Thermal stress simulation method and system based on casting mold

Abstract

The invention relates to the field of advanced manufacturing, and discloses a thermal stress simulation method and system based on a casting mold, and the method comprises the steps: constructing a three-dimensional geometric model of the mold, carrying out the finite element mesh division of the model, and carrying out the quality evaluation of the divided mesh, thereby achieving the simulation of the thermal stress. Thermal physical performance parameters, mechanical performance parameters and mold boundaries are set for the constructed mold three-dimensional geometric model, whether changes of a temperature field, a stress field and a contact state meet convergence criteria or not is judged on the basis of analysis and calculation of the content of the mold three-dimensional geometric model, and the casting performance and the casting quality of the model are analyzed, so that the casting quality is improved. According to the method, the simulation evaluation coefficient is calculated and used for evaluating the casting performance and the casting quality of the model, and then the simulation evaluation coefficient and experimental data are compared and analyzed, so that the parameters of the model are adjusted, the simulation model can be continuously optimized, the simulation precision and reliability of the model are greatly improved, and the actual production requirements are better met.

Description

Technical Field

[0001] This invention relates to the field of advanced manufacturing technology, and more specifically to a method and system for simulating thermal stress based on casting molds. Background Technology

[0002] Traditional mold design relies heavily on engineers' experience and repeated trial and error. This results in long design cycles and makes it impossible to completely avoid thermal stress-related problems in the early stages of production, increasing trial costs and risks. With the development of computer technology and computational mechanics, numerical simulation methods, especially the finite element method, provide powerful tools for solving complex thermal stress problems. By creating three-dimensional models of the mold and casting, simulating heat transfer and stress evolution throughout the casting process, the thermal behavior of the mold can be predicted during the design phase, potential risks can be assessed, and the design scheme optimized, thus avoiding costly trial and error processes.

[0003] However, existing simulation methods still have the following drawbacks:

[0004] Firstly, existing simulation methods may result in significant differences between the 3D geometric model of the mold and the actual mold due to inaccurate scanning data and a lack of effective quality assessment of the mesh, which in turn affects the accuracy of subsequent analysis results.

[0005] Secondly, existing simulation methods may lack effective means to quickly locate and resolve convergence problems, and the evaluation of casting performance and quality may lack effective quantitative indicators and experimental verification, resulting in inaccurate evaluation results and failing to provide reliable guidance for actual production. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides a thermal stress simulation method and system based on casting molds to solve the problems existing in the background art.

[0007] This invention provides the following technical solution: a thermal stress simulation method based on casting molds, comprising:

[0008] S1: The actual casting mold is scanned by a 3D scanning device to obtain point cloud data of the mold surface, so as to construct a 3D geometric model of the mold and divide the 3D geometric model into a finite element mesh, thereby discretizing the model into a finite number of sub-mesh units.

[0009] S2: Used to collect the shape parameters of each sub-mesh unit, and then perform parallel analysis on the collected shape parameters of each sub-mesh unit to obtain the sub-mesh quality evaluation coefficient, which is used to evaluate the quality of each sub-mesh unit.

[0010] S3: Used to set the thermophysical performance parameters, mechanical performance parameters, and mold boundaries for the constructed three-dimensional geometric model of the mold;

[0011] S4: Based on the set thermophysical performance parameters, mechanical performance parameters and mold boundaries, analyze and calculate the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field and contact state meet the convergence criteria.

[0012] S5: Used to analyze the casting performance and casting quality of the model, and calculate the simulation evaluation coefficients to evaluate the casting performance and casting quality of the model.

[0013] S6: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

[0014] Preferably, step S1 involves using 3D modeling software to construct a 3D geometric model of the mold according to its actual size and shape, then importing the established 3D geometric model into finite element analysis software to perform mesh generation on the model, discretizing the model into a finite number of sub-mesh elements for numerical calculation.

