling object, and the preset position includes: a first type of position for reflecting the stress state of the rolling object during the rolling process, a second type of position for reflecting the thermodynamic changes of the rolling object during the rolling process, and a third type of position for reflecting the deformation uniformity of the rolling object during the rolling process; A target grid is determined in the optional grid, and a set of simulation parameters distributed on the target grid are determined as the target simulation parameters. The target simulation parameters include: a first type of history data of thermal parameters and a second type of history data of mechanical parameters distributed in the target grid. The first type of history data is used to reflect the change of the thermal parameters with rolling time, and the second type of history data is used to reflect the change of the mechanical parameters with rolling time.

5. The method according to claim 3, characterized in that, The second simulation model is generated based on the target simulation parameters and the rolling parameters, including: The second simulation model is generated based on the target simulation parameters and the material property parameters of the rolled object included in the rolling parameters. The material property parameters of the rolled object are used as attribute parameters of the second simulation model. The second simulation model includes a matrix domain, an impurity domain, and a void domain. The matrix domain is used to represent the microstructure of the target region. The impurity domain is used to represent the shape and location of impurities contained in the target region. The void domain is used to represent the region in the target region where no filling material exists. The target region is the region covered by the main material in the target mesh. The target mesh is the mesh associated with the target simulation parameters. The main material is the material with the highest proportion in the rolled object.

6. The method according to claim 1, characterized in that, The second simulation model is analyzed based on the target simulation parameters to obtain simulation results, including: The boundary conditions in the simulation operation parameters are replaced with the target simulation parameters to obtain the target simulation operation parameters, wherein the boundary conditions are used to represent the external environmental conditions that affect the dynamic changes of the impurities during the rolling process. The simulation operation is performed on the second simulation model using the target simulation operation parameters to obtain the simulation results, wherein the simulation results include: the number of impurities and the size information of each impurity.

7. The method according to claim 6, characterized in that, The target rolling parameters are determined from the multiple sets of rolling parameters based on the simulation results corresponding to the multiple sets of rolling parameters, including: Among the multiple sets of simulation results, determine the simulation result with the highest number of impurities to be screened; For each simulation result to be screened, the largest impurity size is determined among the multiple impurity sizes contained in the simulation result to be screened; The minimum impurity size is determined among the multiple maximum impurity sizes, the target simulation result to be screened corresponding to the minimum impurity size is determined, and a set of rolling parameters corresponding to the target simulation result to be screened is determined as the target rolling parameters.

8. An apparatus for screening rolling parameters, characterized in that, include: The acquisition module is used to acquire rolling parameters, wherein the rolling parameters include: rolling process parameters and material property parameters of the rolled object; A first generation module is used to generate a first simulation model based on the rolling parameters, wherein the first simulation model is used to reflect the process of rolling the object using the rolling process parameters; The second generation module is used to generate a second simulation model based on the first simulation model and the rolling parameters, wherein the second simulation model is used to reflect the changes of impurities contained in the rolled object during the rolling process; An analysis module is used to determine target simulation parameters associated with the second simulation model from the set of simulation parameters of the first simulation model, and to analyze the second simulation model according to the target simulation parameters to obtain simulation results, wherein the simulation results are used to quantify the crushing effect of impurities contained in the rolled object; The determination module is used to determine a target rolling parameter from multiple sets of rolling parameters based on multiple simulation results corresponding to multiple sets of rolling parameters, wherein the rolling operation corresponding to the target rolling parameter has the best crushing effect on the impurities.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a computer program, wherein the device containing the non-volatile storage medium executes the method for screening rolling parameters as described in any one of claims 1 to 7 by running the computer program.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of screening rolling parameters according to any one of claims 1 to 7 through the computer program.

11. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method for screening rolling parameters as described in any one of claims 1 to 7.

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