[0015] Preferably, step S2 reads mesh information from the mesh cells, including the coordinates of all nodes, the node index list of each cell, and the cell type. It then iteratively processes each sub-mesh cell in the mesh. Based on the node index of the cell, it obtains the three-dimensional coordinates of all nodes constituting that cell from the node coordinate list. Using the node coordinates of that cell, it calculates all shape quality parameters in each mesh cell. Based on parallel analysis of all shape quality parameters in each sub-mesh cell, it calculates the sub-mesh quality evaluation coefficient. The specific calculation formula is as follows: ,in, This represents the quality evaluation coefficient of the i-th sub-mesh cell. This represents the weight of the j-th shape parameter of the i-th sub-mesh cell. This represents the j-th shape parameter value of the i-th sub-mesh cell. This represents the ideal value of the j-th shape parameter. This represents the maximum value of the j-th shape parameter;

[0016] By submesh quality evaluation coefficient Compared with the preset mesh quality assessment threshold Comparison is used to detect the quality of each sub-mesh element. If the sub-mesh cell is deemed to be of acceptable quality, then the quality of the sub-mesh cell is considered acceptable. If a sub-grid cell fails to meet the quality standard, its quality is considered unqualified. The quality of each sub-grid cell is then evaluated based on its sub-grid quality evaluation coefficient, and all cells meeting the standard are counted. The number of grid cells, denoted as And count the total number of all grid cells, denoted as N, based on all satisfying The proportion of defective mesh cells is calculated by combining the number of mesh cells in the given grid with the total number of cells in all grids. .

[0017] Preferably, the proportion of defective mesh cells is used to comprehensively evaluate the overall mesh quality, and the threshold for the proportion of defective cells is set based on simulation accuracy requirements and experience. ,like If the overall mesh quality is deemed unacceptable, the mesh needs to be re-generated. Then continue to find the smallest subgrid quality evaluation coefficient calculated in all grid cells. Value, denoted as The minimum subgrid quality evaluation coefficient With minimum mesh quality assessment threshold ,when When the mesh quality is satisfactory, it indicates that the overall mesh quality is acceptable and there is no need to re-mesh. If the mesh quality fails, it indicates that the overall mesh quality is unqualified and the mesh needs to be re-generated. The quality of the re-generated mesh needs to be re-evaluated until the mesh quality is qualified before proceeding to the next step of setting the model parameters.

[0018] Preferably, step S3 involves obtaining the thermophysical performance parameters of the mold material from the database, including thermal conductivity, specific heat capacity, and density, and inputting these parameters into the model using simulation software. It also involves obtaining the mechanical performance parameters of the mold material from the material handbook, including elastic modulus, Poisson's ratio, and yield strength, and inputting these parameters into the model using simulation software. Furthermore, the simulation software sets the initial temperature of the mold before casting begins, the pouring temperature and heat transfer coefficient of the molten metal, the cooling water temperature and the heat transfer coefficient of the cooling channel wall, the natural convection heat transfer coefficient of the mold-air contact surface, constraint conditions, and load conditions for the model.

[0019] Preferably, step S4 calculates the temperature field change of the mold based on the heat conduction equation, combined with thermophysical performance parameters and the thermal boundary conditions of the mold boundary. ;

[0020] Based on the thermo-mechanical coupling algorithm, the temperature field change value of the mold obtained from thermal analysis is combined with the mechanical property parameters of the material to calculate the stress field change value. ;

[0021] The interface interaction between the mold and the casting was simulated using a nonlinear contact algorithm, and the change in contact state was calculated. ;

[0022] By changing the temperature field value of the mold Convergence tolerance with respect to preset temperature field Compare the stress field changes. Convergence tolerance of the preset stress field Compare the contact state change values Convergence tolerance with preset contact state When comparing, and and If the changes in temperature field, stress field, and contact state satisfy the convergence criterion, the simulation results are considered to have converged, and iteration can be stopped. Otherwise, if the changes in temperature field, stress field, and contact state do not satisfy the convergence criterion, iteration needs to continue, the temperature field, stress field, and contact state need to be updated, and the change values ​​need to be recalculated until the temperature field, stress field, and contact state all satisfy the convergence criterion.

[0023] Preferably, step S5 obtains performance and quality index parameters of the casting, including shrinkage cavity volume fraction, maximum residual stress, maximum deformation, and contact area change rate. Based on the obtained performance and quality index parameters, it analyzes the casting performance and quality of the model and calculates the simulation evaluation coefficient. ,in, Indicates the volume fraction of shrinkage cavities. This indicates the maximum permissible volume fraction of shrinkage cavities. Indicates the maximum residual stress. This indicates the maximum allowable residual stress. represents the maximum deformation amount, This represents the maximum allowed deformation. This represents the rate of change of contact area. This indicates the maximum allowable rate of change in contact area. These represent the weighting coefficients.

[0024] Preferably, step S6 involves actually producing castings according to the process parameters set in the simulation, inspecting the actually produced castings, and obtaining the same performance and quality indicators as the simulation analysis, thereby calculating the experimental evaluation coefficient. Then, the simulation evaluation coefficient Z and the experimental evaluation coefficient Z are compared. The difference is calculated to obtain the error detection coefficient, and its calculation formula is as follows: ;

[0025] By comparing the error detection coefficient U with a preset error threshold A comparison is made to determine whether the model parameters need to be adjusted, when the error detection coefficient U... Preset error threshold If the error is detected, it indicates that the accuracy of the simulation model is low, and the model parameters need to be adjusted immediately. The error detection results should be fed back to the user immediately to prompt the user to adjust the model parameters.

[0026] To achieve the above objectives, the present invention provides the following technical solution: a thermal stress simulation system based on casting molds, implementing the above-mentioned thermal stress simulation method based on casting molds, including:

[0027] Model building module: The actual casting mold is scanned by a 3D scanning device to obtain point cloud data of the mold surface, so as to build a 3D geometric model of the mold, and the 3D geometric model is divided into finite element meshes, thereby discretizing the model into a finite number of sub-mesh units;

[0028] Mesh quality assessment module: Used to collect the shape parameters of each sub-mesh unit, and then perform parallel analysis on the collected shape parameters of each sub-mesh unit to obtain the sub-mesh quality assessment coefficient, which is used to assess the quality of each sub-mesh unit.

[0029] Parameter setting module: Used to set the thermophysical property parameters, mechanical property parameters, and mold boundaries for the constructed 3D geometric model of the mold;

[0030] Convergence detection module: Based on the set thermophysical performance parameters, mechanical performance parameters and mold boundaries, it analyzes and calculates the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field and contact state meet the convergence criteria.

[0031] Simulation evaluation module: used to analyze the casting performance and casting quality of the model, and calculate the simulation evaluation coefficients to evaluate the casting performance and casting quality of the model;

[0032] Error detection module: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

[0033] The technical effects and advantages of this invention are as follows:

[0034] (1) Based on the point cloud data of the mold surface obtained by the three-dimensional scanning equipment, a three-dimensional geometric model is constructed, and then a finite element mesh is divided. The quality of the divided mesh is effectively evaluated, and sub-mesh units with poor quality can be optimized, which improves the fit between the model and the actual mold. At the same time, the accuracy and stability of the calculation results are improved, thereby improving the model accuracy.

[0035] (2) Based on whether the changes in temperature field, stress field and contact state meet the convergence criteria, the calculation results are more accurate. The casting performance and casting quality of the model are analyzed, and the model parameters are adjusted by comparing and analyzing with experimental data. This improves the accuracy of casting performance and quality assessment, further enhances the accuracy and authenticity of the model, and better meets the needs of actual production. Attached Figure Description

[0036] Figure 1 This is a diagram illustrating the method steps of the present invention.

[0037] Figure 2 This is a system structure block diagram of the present invention. Detailed Implementation

[0038] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The thermal stress simulation method and system based on casting molds involved in the present invention are not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] like Figure 1 The embodiment shown provides a thermal stress simulation method based on casting molds, including:

[0040] S1: The actual casting mold is scanned using a 3D scanning device to obtain point cloud data of the mold surface, thereby constructing a 3D geometric model of the mold. The 3D geometric model is then divided into finite element meshes, thus discretizing the model into a finite number of sub-mesh units.

[0041] In this embodiment, S1 uses 3D modeling software to construct a 3D geometric model of the mold according to its actual size and shape. Then, the established 3D geometric model is imported into finite element analysis software to perform mesh generation on the model, discretizing the model into a finite number of sub-mesh elements for numerical calculation.

[0042] It should be specifically noted that, based on the size, shape, and surface characteristics of the casting mold, a suitable 3D scanning device should be selected. Commonly used 3D scanning devices include laser scanners, structured light scanners, and industrial CT scanners. The casting mold should then be scanned from all angles to obtain point cloud data of the mold surface. During scanning, attention should be paid to factors such as scanning angle and lighting conditions. Point cloud processing software should be used to clean, align, and optimize the obtained point cloud data. The processed point cloud data should be converted into a 3D geometric model using 3D modeling software. The generated 3D geometric model should be optimized and its dimensions verified to ensure that the model is consistent with the actual mold. The constructed 3D geometric model should then be imported into finite element analysis software. According to the material characteristics of the casting mold, the corresponding material properties, such as elastic modulus, Poisson's ratio, and density, should be set. According to the actual working conditions, the boundary conditions of the model, such as fixed constraints and loads, should be defined. The mesh generation function of the finite element analysis software should be used to discretize the 3D geometric model into a finite number of sub-mesh elements.

[0043] S2: Used to collect the shape parameters of each sub-grid unit, and then perform parallel analysis on the collected shape parameters of each sub-grid unit to obtain the sub-grid quality evaluation coefficient, which is used to evaluate the quality of each sub-grid unit.

[0044] In this embodiment, step S2 reads mesh information from the mesh cells, including the coordinates of all nodes, the node index list of each cell, and the cell type. It then iteratively processes each sub-mesh cell in the mesh. Based on the node index of the cell, it obtains the three-dimensional coordinates of all nodes constituting that cell from the node coordinate list. Using the node coordinates of that cell, it calculates all shape quality parameters in each mesh cell. Based on parallel analysis of all shape quality parameters in each sub-mesh cell, it calculates the sub-mesh quality evaluation coefficient. The specific calculation formula is as follows: ,in, This represents the quality evaluation coefficient of the i-th sub-mesh cell. This represents the weight of the j-th shape parameter of the i-th sub-mesh cell. This represents the j-th shape parameter value of the i-th sub-mesh cell. This represents the ideal value of the j-th shape parameter. This represents the maximum value of the j-th shape parameter;

[0045] By submesh quality evaluation coefficient Compared with the preset mesh quality assessment threshold Comparison is used to detect the quality of each sub-mesh element. If the sub-mesh cell is deemed to be of acceptable quality, then the quality of the sub-mesh cell is considered acceptable. If a sub-grid cell fails to meet the quality standard, its quality is considered unqualified. The quality of each sub-grid cell is then evaluated based on its sub-grid quality evaluation coefficient, and all cells meeting the standard are counted. The number of grid cells, denoted as And count the total number of all grid cells, denoted as N, based on all satisfying The proportion of defective mesh cells is calculated by combining the number of mesh cells in the given grid with the total number of cells in all grids. .

[0046] The proportion of defective mesh cells is used to comprehensively evaluate the overall mesh quality. The threshold for the proportion of defective cells is set based on simulation accuracy requirements and experience. ,like If the overall mesh quality is deemed unacceptable, the mesh needs to be re-generated. Then continue to find the smallest subgrid quality evaluation coefficient calculated in all grid cells. Value, denoted as The minimum subgrid quality evaluation coefficient With minimum mesh quality assessment threshold ,when When the mesh quality is satisfactory, it indicates that the overall mesh quality is acceptable and there is no need to re-mesh. If the mesh quality fails, it indicates that the overall mesh quality is unqualified and the mesh needs to be re-generated. The quality of the re-generated mesh needs to be re-evaluated until the mesh quality is qualified before proceeding to the next step of setting the model parameters.

[0047] S3: Used to set the thermophysical performance parameters, mechanical performance parameters, and mold boundaries for the constructed three-dimensional geometric model of the mold.

[0048] In this embodiment, step S3 obtains the thermophysical performance parameters of the mold material from the database, including thermal conductivity, specific heat capacity, and density. The simulation software inputs the obtained thermophysical performance parameters into the model. The simulation software also obtains the mechanical performance parameters of the mold material from the material handbook, including elastic modulus, Poisson's ratio, and yield strength. The simulation software inputs the obtained mechanical performance parameters into the model. In the simulation software, the initial temperature of the mold before casting begins, the pouring temperature and heat transfer coefficient of the molten metal, the cooling water temperature and the heat transfer coefficient of the cooling channel wall, the natural convection heat transfer coefficient of the mold-air contact surface, constraint conditions, and load conditions are set for the model.

[0049] S4: Based on the set thermophysical performance parameters, mechanical performance parameters, and mold boundaries, analyze and calculate the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field, and contact state meet the convergence criteria.

[0050] In this embodiment, step S4 calculates the temperature field change of the mold based on the heat conduction equation, combined with thermophysical performance parameters and the thermal boundary conditions of the mold boundary. ;

[0051] Based on the thermo-mechanical coupling algorithm, the temperature field change value of the mold obtained from thermal analysis is combined with the mechanical property parameters of the material to calculate the stress field change value. ;

[0052] The interface interaction between the mold and the casting was simulated using a nonlinear contact algorithm, and the change in contact state was calculated. ;

[0053] By changing the temperature field value of the mold Convergence tolerance with respect to preset temperature field Compare the stress field changes. Convergence tolerance of the preset stress field Compare the contact state change values Convergence tolerance with preset contact state When comparing, and and If the changes in temperature field, stress field, and contact state satisfy the convergence criterion, the simulation results are considered to have converged, and iteration can be stopped. Otherwise, if the changes in temperature field, stress field, and contact state do not satisfy the convergence criterion, iteration needs to continue, the temperature field, stress field, and contact state need to be updated, and the change values ​​need to be recalculated until the temperature field, stress field, and contact state all satisfy the convergence criterion.

[0054] It should be specifically noted that the method for analyzing the temperature field changes of the mold is as follows:

[0055] Step S401: First, calculate the temperature field for the next time step. The specific calculation formula is as follows: ,in, This represents the temperature field at the next time step. This represents the temperature field at the current time step. Indicates the time step. Indicates density, K represents specific heat capacity, and k represents thermal conductivity. This represents the heat flux divergence caused by the temperature gradient at time step n+1, and Q represents the heat generated per unit volume per unit time.

[0056] Step S402: The temperature field change value of the mold is obtained by calculating the difference between the temperature field of the next time step and the temperature field of the current time step. ;

[0057] The method for analyzing the stress field variation is as follows:

[0058] Step S411: Calculate the total strain based on the temperature field change and mechanical strain. ,in, Indicates the coefficient of thermal expansion of a material. This represents the temperature field change value of the mold. Indicates mechanical strain;

[0059] Step S412: Based on the total strain, calculate the stress for the next time step. ,in, This represents the elastic stiffness tensor of a material. Represents the tensor double dot product. This represents the total strain at the next time step. Represents a unit tensor;

[0060] Step S413: Calculate the stress field change value based on the stress at the next time step and the current stress. ,in, This represents the stress at the current time step;

[0061] The method for analyzing the change in contact state is as follows:

[0062] Step S421: The simulated interface contact state between the mold and the casting can be divided into a closed state, a sliding state, and a separated state. The closed state can be represented as... The sliding state can be represented as The separated state can be represented as ;

[0063] Step S422: Based on the contact state, contact pressure, contact force, contact area, and the analysis of the contact area, calculate the change value of the contact state. ,in, This represents the rate of change of contact pressure over time. Q represents the rate of change of contact force over time, and Q represents the contact area.

[0064] S5: Used to analyze the casting performance and quality of the model and calculate the simulation evaluation coefficients to evaluate the casting performance and quality of the model.

[0065] In this embodiment, step S5 acquires performance and quality parameters of the casting, including shrinkage cavity volume fraction, maximum residual stress, maximum deformation, and contact area change rate. Based on these acquired performance and quality parameters, it analyzes the casting performance and quality of the model and calculates the simulation evaluation coefficient. ,in, Indicates the volume fraction of shrinkage cavities. This indicates the maximum permissible volume fraction of shrinkage cavities. Indicates the maximum residual stress. This indicates the maximum allowable residual stress. represents the maximum deformation amount, This represents the maximum allowed deformation. This represents the rate of change of contact area. This indicates the maximum allowable rate of change in contact area. These represent the weighting coefficients.

[0066] S6: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

[0067] In this embodiment, step S6 involves actually producing castings according to the process parameters set in the simulation, inspecting the actual produced castings, and obtaining the same performance and quality indicators as the simulation analysis, thereby calculating the experimental evaluation coefficient. Then, the simulation evaluation coefficient Z and the experimental evaluation coefficient Z are compared. The difference is calculated to obtain the error detection coefficient, and its calculation formula is as follows: ;

[0068] By comparing the error detection coefficient U with a preset error threshold A comparison is made to determine whether the model parameters need to be adjusted, when the error detection coefficient U... Preset error threshold If the error is detected, it indicates that the accuracy of the simulation model is low, and the model parameters need to be adjusted immediately. The error detection results should be fed back to the user immediately to prompt the user to adjust the model parameters.

[0069] like Figure 2 The embodiment shown provides an implementation system for a thermal stress simulation method based on casting molds, including a model building module, a mesh quality evaluation module, a parameter setting module, a convergence detection module, a simulation evaluation module, and an error detection module. The model building module is connected to the mesh quality evaluation module, the mesh quality evaluation module is connected to the parameter setting module, the parameter setting module is connected to the convergence detection module, the convergence detection module is connected to the simulation evaluation module, and the simulation evaluation module is connected to the error detection module.

[0070] Model building module: The actual casting mold is scanned by a 3D scanning device to obtain point cloud data of the mold surface, so as to build a 3D geometric model of the mold, and the 3D geometric model is divided into finite element meshes, thereby discretizing the model into a finite number of sub-mesh units;

[0071] Mesh quality assessment module: Used to collect the shape parameters of each sub-mesh unit, and then perform parallel analysis on the collected shape parameters of each sub-mesh unit to obtain the sub-mesh quality assessment coefficient, which is used to assess the quality of each sub-mesh unit.

[0072] Parameter setting module: Used to set the thermophysical property parameters, mechanical property parameters, and mold boundaries for the constructed 3D geometric model of the mold;

[0073] Convergence detection module: Based on the set thermophysical performance parameters, mechanical performance parameters and mold boundaries, it analyzes and calculates the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field and contact state meet the convergence criteria.

[0074] Simulation evaluation module: used to analyze the casting performance and casting quality of the model, and calculate the simulation evaluation coefficients to evaluate the casting performance and casting quality of the model;

[0075] Error detection module: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

[0076] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0077] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A thermal stress simulation method based on casting molds, characterized in that, include: S1: The actual casting mold is scanned by a 3D scanning device to obtain point cloud data of the mold surface, so as to construct a 3D geometric model of the mold and divide the 3D geometric model into a finite element mesh, thereby discretizing the model into a finite number of sub-mesh units. S2: Used to collect the shape parameters of each sub-mesh unit, and then perform parallel analysis on the collected shape parameters of each sub-mesh unit to obtain the sub-mesh quality evaluation coefficient, which is used to evaluate the quality of each sub-mesh unit. S3: Used to set the thermophysical performance parameters, mechanical performance parameters, and mold boundaries for the constructed three-dimensional geometric model of the mold; S4: Based on the set thermophysical performance parameters, mechanical performance parameters and mold boundaries, analyze and calculate the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field and contact state meet the convergence criteria. S5: Used to analyze the casting performance and casting quality of the model, and calculate the simulation evaluation coefficients to evaluate the casting performance and casting quality of the model. S6: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

2. The thermal stress simulation method based on casting molds according to claim 1, characterized in that, S1 uses 3D modeling software to construct a 3D geometric model of the mold according to its actual size and shape. Then, the established 3D geometric model is imported into finite element analysis software to perform mesh generation on the model, discretizing the model into a finite number of sub-mesh elements for numerical calculation.

3. The thermal stress simulation method based on casting molds according to claim 2, characterized in that, S2 reads mesh information from the mesh cells, including the coordinates of all nodes, the node index list of each cell, and the cell type. It iteratively processes each sub-mesh cell, retrieving the 3D coordinates of all nodes constituting that cell from the node coordinate list based on the cell's node index. Using these coordinates, it calculates all shape quality parameters for each mesh cell. Based on parallel analysis of all shape quality parameters in each sub-mesh cell, it calculates the sub-mesh quality evaluation coefficient. The specific calculation formula is as follows: ,in, This represents the quality evaluation coefficient of the i-th sub-mesh cell. This represents the weight of the j-th shape parameter of the i-th sub-mesh cell. This represents the j-th shape parameter value of the i-th sub-mesh cell. This represents the ideal value of the j-th shape parameter. This represents the maximum value of the j-th shape parameter; By submesh quality evaluation coefficient Compared with the preset mesh quality assessment threshold Comparison is used to detect the quality of each sub-mesh element. If the sub-mesh cell is deemed to be of acceptable quality, then the quality of the sub-mesh cell is considered acceptable. If a sub-grid cell fails to meet the quality standard, its quality is considered unqualified. The quality of each sub-grid cell is then evaluated based on its sub-grid quality evaluation coefficient, and all cells meeting the standard are counted. The number of grid cells, denoted as And count the total number of all grid cells, denoted as N, based on all satisfying The proportion of defective mesh cells is calculated by combining the number of mesh cells in the given grid with the total number of cells in all grids. .

4. The thermal stress simulation method based on casting molds according to claim 3, characterized in that, The proportion of defective mesh cells is used to comprehensively evaluate the overall mesh quality. The threshold for the proportion of defective cells is set based on simulation accuracy requirements and experience. ,like If the overall mesh quality is deemed unacceptable, the mesh needs to be re-generated. Then continue to find the smallest subgrid quality evaluation coefficient calculated in all grid cells. Value, denoted as The minimum subgrid quality evaluation coefficient With minimum mesh quality assessment threshold ,when When the mesh quality is satisfactory, it indicates that the overall mesh quality is acceptable and there is no need to re-mesh. If the mesh quality fails, it indicates that the overall mesh quality is unqualified and the mesh needs to be re-generated. The quality of the re-generated mesh needs to be re-evaluated until the mesh quality is qualified before proceeding to the next step of setting the model parameters.

5. The thermal stress simulation method based on casting molds according to claim 4, characterized in that, S3 obtains the thermophysical performance parameters of the mold material from the database, including thermal conductivity, specific heat capacity, and density. The simulation software inputs the obtained thermophysical performance parameters into the model. It also obtains the mechanical performance parameters of the mold material from the material handbook, including elastic modulus, Poisson's ratio, and yield strength. The simulation software inputs the obtained mechanical performance parameters into the model. In the simulation software, the initial temperature of the mold before casting begins, the pouring temperature and heat transfer coefficient of the molten metal, the cooling water temperature and the heat transfer coefficient of the cooling channel wall, the natural convection heat transfer coefficient of the mold-air contact surface, constraint conditions, and load conditions are set for the model.

6. The thermal stress simulation method based on casting molds according to claim 5, characterized in that, S4 calculates the temperature field change of the mold based on the heat conduction equation, combined with thermophysical performance parameters and the thermal boundary conditions of the mold boundary. ; Based on the thermo-mechanical coupling algorithm, the temperature field change value of the mold obtained from thermal analysis is combined with the mechanical property parameters of the material to calculate the stress field change value. ; The interface interaction between the mold and the casting was simulated using a nonlinear contact algorithm, and the change in contact state was calculated. ; By changing the temperature field value of the mold Convergence tolerance with respect to preset temperature field Compare the stress field changes. Convergence tolerance of the preset stress field Compare the contact state change values Convergence tolerance with preset contact state When comparing, and and If the changes in temperature field, stress field, and contact state satisfy the convergence criterion, the simulation results are considered to have converged, and iteration can be stopped. Otherwise, if the changes in temperature field, stress field, and contact state do not satisfy the convergence criterion, iteration needs to continue, the temperature field, stress field, and contact state need to be updated, and the change values ​​need to be recalculated until the temperature field, stress field, and contact state all satisfy the convergence criterion.

7. The thermal stress simulation method based on casting molds according to claim 6, characterized in that, S5 obtains performance and quality parameters of the casting, including shrinkage cavity volume fraction, maximum residual stress, maximum deformation, and contact area change rate. Based on these parameters, it analyzes the casting performance and quality of the model and calculates the simulation evaluation coefficient. ,in, Indicates the volume fraction of shrinkage cavities. This indicates the maximum permissible volume fraction of shrinkage cavities. Indicates the maximum residual stress. This indicates the maximum allowable residual stress. represents the maximum deformation amount, This represents the maximum allowed deformation. This represents the rate of change of contact area. This indicates the maximum allowable rate of change in contact area. These represent the weighting coefficients.

8. The thermal stress simulation method based on casting molds according to claim 7, characterized in that, S6 involves producing castings according to the process parameters set in the simulation, inspecting the actual castings, and obtaining the same performance and quality indicators as the simulation analysis, thereby calculating the experimental evaluation coefficient. Then, the simulation evaluation coefficient Z and the experimental evaluation coefficient Z are compared. The difference is calculated to obtain the error detection coefficient, and its calculation formula is as follows: ; By comparing the error detection coefficient U with a preset error threshold A comparison is made to determine whether the model parameters need to be adjusted, when the error detection coefficient U... Preset error threshold If the error is detected, it indicates that the accuracy of the simulation model is low, and the model parameters need to be adjusted immediately. The error detection results should be fed back to the user immediately to prompt the user to adjust the model parameters.

9. A thermal stress simulation system based on casting molds, implementing the thermal stress simulation method based on casting molds as described in any one of claims 1-8, characterized in that, include: Model building module: The actual casting mold is scanned by a 3D scanning device to obtain point cloud data of the mold surface, so as to build a 3D geometric model of the mold, and the 3D geometric model is divided into finite element meshes, thereby discretizing the model into a finite number of sub-mesh units; Mesh quality assessment module: Used to collect the shape parameters of each sub-mesh unit, and then perform parallel analysis on the collected shape parameters of each sub-mesh unit to obtain the sub-mesh quality assessment coefficient, which is used to assess the quality of each sub-mesh unit. Parameter setting module: Used to set the thermophysical property parameters, mechanical property parameters, and mold boundaries for the constructed 3D geometric model of the mold; Convergence detection module: Based on the set thermophysical performance parameters, mechanical performance parameters and mold boundaries, it analyzes and calculates the contents of the three-dimensional geometric model of the mold to determine whether the changes in temperature field, stress field and contact state meet the convergence criteria. Simulation evaluation module: used to analyze the casting performance and casting quality of the model, and calculate the simulation evaluation coefficients to evaluate the casting performance and casting quality of the model; Error detection module: By comparing and analyzing the simulation evaluation coefficients with the experimental data, error detection coefficients are obtained, which are used to detect errors in the simulation model and adjust the model parameters accordingly.

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